Oliver Carsten

 (conventional, hybrid, electrical)and vehicles types (passenger cars, vans, trucks, buses) will be tested in order to optimize the driver-powertrain-environment feedback loop. The ultimate goal is to deliver the most appropriate eco-driving advice or feedback for any given situation. This document summarizes the information related to the vehicles and test scenarios for the different VMCs (Vehicle Management Centres) at this point in the project. During the next months the information contained in this document will be complemented with the results of the next activities and deliverables.

Index of figures

Index of tables

Glossary of terms

Term Description Application

An application is a piece of software running on a system for implementing one or more functions. Situation A situation is one specific level or a combination of more specific levels of situational variables.

Test scenario

Test scenario is the test setup in which scenarios are triggered in order to collect data specific to this scenario. Function A function is the implementation of a set of rules to achieve a specified goal.

Pilot

Piloting is the final stage in system or function testing prior to full-scale trialling.

System

A system is a combination of hardware and software enabling one or more functions.

Baseline

Baseline is a scenario with system under evaluation "turned off". Hypothesis A hypothesis is a specific question which can be tested using statistical methods by analysing measures and performance indicators.

Acronyms

Introduction 1.1 Background information on ecoDriver

ecoDriver addresses the need to consider the human element when encouraging "green" driving, since driver behaviour is a critical element in energy efficiency. The focus of the project is on technology working with the driver. The project aims to deliver the most effective feedback to drivers on green driving by optimising the driver-powertrain-environment feedback loop. It will carry out a substantial programme of work to investigate how best to win the support of the driver to obtain the most energy-efficient driving style for best energy use.

Feedback coverage will include preview of the upcoming situation, optimising the current driving situation as well as post-drive feedback and learning. The project will address this across a wide range of vehicles (cars, light trucks and vans, medium and heavy trucks and buses) covering both individual and collective transport, and will optimise feedback to drivers for both nomadic devices and built-in systems and compare the effectiveness of each. The project will evaluate HMIs and feedback to drivers via both nomadic devices and built-in systems and compare the effectiveness of each. In each case a range of HMIs and feedback styles will be assessed. The project aims to examine driving not only with current and near-term powertrains but also with a full range of future vehicles, including various types of hybrid and plug-in electric vehicles.

A comprehensive evaluation will be carried out both in the laboratory (a variety of driving simulators) and in real world driving in both the private and fleet contexts. Scenarios will be developed to assess the implications for the future effectiveness of green driving support. The target of ecoDriver is to deliver a 20% improvement in energy efficiency by autonomous means alone, which opens up the possibility of greater than 20% savings in combination with cooperative systems.

Scope and objectives of SP3: Real-World Trials

SP3 has the goal to organize and carry out real-world trials over a wide variety of fuel-efficiency oriented systems and methods, including the prototype systems produced in SP1. The ecoDriver systems considered in the project are the following ones:

 Full ecoDriver system
This version of the system uses as inputs all available sensors and information available in the vehicles. The system will be integrated in the vehicle (see MS28 still under development).

 Aftermarket system

The aftermarket system is based on an Android device with a limited number of inputs to be used by the algorithm: accelerometer, GPS and OBD (i.e. not connected to the CAN of the vehicle or other sensors) (see MS28 still under development).

 Navigation system

This version is based on the navigation system of TomTom containing also a limited set of sensors at the input (e.g. Map, GPS and OBD) (see MS28 still under development).

The three different kinds of systems will be tested in seven countries: Spain, France, UK, The Netherlands, Germany, Sweden and Italy as shown in Figure 1. The organization of this SP will be arranged through different VMCs (Vehicle Management Centres), located in the home country where the trials will take place. In Annex B a summary of the main characteristics of the different fleets in each VMC is included. Once the tests will be carried out, SP3 will provide data to other SPs for use in the implementation of models and the evaluation of effectiveness of the tested solutions.

To that end, SP3 will:

 Refine the testing protocol provided by SP4 for each individual testing place. o Existing types of powertrain on the short, mid and long term across Europe: petrol and diesel Internal Combustion Engines (ICEs), Hybrid Vehicles and Electric Vehicles.

o Different types of drivers and driver behaviour: professional fleet drivers, private drivers, etc.

 Collect and provide data to SP2 and SP4 on the requested signals and / or indicators for later modelling and evaluation.

Scope and structure of the report

The main aim of this document is the definition of Use Cases and Scenarios per VMC, taking into account as a reference the general Use Cases defined for the ecoDriver system within the WP13 (see deliverable D13.1).

This version of the report was prepared with the information available at this moment in the project and taking into account that the discussions about the final implementation of the system are on course. As soon as the definition of the system is closed, more detailed information about the scenarios and uses cases will be provided by the VMCs in the following months.

The report will start by briefly explaining the Trial preparation work package (WP32) overview. The links between the tasks within this work package and their relation to other work packages are described with the help of a flowchart.

In chapter 3, the term use case is defined and explained in a detailed level. The description is followed by a table summarizing all uses cases in the project. The detailed description of each use case and scenarios will be the bigger part of this report.

For defining the scenario for each test site, the environmental variables outlined in work package 41 are described in a detailed level for each VMC in chapter 4. The scenario definitions will consist of defining the test routes, road type, traffic conditions, weather conditions, time of the day and season of the year.

Trial preparation work package (WP32) overview

The objective of trial preparation work package is to prepare the different VMCs in terms of the following elements:  Use cases adaptation to VMC  Specific tools to be used for acquiring, storing, enriching and analysing the data  Selection of Vehicles  Selection of Drivers Within WP32, the elements mentioned above will be focused from the VMC's point of view, and will provide the necessary tools and equipment to WP34 to collect data for other SPs. These tools will be integrated and tested in WP33. The connection between the tasks and work packages is shown in Figure 2.

The first task is to adapt the use cases to the test scenarios per test site. This task receives feedback from SP1 and adapts the Use Cases defined in the evaluation plan in WP13 to the specific characteristics of each VMC. Experimental procedures defined in WP31 will also be taken into account.

Interaction with other work packages

Figure 2 shows the interactions within Task 32.1 'Test Scenarios and Use Case Definition per Test Site' and other WPs and tasks. The general approach to be followed during the development of test scenarios (scenarios to be implemented in the driving simulators and the scenarios to be implemented in real environment tests) is defined in WP13. In this work package the general use cases for the ecoDriver system were defined. This use cases will be used as a base in the task T32.1 in which the mapping of the use cases to be tested in each test site will be done. Not all test sites are going to test all use cases as they have different fleets of vehicles (passenger cars, trucks, buses, etc…) and different configurations of the ecoDriver systems will be implemented (full ecoDriver solution, nomadic solution or after-market solution) (see Annex B for additional information of the fleets). In T32.1 the first step followed was the identification of use cases per site, from the point of view of field trials implementation (see in Section 3 the use cases per VMC). In a second step, the scenarios for each VMC were identified and described; taking into account the particular use cases to be tested in each VMC (see in Section 4 the scenarios per VMC).

The other main input for the Task 32.1 originates from WP41. This input comes in two ways: indirectly through WP31 and directly from WP41. The generic research questions, hypothesis, indicators, measurements and protocols have been defined in WP41 (they could be checked in D41.1). In WP31, the work focused is mapped to the general protocols defined in the test sites, each one with their specific characteristics. Once the specific protocols are mapped by the test site, the information is directed to Task 32.1 where the test site leaders define the most suitable scenarios taking into account the application of the protocols.

On the other side, an important part of the scenarios are the hypotheses that are going to be tested.

Taking the general hypothesis defined in WP41 as a starting point, the hypotheses objective are identified and mapped for each scenario in task 32.1.

Within Task 32.1, each VMC leader will be responsible to search for the best possible routes and / or possible areas where to test in real life conditions in the ecoDriver concept. These routes will determine possible candidates to participate in the test and will also be determined by the type of vehicles foreseen for each VMC. The output of Task 32.1 will serve as an input to Task 32. All the results obtained in WP32 will contribute to WP33 where implementing and performing the tests in the real environment is carried out.

Use cases

A use case is a methodology used in system analysis to identify, clarify, and organize system requirements. (Hoffer, George and Valaicg, 2002) describe a use case as follows: "Use case is made up of a set of possible sequences of interactions between systems and users in a particular environment and related to a particular goal. It consists of a group of elements (for example, classes and interfaces) that can be used together in a way that will have an effect larger than the sum of the separate elements combined'. This definition is applicable to all aspects of fields. A more specific definition in relation to this project is the one by COMeSafety,

According to COMeSafety, a use-case "defines a subset of functionalities of a system. It is primarily used to define the behaviour of a system without specifying its internal structure" (COMeSafety).

The general rule is that a use case should contain all system activities that have significance to the users. A use case can be thought of as a collection of possible scenarios related to a particular goal. Indeed, the use case and goal are sometimes considered to be synonymous. The main goal in the ecoDriver project is reducing CO 2 traffic emissions by 20%. This goal is rather general and needs to be defined in more detail.

Description of use case

A common understanding in describing a use case is having a unique name suggesting its purpose.

The name should express what happens when the use case is performed. It is recommended the name to be an active phrase, e.g. speed assistance. It is convenient to include a reference number to indicate how it relates to other use cases. Each use case should have a description that describes the main business goals of the use case.

Use cases of the ecoDriver project which are currently laid down in a more general way need to be refined into a reasonable level of detail. The FESTA handbook handles use case refinement by describing so-called situations. A situation is a combination of certain characteristics of a use case (FESTA, FESTA Handbook version 4, 2011). Situations can be derived from use cases compiling a reasonable permutation of the use. The detailed description of the use case and scenario in return triggers the development of specific hypotheses for later analysis.

There are two types of situational descriptors which are used in evaluating a system or function; static and dynamic descriptors. The static situational descriptors are constant and do not change significantly during the course of the entire one ride, like gender and education level of the driver. Dynamic descriptors change during a ride of the vehicle/simulator, such as the system action status (system on or off), the traffic conditions, road characteristics or the environmental situation. The situational descriptors are selected in a way that relevant information can be gathered to distinguish between main differences while evaluating the systems under consideration.

In the FOT project a set of rules had been laid out for the design of the situations for a FOT. Those rules are:

1. Situations are not allowed to overlap.

2. The sum of all situations should describe the complete use case.

3. Baseline: the same situation without the use of the systems (system off or not present) is defined as the baseline. The baseline is the basis for the benefit assessment of the system and the comparison between systems. Therefore, for the same use case, there can be many baselines depending on the number of situations. 4. Variability of situation parameters: depending on the point of view (user, trip, vehicle, etc.), attributes describing a situation can vary considerably or not.

The process of defining the use cases will help the trial preparation of the ecoDriver for the next steps, namely:

1. The definition of the research questions and hypotheses 2. The identification of the required indicators.

Most of the indicators, hypotheses and research questions have been discussed in previous meetings and are available in work package 41 [START_REF] Kircher | D41.1: Performance indicators and ecoDriver test design[END_REF]. For an easy reference to the reader the identified hypotheses for this project are provided in Annex A: List of ecoDriver Hypotheses. The scenario, as defined at this stage, are not detailed enough for data analysis purposes. For this reason, after the definition of the indicators, the scenarios (and their situations) need to be further described in terms of events for data analysis purposes.

Individual use cases

In total 51 use cases are identified for this project, Table 1 summarises all of them. The detailed description of each use case is based on the template shown in Annex C. Connected Hypotheses H02, H16, H25, H30 (TBD, related to feed-forward)

Partner

Description

Using map and sensor data, the system is able to anticipate the vehicle's path. Approaching relevant traffic signs, the system provides feedforward information in order to support the driver in anticipatory 1 driving.

Relevant traffic signs for this feature are speed limits and stop signs.

System status

The system needs to be turned ON.

System action status

The system provides in-trip advice and information.

Characteristics

Interaction between systems The system uses IKA's powertrain model from SP2.

Frequency

Drivers are briefed about the system and its features.

Driver characteristics and status

Driver specification

No requirements on drivers.

Environmental conditions

Traffic conditions

The described feature works within regular traffic. High traffic densities like traffic jams or stop-and-go will cause the feature to be ineffective.

Weather conditions

The described feature works within regular weather conditions as long as driving safety is not compromised.

Geographical characteristics

The described feature does not require special geographical characteristics.

Partner name IKA Identification and description

Use case name Information on road geometry

Use case abbreviation EcoD-UC-02-IKA

Connected systems Powertrain model and ecoDriver system

Connected Hypotheses H02, H16, H25, H30 (TBD, related to feed-forward)

1 Anticipatory driving is a key concept of ecodriving and refers to the driver's ability to make smooth and gradual changes to their acceleration based on their prediction of future events.

Partner name IKA

Description

Using map and sensor data, the system is able to anticipate the vehicle's path. Approaching relevant structural and geographical conditions the system provides feed-forward information in order to support the driver in anticipatory driving.

Relevant road geometries and structural conditions (determined by curvature data if available) may be for example upcoming curves, road inclines or roundabouts.

System and vehicle specification

System status

The system needs to be turned ON.

System action status

The system provides in-trip advice and information.

Characteristics

Interaction between systems The system uses IKA's powertrain model from SP2.

Frequency

Drivers are briefed about the system and its features.

Driver characteristics and status

Driver specification

No certain requirements on drivers.

Environmental conditions

Traffic conditions

The described feature works within regular traffic. High traffic densities like traffic jams or stop-and-go will cause the feature to be ineffective.

Weather conditions

The described feature works within regular weather conditions as long as driving safety is not compromised.

Geographical characteristics

Geographical characteristics like smooth hills and road bends are necessary for this use case.

Partner name IKA Identification and description

Use case name Information on surrounding traffic

Use case abbreviation EcoD-UC-03-IKA

Connected systems

Powertrain model and ecoDriver system Connected Hypotheses H02, H16, H25, H30 (TBD, related to feed-forward)

Description

Using sensor data, the system is able to monitor the vehicle's surroundings and detect other road users within its path. Approaching other vehicles driving upfront, the system provides feed-forward information in order to support the driver in anticipatory driving.

System and vehicle specification

System status

The system needs to be turned ON.

System action status

The system provides in-trip advice and information.

Characteristics

Interaction between systems The system uses IKA's powertrain model from SP2.

Frequency

Drivers are briefed about the system and its features.

Driver characteristics and status

Driver specification

No certain requirements on drivers.

Environmental conditions

Traffic conditions

The described feature works within regular traffic. High traffic densities like traffic jams or stop-and-go will cause the feature to be ineffective.

Weather conditions

The described feature works within regular weather conditions as long as driving safety is not compromised.

Geographical characteristics

The described feature does not require special geographical characteristics.

Partner name IKA Identification and description

Use case name Semi-autonomous support on traffic signs

Use case abbreviation EcoD-UC-04-IKA

Connected systems

Powertrain model and ecoDriver system Connected Hypotheses H02, H16, H25, H30 (TBD, related to feed-forward)

Description

Using map and sensor data, the system is able to anticipate the vehicle's path. Approaching relevant traffic signs, the system provides feed-forward information in order to support the driver in anticipatory driving. If the driver reacts, the system automatically adjusts the current velocity (based on feed-forward information).

Relevant traffic signs for this feature are speed limits and stop signs.

System status

The system needs to be turned ON.

System action status

The system provides in-trip advice and semi-autonomous driving support.

Characteristics

Interaction between systems The system uses IKA's powertrain model from SP2.

Frequency

Drivers are briefed about the system and its features.

Driver characteristics and status

Driver specification

No certain requirements on drivers.

Environmental conditions

Traffic conditions

The described feature works within regular traffic. High traffic densities like traffic jams or stop-and-go will cause the feature to be ineffective.

Weather conditions

The described feature works within regular weather conditions as long as driving safety is not compromised.

Geographical characteristics

The described feature does not require special geographical characteristics.

Partner name IKA Identification and description

Use case name Semi-autonomous support on road geometry

Use case abbreviation EcoD-UC-05-IKA

Connected systems

Powertrain model and ecoDriver system Connected Hypotheses H02, H16, H25, H30 (TBD, related to feed-forward)

Description

Using map and sensor data, the system is able to monitor and anticipate the vehicle's path. Approaching relevant structural and geographical conditions the system provides feed-forward information in order to support the driver in anticipatory driving. If the driver reacts, the system automatically 2 adjusts the current velocity (based on feed-forward information).

Relevant road geometries and structural conditions (determined by curvature data if available) may be for example upcoming curves, road inclines or roundabouts.

System and vehicle specification

System status

The system needs to be turned ON.

System action status

The system provides in-trip advice and semi-autonomous driving support.

Characteristics

Interaction between systems The system uses IKA's powertrain model from SP2.

Frequency

Drivers are briefed about the system and its features.

Driver characteristics and status

Driver specification

No certain requirements on drivers.

Environmental conditions

Traffic conditions

The described feature works within regular traffic. High traffic densities like traffic jams or stop-and-go will cause the feature to be ineffective.

Weather conditions

The described feature works within regular weather conditions as long as driving safety is not compromised.

Geographical characteristics

Geographical characteristics like smooth hills and road bends are necessary for this use case.

Identification and description

2 But can be over-ridden by the driver at any time

Partner name IKA

Use case name Semi-autonomous support on traffic

Use case abbreviation EcoD-UC-06-IKA

Connected systems Powertrain model and ecoDriver system

Connected Hypotheses H02, H16, H25, H30 (TBD, related to feed-forward)

Description

Using sensor data, the system is able to monitor the vehicle's surroundings and detect other road users within its path. Thus, the system provides feed-forward information on other vehicles driving upfront in order to support the driver in anticipatory driving. If the driver reacts, the system automatically adjusts the current velocity (based on feed-forward information).

System and vehicle specification

System status

The system needs to be turned ON.

System action status

The system provides in-trip advice and semi-autonomous driving support.

Characteristics

Interaction between systems The system uses IKA's powertrain model from SP2.

Frequency

Drivers are briefed about the system and its features.

Driver characteristics and status

Driver specification

No certain requirements on drivers.

Environmental conditions

Traffic conditions

The described feature works within regular traffic. High traffic densities like traffic jams or stop-and-go will cause the feature to be ineffective.

Weather conditions

The described feature works within regular weather conditions as long as driving safety is not compromised.

Geographical characteristics

The described feature does not require special geographical characteristics.

Partner name IKA

Identification and description

Use case name Automatic longitudinal control on traffic signs

Use case abbreviation EcoD-UC-07-IKA

Connected systems

Powertrain model and ecoDriver system Connected Hypotheses H02, H16, H25, H30 (TBD, related to feed-forward)

Description

Using map and sensor data, the system monitors and anticipates the vehicle's path. Approaching relevant traffic signs, the system automatically adjusts the current velocity in order to realize an efficient and anticipatory driving style. The system has full automatic control over the vehicle's longitudinal dynamics.

Relevant traffic signs for this feature are speed limits and stop signs.

System status

The system needs to be turned ON.

System action status

The system has full automatic control over the vehicle's longitudinal dynamics.

Characteristics

Interaction between systems The system uses IKA's powertrain model from SP2.

Frequency

Drivers are briefed about the system and its features.

Driver characteristics and status

Driver specification

No certain requirements on drivers.

Environmental conditions

Traffic conditions

The described feature works within regular traffic. High traffic densities like traffic jams or stop-and-go will cause the feature to be ineffective.

Weather conditions

The described feature works within regular weather conditions as long as driving safety is not compromised.

Geographical characteristics

The described feature does not require special geographical characteristics.

Partner name IKA Use case name Automatic longitudinal control on road geometry

Use case abbreviation EcoD-UC-08-IKA

Connected systems

Powertrain model and ecoDriver system Connected Hypotheses H02, H16, H25, H30 (TBD, related to feed-forward)

Description

Using map and sensor data, the system monitors and anticipates the vehicle's path. Approaching relevant structural and geographical conditions, the system automatically adjusts the current velocity in order to realize an efficient and anticipatory driving style. The system has full automatic control over the vehicle's longitudinal dynamics.

Relevant road geometries and structural conditions (determined by curvature data if available) may be for example upcoming curves, road inclines or roundabouts.

System and vehicle specification

System status

The system needs to be turned ON.

System action status

The system has full automatic control over the vehicle's longitudinal dynamics.

Characteristics

Interaction between systems The system uses IKA's powertrain model from SP2.

Frequency

Drivers are briefed about the system and its features.

Driver characteristics and status

Driver specification

No certain requirements on drivers.

Environmental conditions

Traffic conditions

The described feature works within regular traffic. High traffic densities like traffic jams or stop-and-go will cause the feature to be ineffective.

Weather conditions

The described feature works within regular weather conditions as long as driving safety is not compromised.

Geographical characteristics

Geographical characteristics like smooth hills and road bends are necessary for this use case.

Partner name IKA

Identification and description

Use case name Automatic longitudinal control on traffic

Use case abbreviation EcoD-UC-09-IKA

Connected systems

Powertrain model and ecoDriver system Connected Hypotheses H02, H16, H25, H30 (TBD, related to feed-forward)

Description

Using vehicle sensors, the system is able to monitor the vehicle's surroundings and detect other road users within its path. Approaching other vehicles, the system automatically adjusts the current velocity in order to realize an efficient and anticipatory driving style. The system has full automatic control over the vehicle's longitudinal dynamics.

System and vehicle specification

System status

The system needs to be turned ON.

System action status

The system has full automatic control over the vehicle's longitudinal dynamics.

Characteristics

Interaction between systems The system uses IKA's powertrain model from SP2.

Frequency

Drivers are briefed about the system and its features.

Driver characteristics and status

Driver specification

No certain requirements on drivers.

Environmental conditions

Traffic conditions

The described feature works within regular traffic. High traffic densities like traffic jams or stop-and-go will cause the feature to be ineffective.

Weather conditions

The described feature works within regular weather conditions as long as driving safety is not compromised.

Geographical characteristics

The described feature does not require special geographical characteristics.

Partner name Daimler

Identification and description

Use case name Driver Assessment Driving

Use case abbreviation EcoD-UC-10-Daimler

Connected systems Vehicle-CAN Connected Hypotheses H01, H02, H03, H04, H06, H25_1, H25_2, H25_3, H25_4, H25_5, H29_1, H29_2, H31, H32, H34, H38, H43, H44

Description

Evaluates the evenness of driving speed over a longer period.

System and vehicle specification

System status ON

System action status Driver Assessment is active

Characteristics

Interaction between systems Info. not available at this moment

Frequency Continuously

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions High traffic density can lead to a rating reduction

Weather conditions

No influence assumed -the driver should drive evenly in any weather condition.

Geographical characteristics

Road gradient is used from map

Partner name Daimler Identification and description

Use case name Driver Assessment Roll/Brake

Use case abbreviation EcoD-UC-11-Daimler

Connected systems Vehicle-CAN Connected Hypotheses H01, H02, H03, H04, H06, H25_1, H25_2, H25_3, H25_4, H25_5, H29_1, H29_2, H31, H32, H34, H38, H43, H44

Description

Evaluates the braking phases that did not result in the vehicle coming to a standstill. This function evaluates whether the vehicle was slowed by rolling or using the brakes, engine brake/retarder and service brake.

It is not distinguished between harsh and emergency braking, as emergency braking is a top priority in any case and the corresponding eco driving assessment is of minor priority.

System and vehicle specification

System status ON

System action status Driver Assessment is active

Characteristics

Interaction between systems Info. not available at this moment

Frequency Continuously

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions Not relevant

Weather conditions No influence assumed, as weather conditions are expected to influence the vehicle's rolling/braking behaviour only slightly.

Geographical characteristics

Map information is used.

Partner name Daimler Identification and description

Use

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions Not relevant

Weather conditions

The weather condition is important for this use case, as some speed limits differ, depending on a dry or wet road in Germany.

Geographical characteristics

Map information is used.

Partner name Daimler Identification and description

Use case name Driver Assessment Continuous Break Usage

Use case abbreviation EcoD-UC-14-Daimler

Connected systems Vehicle-CAN Connected Hypotheses H01, H02, H03, H04, H06, H25_1, H25_2, H25_3, H25_4, H25_5, H29_1, H29_2, H31, H32, H34, H38, H43, H44

Description

Evaluates the use of the continuous brake and progressive activation of the brake levels with foresight.

System and vehicle specification

System status ON

System action status Driver Assessment is active

Characteristics

Interaction between systems Info. not available at this moment Frequency Continuously

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions -

Weather conditions

No influence assumed, as weather conditions are expected to influence the vehicle's rolling/braking behaviour only slightly.

Geographical characteristics

Map information is used.

Partner name Daimler Identification and description

Use

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions -

Weather conditions

No influence assumed, as weather conditions does not affect shifting behaviour in terms of eco driving.

Geographical characteristics

Map information is used.

Partner name Daimler Identification and description

Use case name Driver Assessment Accelerator Pedal Usage

Use case abbreviation EcoD-UC-16-Daimler

Connected systems Vehicle-CAN Connected Hypotheses H01, H02, H03, H04, H06, H25_1, H25_2, H25_3, H25_4, H25_5, H29_1, H29_2, H31, H32, H34, H38, H43, H44

Description

Evaluates the use of the accelerator pedal as well as the use of the kick-down function. A smooth and even use of the accelerator pedal will be evaluated positively.

System and vehicle specification

System status ON

System action status Driver Assessment is active

Characteristics

Interaction between systems

Info not available at this moment Frequency Continuously

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions Not relevant

Weather conditions No influence assumed, as weather conditions does not affect accelerator pedal usage behaviour in terms of eco driving.

Geographical characteristics

Map information is used.

Partner name Daimler Identification and description

Use -the engine run time when the vehicle is stationary If you allow the engine to run when the vehicle is at a standstill without a discernible reason for approximately 1 minute, the evaluation will be negative. If you switch off the engine, e.g. during periods spent in stationary traffic, the evaluation will be positive.

-the tyre pressure (only monitorized in vehicles with tyre pressure monitor) If you drive with insufficient tyre pressures, the evaluation will be negative.

-the regeneration of the diesel particle filter If you do not perform a regeneration of the diesel particle filter when it is due, the evaluation will be negative.

-the maintenance of the air filter If you exceed the due date for maintaining the air filter, the evaluation will be negative.

System and vehicle specification

System status ON

System action status Driver Assessment is active

Characteristics

Interaction between systems Info. not available at this moment Frequency Continuously

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions Not relevant

Weather conditions Truck checks are performed in the stationary mode and do not affect weather. As an additional remark, trucks usually use the same tyre type for all weather conditions.

Geographical characteristics

Map information is used.

Partner name Daimler

Identification and description

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions Not relevant

Weather conditions No influence assumed

Geographical characteristics

Map information is used.

Partner name Daimler

Identification and description

Use case name Predictive Driver Coach Sink coasting

Use case abbreviation EcoD-UC-20-Daimler

Connected systems Vehicle-CAN, Map

Connected Hypotheses H01, H02, H03, H04, H06, H25_1, H25_2, H25_3, H25_4, H25_5, H29_1, H29_2, H31, H32, H34, H38, H43, H44 Description Recommendation to release brake to accelerate and coast through a sink.

System and vehicle specification

System status ON

System action status Predictive Driver Coach is active

Characteristics

Interaction between systems Info. not available at this moment Frequency Activated when driving situation is identified (map preview).

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions Not relevant

Weather conditions No influence assumed

Geographical characteristics

Map information is used.

Partner name Daimler

Identification and description

Use case name

System and vehicle specification

System status ON

System action status Predictive Driver Coach is active

Characteristics

Interaction between systems Info. not available at this moment Frequency Activated when driving situation is identified (map preview).

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions Not relevant

Weather conditions

The weather condition is important for this use case, as a slippery road due to water or ice limits the possible curve velocity.

Geographical characteristics

Map information is used.

Partner name Daimler

Identification and description

Use case name Predictive Driver Coach Approaching Speed Limit

Use case abbreviation EcoD-UC-22-Daimler

Connected systems Vehicle-CAN, Map

Connected Hypotheses H01, H02, H03, H04, H06, H25_1, H25_2, H25_3, H25_4, H25_5, H29_1, H29_2, H31, H32, H34, H38, H43, H44

Description Recommendation to roll towards a speed limit, where a manual shift is used.

System and vehicle specification

System status ON

System action status Predictive Driver Coach is active

Characteristics

Interaction between systems Info. not available at this moment Frequency Activated when driving situation is identified (map preview).

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions

No influence assumed

Weather conditions

The weather condition is important for this use case, as some speed limits differ, depending on a dry or wet road in Germany.

Geographical characteristics

Map information is used.

Partner name Daimler

Identification and description

Use case name

System and vehicle specification

System status ON

System action status Predictive driver coach is active

Characteristics

Interaction between systems Info. not available at this moment Frequency Activated when driving situation is identified (map preview).

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions

No influence assumed

Weather conditions

No influence assumed

Geographical characteristics

Map information is used.

Partner name Daimler

Identification and description

Use case name

System and vehicle specification

System status ON

System action status Predictive Driver Coach is active

Characteristics

Interaction between systems Info. not available at this moment Frequency Activated when driving situation is identified (camera).

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions

No influence assumed

Weather conditions

No influence assumed

Geographical characteristics

Map information is used.

Partner name Daimler

Identification and description

Use case name

System and vehicle specification

System status ON

System action status Predictive Driver Coach is active

Characteristics

Interaction between systems Info. not available at this moment Frequency Activated when driving situation is identified (camera).

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions Not relevant

Weather conditions No influence assumed

Geographical characteristics

Map information is used.

Partner name Daimler

Identification and description

Use case name Predictive Driver Coach Approaching Vehicles

Use case abbreviation EcoD-UC-26-Daimler

Connected systems Vehicle-CAN, RADAR, LIDAR, Camera

Connected Hypotheses H01, H02, H03, H04, H06, H25_1, H25_2, H25_3, H25_4, H25_5, H29_1, H29_2, H31, H32, H34, H38, H43, H44 Description Recommendation to release the accelerator pedal or brake when approaching a preceding vehicle.

System and vehicle specification

System status ON

System action status Predictive Driver Coach is active

Characteristics

Interaction between systems Info. not available at this moment Frequency Activated when driving situation is identified (camera).

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions Not relevant

Weather conditions No influence assumed

Geographical characteristics

Map information is used.

Partner name Daimler

Identification and description

Use case name Driver Tips on Demand

Use case abbreviation EcoD-UC-27-Daimler

Connected systems EcoDriver System

Connected Hypotheses H01, H02, H03, H04, H06, H25_1, H25_2, H25_3, H25_4, H25_5, H29_1, H29_2, H31, H32, H34, H38, H43, H44 Description Presentation of a collection of tips for economical and ecological driving.

System and vehicle specification

System status ON

System action status

Characteristics

Interaction between systems Info. not available at this moment Frequency On Demand

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions

No influence assumed

Weather conditions

No influence assumed

Geographical characteristics

Map information is used.

General comment on the VTI use cases: The specific task of VTI is to look at driver attention related issues in connection with the ecoDriver device. How continuous versus intermittent feedback affects eye movements will be investigated in a simulator study in November 2012. The results will affect the design of the system. Therefore it is not yet clear whether the use cases presented below are going to appear in the field study exactly as described here.

Also, when the hypotheses were written, the terminology "feedforward", "feedback" was not yet clearly established within the project. Rather, "feedback" was used for all information given to the driver. Therefore all gaze related hypotheses fit to all three use cases.

Partner name VTI

Identification and description

Use case name Glance behaviour test scenarios-feedforward

Use case abbreviation EcoD-UC-28-VTI

Connected systems ecoDriver full system

Connected Hypotheses H10, H11, H12

Description

The system provides feedforward/information on how to shift gear, or on some other discrete manoeuvre. The information is location critical, i.e. it has to be given in a certain location in order to achieve the desired effect. Therefore there is a risk that the information is presented in an inopportune moment, when situational demands may be high. If the information is presented visually with high salience, a bottomup reaction to this pop-up stimulus can be expected, with the driver "being forced to look at the display.

System and vehicle specification

System status ON System action status

The system is on and functioning in the process of providing information on a concrete, distinct action. This type of information cannot easily presented in a continuous manner.

Characteristics

The information is time critical and the driver must react within a short time interval for optimal performance.

Interaction between systems N/A

Frequency This situation is expected to occur a few times during each experimental drive.

Driver characteristics and status

Driver specification

At VTI approximately 10 drivers will be tested. Therefore it will be difficult to group them into specific driver types. More qualitative analyses may be conducted.

Partner name VTI Environmental conditions

Traffic conditions

The situation is expected to occur at slightly varying locations, depending on the type of info given and the previous behaviour of the driver. The pilot trials will show whether there are typical spots in which the information will be given (provided that such discrete information will be given at all).

Weather conditions It will be difficult to test (long-term/seasonal) weather without confounding it with familiarity with the system. Short term weather (rain or shine) cannot be predicted.

Geographical characteristics see "traffic conditions"

Partner name VTI Identification and description

Use case name Glance behaviour test scenarios-feedback

Use case abbreviation EcoD-UC-29-VTI

Partner name VTI

Connected systems ecoDriver full system Connected Hypotheses H10, H11, H12

Description

The system provides feedback after a certain manoeuvre. The feedback is discrete and related to a certain action, but it is not location critical in the sense that it requires an immediate action.

Therefore the feedback can be given at a geographical location that is likely to be rather simple in terms of predictability and cognitive loading.

It is expected that the driver will look at the information when it is presented, due to a certain pop-up effect.

System and vehicle specification

System status ON System action status

The system is on and functioning in the process of providing feedback on a concrete, distinct action. This type of information may alternatively also be presented in a more continuous manner and may therefore not be as likely to capture the driver's attention at a certain location/point in time.

Characteristics

The information is not time critical. Performance is expected to improve if the driver accepts the information, can relate it to a previous behaviour/action, is willing and able to do something about it the next time, and is able to understand and remember the required action for the next occurrence.

Interaction between systems N/A

Frequency This situation is expected to occur a few times during each experimental drive.

Driver characteristics and status

Driver specification

At VTI only about 10 drivers will be tested, therefore it will be difficult to group them into specific driver types. More qualitative analyses may be conducted.

Environmental conditions

Traffic conditions

The situation is expected to occur at slightly varying locations, depending on whether feedback is required. The pilot trials will show whether there are typical spots in which the information will be given (provided that such information will be given at all).

Weather conditions It will be difficult to test (long-term/seasonal) weather without confounding it with familiarity with the system. Short term weather (rain or shine) cannot be predicted.

Geographical characteristics see "traffic conditions"

Partner name VTI Identification and description

Use case name Glance behaviour test scenarios-continuous

Use case abbreviation EcoD-UC-30-VTI Connected systems ecoDriver full system Connected Hypotheses H10, H11, H12

Description

The system provides continuous performance information to the driver (deviation from some optimum). The information is present all the time. The driver can choose freely when to sample the information, and can therefore plan for suitable situations.

System and vehicle specification

System status ON System action status

The system is on and functioning and in the process of providing continuous visual information.

Characteristics

The info is not time critical and can be sampled when the driver deems it suitable. A more frequent info sampling, especially in more variable conditions, will increase the likelihood to remain at a high performance level, especially when the driver still is unfamiliar with the system.

Interaction between systems N/A

Frequency If the system is providing continuous information, there is potential for glances to the system throughout the drive. (As baseline, a simple "average fuel consumption" will be shown in the same place.)

Driver characteristics and status

Driver specification

At VTI only about 10 drivers will be tested, therefore it will be difficult to group them into specific driver types. More qualitative analyses may be conducted.

Environmental conditions

Traffic conditions Traffic complexity may be assessed in hindsight and then be related to the frequency and type of glance behaviour to the system. A quantitative traffic complexity classification system should be used.

Weather conditions It will be difficult to test (long-term/seasonal) weather without confounding it with familiarity with the system. Short term weather (rain or shine) cannot be predicted.

Geographical characteristics

Can be categorised and used as independent variable.

Partner name TomTom Identification and description

Use case name Pre-trip general information Use case abbreviation EcoD-UC-32-TomTom

Connected systems Connection to TomTom backend in order to retrieve weather conditions and remote updates.

Connected Hypotheses H01, H02, H03, H04, H05, H32, H33, H34, H35, H36

Description

The driver receives general information on the main screen after switching on the device.  Generic tips A list of generic tips, such as:  Turn off the engine when idling, check tires  , …  Adjust tips according to the weather conditions/season  Timing  Randomly, after switching on the device (same as per map update message)  Tick-box to suppress the message the next time (all ecoDriver messages can be disabled/enabled through specific option in the settings menu)  Type of HMI  Visual message on the display  Messages could be updated remotely/OTA

System and vehicle specification

System status

The application needs to be turned on.

System action status

The system will be active as soon as it is turned on. It will always show information about the driving style and give advice whenever necessary. The PND will provide pre-trip info, in-trip info and post trip info. There will be a dedicated ecoDriver menu for real-time/historical statistics updates (current trip/driver's average performance) during all the trip stages.

Characteristics N/A

Interaction between systems

Interaction with TomTom backend through mobile connection.

Frequency

The drivers are familiar with the device, vehicle and wireless connection.

Driver characteristics and status

Driver specification

The drivers will be professional drivers. A description of the drivers' characteristics (age, gender, income group and educational level) will be made available once the driver selection Task 32.2 is completed.

Environmental conditions

Partner name TomTom

Traffic conditions As TomTom test fleets are naturalistic, the tests are expected to be carried out in the whole Dutch and German road network during peak and non-peak hours of the day.

During the peak hours traffic congestions is common in most of the network. Significant traffic volumes on both motorways and regular highways are expected. Speed limits are not always fixed, in some roads the speed limit is adjusted dynamically in order to respond to traffic, weather and road conditions.

Weather conditions

The system will work in standard and adverse weather conditions of the Dutch and German environment. During the trials, conditions of the whole year ranging from winter to sunny conditions are expected.

Geographical characteristics

The trials will be carried on the Dutch and German geographical characteristics. Generally speaking, the tests will be carried out in a mostly flat landscape in the Netherlands and a German landscape which varies from flat terrain in the north to mountainous terrain in the south.

Partner name TomTom

Identification and description

Use case name Pre-trip general feedback

Use case abbreviation EcoD-UC-33-TomTom

Connected systems Connection to TomTom backend (via mobile network) in order to retrieve traffic information and to OBD connector to retrieve vehicle characteristics.

Connected Hypotheses H01, H02, H03, H04, H05, H32, H33, H34, H35, H36

Description

The driver will get personalized feedback on the main screen after route selection.  General advice for the specific route / traffic conditions / vehicle type  Timing  After the route is calculated  Type of HMI  Visual message on the display  Tick-box to suppress the message the next time (all ecoDriver messages can be disabled/enabled through specific option in the settings menu)

System and vehicle specification

System status

The application needs to be turned on.

System action status

The system will be active as soon as it is turned on. It will always show information about the driving style and give advice whenever necessary. The PND will provide pre-trip info, in-trip info and post trip info. There will be a dedicated ecoDriver menu for real-time/historical statistics updates (current trip/driver's average performance) during all the trip stages.

Characteristics

Interaction between systems

Interaction with TomTom backend through mobile connection and OBD vehicle data.

Frequency

The drivers are familiar with the device, vehicle and wireless connection.

Driver characteristics and status

Driver specification

The drivers will be professional. A description of the drivers' characteristics (age, gender, income group and educational level) will be made available once the driver selection Task 32.2 is completed.

Environmental conditions

Traffic conditions

As TomTom test fleets are naturalistic, the tests are expected to be carried out in the whole Dutch and German road network during peak and non-peak hours of the day.

During the peak hours traffic congestions is common in most of the network. Significant traffic volumes on both motorways and regular highways are expected. Speed limits are not always fixed, in some roads the speed limit is adjusted dynamically in order to respond to traffic, weather and road conditions.

Partner name TomTom

Weather conditions

The system will work in standard and adverse weather conditions of the Dutch and German environment. During the trials, conditions of the whole year ranging from winter to sunny conditions are expected.

Geographical characteristics

The trials will be carried on the Dutch and German geographical characteristics. Generally speaking, the tests will be carried out in a mostly flat landscape in the Netherlands and a German landscape which varies from flat terrain in the north to mountainous terrain in the south.

Partner name TomTom

Identification and description

Use case name Pre-trip personalized feedback (main screen)

Use case abbreviation EcoD-UC-34-TomTom

Connected systems Connection to TomTom backend in order to retrieve driver historical information.

Connected Hypotheses H01, H02, H03, H04, H05, H32, H33, H34, H35, H36

Description

The driver will get personalized feedback on the main screen after route selection.  Main screen  Specific tips/advices on how to improve personal performance  Timing  After the route is calculated  Type of HMI  Visual message on the display

System and vehicle specification

System status

The application needs to be turned on.

System action status

The system will be active as soon as it is turned on. It will always show information about the driving style and give advice whenever necessary. The PND will provide pre-trip info, in-trip info and post trip info. There will be a dedicated ecoDriver menu for real-time/historical statistics updates (current trip/driver's average performance) during all the trip stages.

Characteristics

Interaction between systems

Interaction with TomTom backend through mobile connection.

Frequency

The drivers are familiar with the device, vehicle and wireless connection.

Driver characteristics and status

Driver specification

The drivers will be professional. A description of the drivers' characteristics (age, gender, income group and educational level) will be made available once the driver selection Task 32.2 is completed.

Environmental conditions

Traffic conditions

As TomTom test fleets are naturalistic, the tests are expected to be carried out in the whole Dutch and German road network during peak and non-peak hours of the day.

During the peak hours traffic congestions is common in most of the network. Significant traffic volumes on both motorways and regular highways are expected.

Speed limits are not always fixed, in some roads the speed limit is adjusted dynamically in order to respond to traffic, weather and road conditions.

Partner name TomTom

Weather conditions

The system will work in standard and adverse weather conditions of the Dutch and German environment. During the trials, conditions of the whole year ranging from winter to sunny conditions are expected.

Geographical characteristics

The trials will be carried on the Dutch and German geographical characteristics. Generally speaking, the tests will be carried out in a mostly flat landscape in the Netherlands and a German landscape which varies from flat terrain in the north to mountainous terrain in the south.

Partner name TomTom

Identification and description

Use case name Pre-trip personalized feedback (specific menu)

Use case abbreviation EcoD-UC-35-TomTom

Connected systems Connection to TomTom backend in order to retrieve driver historical information.

Connected Hypotheses H32, H33, H34, H35, H36

Description

The driver will get personalized feedback when entering a specific menu.

System and vehicle specification

System status

The application needs to be turned on.

System action status

The system will be active as soon as it is turned on. It will always show information about the driving style and give advice whenever necessary. The PND will provide pre-trip info, in-trip info and post trip info. There will be a dedicated ecoDriver menu for real-time/historical statistics updates (current trip/driver's average performance) during all the trip stages.

Characteristics

Interaction between systems

Interaction with TomTom backend through mobile connection.

Frequency

The drivers are familiar with the device, vehicle and wireless connection.

Driver characteristics and status

Driver specification

The drivers will be professional. A description of the drivers' characteristics (age, gender, income group and educational level) will be made available once the driver selection Task 32.2 is completed.

Environmental conditions

Partner name TomTom

Traffic conditions As TomTom test fleets are naturalistic, the tests are expected to be carried out in the whole Dutch and German road network during peak and non-peak hours of the day.

During the peak hours traffic congestions is common in most of the network. Significant traffic volumes on both motorways and regular highways are expected. Speed limits are not always fixed, in some roads the speed limit is adjusted dynamically in order to respond to traffic, weather and road conditions.

Weather conditions

The system will work in standard and adverse weather conditions of the Dutch and German environment. During the trials, conditions of the whole year ranging from winter to sunny conditions are expected.

Geographical characteristics

The trials will be carried on the Dutch and German geographical characteristics. Generally speaking, the tests will be carried out in a mostly flat landscape in the Netherlands and a German landscape which varies from flat terrain in the north to mountainous terrain in the south.

Partner name TomTom

Identification and description

Use case name In-trip general feedback (moving map)

Use case abbreviation EcoD-UC-36-TomTom

Connected systems Power train model and feed forward/feedback systems Connected Hypotheses H01, H02, H03, H04, H05, H09, H10, H11, H12, H13, H16, H17_3, H17_5, H23 (Trucks only), H24 (Trucks only), H25_1, H25_3, H25_5, H26, H31, H32, H33, H34, H35, H36, H39, H40, H41, H42, H43, H44

Description

The driver will get general feedback when displaying the moving map.

• Moving map view  Feed-forward based on SP2 fuel model (shift up/down now, speed up, slow down, coast) • Type of HMI  Visual icons on the display

System and vehicle specification

System status

The application needs to be turned on.

System action status

The system will be active as soon as it is turned on. It will always show information about the driving style and give advice whenever necessary. The PND will provide pre-trip info, in-trip info and post trip info. There will be a dedicated ecoDriver menu for real-time/historical statistics updates (current trip/driver's average performance) during all the trip stages.

Characteristics

Interaction between systems

There will be an interaction between TomTom system and the ecoDriver applications developed in SP2.

Frequency

The drivers are familiar with the device, vehicle and wireless connection.

Driver characteristics and status

Driver specification

The drivers will be professional. A description of the drivers' characteristics (age, gender, income group and educational level) will be made available once the driver selection Task 32.2 is completed.

Environmental conditions

Traffic conditions

As TomTom test fleets are naturalistic, the tests are expected to be carried out in the whole Dutch and German road network during peak and non-peak hours of the day.

During the peak hours traffic congestions is common in most of the network. Significant traffic volumes on both motorways and regular highways are expected. Speed limits are not always fixed, in some roads the speed limit is adjusted dynamically in order to respond to traffic, weather and road conditions.

Partner name TomTom

Weather conditions

The system will work in standard and adverse weather conditions of the Dutch and German environment. During the trials, conditions of the whole year ranging from winter to sunny conditions are expected.

Geographical characteristics

The trials will be carried on the Dutch and German geographical characteristics. Generally speaking, the tests will be carried out in a mostly flat landscape in the Netherlands and a German landscape which varies from flat terrain in the north to mountainous terrain in the south.

Partner name TomTom

Identification and description

Use case name In-trip personalized feedback (moving map)

Use case abbreviation EcoD-UC-37-TomTom

Connected systems Power train model and feed forward/feedback systems Connected Hypotheses H01, H02, H03, H04, H05, H09, H10, H11, H12, H13, H16, H17_3, H17_5, H23 (Trucks only), H24 (Trucks only), H25_1, H25_3, H25_5, H26, H31, H32, H33, H34, H35, H36, H39, H40, H41, H42, H43, H44

Description

The driver will get personalized feedback when displaying the moving map.

• Moving map view  An indicator will show if the driver is currently driving green or not.

 Feedback based on driving-events, over-revving events, idling events, fuel consumption • Type of HMI  Visual icons on the display

System and vehicle specification

System status

The application needs to be turned on.

System action status

The system will be active as soon as it is turned on. It will always show information about the driving style and give advice whenever necessary. The PND will provide pre-trip info, in-trip info and post trip info. There will be a dedicated ecoDriver menu for real-time/historical statistics updates (current trip/driver's average performance) during all the trip stages.

Characteristics

Interaction between systems

There will be an interaction between TomTom system and the ecoDriver applications developed in SP2.

Frequency

The drivers are familiar with the device, vehicle and wireless connection.

Driver characteristics and status

Driver specification

The drivers will be professional. A description of the drivers' characteristics (age, gender, income group and educational level) will be made available once the driver selection Task 32.2 is completed.

Environmental conditions

Partner name TomTom

Traffic conditions As TomTom test fleets are naturalistic, the tests are expected to be carried out in the whole Dutch and German road network during peak and non-peak hours of the day.

During the peak hours traffic congestions is common in most of the network. Significant traffic volumes on both motorways and regular highways are expected. Speed limits are not always fixed, in some roads the speed limit is adjusted dynamically in order to respond to traffic, weather and road conditions.

Weather conditions

The system will work in standard and adverse weather conditions of the Dutch and German environment. During the trials, conditions of the whole year ranging from winter to sunny conditions are expected.

Geographical characteristics

The trials will be carried on the Dutch and German geographical characteristics. Generally speaking, the tests will be carried out in a mostly flat landscape in the Netherlands and a German landscape which varies from flat terrain in the north to mountainous terrain in the south.

Partner name TomTom

Identification and description

Use case name In-trip personalized feedback (specific menu)

Use case abbreviation EcoD-UC-38-TomTom

Connected systems Connected to the power train model and feed forward/feedback systems and to TomTom backend in order to retrieve driver historical information for comparison.

Connected Hypotheses H09, H10, H11, H12, H13, H16, H17_3, H17_5, H23 (Trucks only), H24 (Trucks only), H25_1, H25_3, H25_5, H26, H31, H32, H33, H34, H35, H36, H39, H40, H41, H42, H43, H44

Description

The driver will get personalized feedback when entering a specific menu.

System and vehicle specification

System status

The application needs to be turned on.

System action status

The system will be active as soon as it is turned on. It will always show information about the driving style and give advice whenever necessary. The PND will provide pre-trip info, in-trip info and post trip info. There will be a dedicated ecoDriver menu for real-time/historical statistics updates (current trip/driver's average performance) during all the trip stages.

Characteristics

Interaction between systems Interaction between TomTom system and the ecoDriver applications developed in SP2. Interaction with TomTom backend through mobile connection.

Frequency

The drivers are familiar with the device, vehicle and wireless connection.

Driver characteristics and status

Driver specification

The drivers will be professional. A description of the drivers' characteristics (age, gender, income group and educational level) will be made available once the driver selection Task 32.2 is completed.

Environmental conditions

Partner name TomTom

Traffic conditions As TomTom test fleets are naturalistic, the tests are expected to be carried out in the whole Dutch and German road network during peak and non-peak hours of the day.

During the peak hours traffic congestions is common in most of the network. Significant traffic volumes on both motorways and regular highways are expected. Speed limits are not always fixed, in some roads the speed limit is adjusted dynamically in order to respond to traffic, weather and road conditions.

Weather conditions

The system will work in standard and adverse weather conditions of the Dutch and German environment. During the trials, conditions of the whole year ranging from winter to sunny conditions are expected.

Geographical characteristics

The trials will be carried on the Dutch and German geographical characteristics. Generally speaking, the tests will be carried out in a mostly flat landscape in the Netherlands and a German landscape which varies from flat terrain in the north to mountainous terrain in the south.

Partner name TomTom

Identification and description

Use case name After-trip personalized feedback

Use case abbreviation EcoD-UC-39-TomTom

Connected systems Connected to the power train model and feed forward/feedback systems and to TomTom backend in order to store trip information.

Connected Hypotheses H32, H33, H34, H35, H36, H38, H44

Description

The driver will get Personalized feedback after the trip; the system will give advices and feedback to the driver through the Personal Navigation Device (PND) which is described in the above use case.

As drivers mostly switch off their devices after they reached their final destination, there shouldn't be any message displayed anymore after the trips was finished. User can enter the specific 'ecoDriver' menu to see the personalized feedback.

The personalized information will be provided using a visual menu; it could also be shown showed on a web page or a mobile app. The information to be provided are:  eco-driving score: last trip and personal average  Fuel consumption: last trip and personal average  CO2 emissions: last trip and personal average  Driving events: last trip and personal average  Driving style: last trip and personal average  Comparisons against a virtual performer (or fleet average/other driver) -

TBC

System and vehicle specification

System status

The application needs to be turned on.

System action status

The system will be active as soon as it is turned on, the PND will provide post trip info.

Characteristics

Interaction between systems  Interaction between TomTom system and the ecoDriver applications developed in SP2.  Interaction with TomTom backend through mobile connection.

Frequency

The drivers are familiar with the device, vehicle and wireless connection.

Driver characteristics and status

Driver specification

The drivers will be professional. A description of the drivers' characteristics (age, gender, income group and educational level) will be made available once the driver selection Task 32.2 is completed.

Environmental conditions

Partner name TomTom

Traffic conditions As TomTom test fleets are naturalistic, the tests are expected to be carried out in the whole Dutch and German road network during peak and non-peak hours of the day.

During the peak hours traffic congestions is common in most of the network. Significant traffic volumes on both motorways and regular highways are expected. Speed limits are not always fixed, in some roads the speed limit is adjusted dynamically in order to respond to traffic, weather and road conditions.

Weather conditions

The system will work in standard and adverse weather conditions of the Dutch and German environment. During the trials, conditions of the whole year ranging from winter to sunny conditions are expected.

Geographical characteristics

The trials will be carried on the Dutch and German geographical characteristics. Generally speaking, the tests will be carried out in a mostly flat landscape in the Netherlands and a German landscape which varies from flat terrain in the north to mountainous terrain in the south. Connected Hypotheses H01, H03, H04, H09, H16, H17-1, H17_2, H17_3, H18, H24, H25,H28

Description

The application will perform a pre-trip, in-trip and post-trip ecodriving assistance system. The pre-trip system is delivering personalized advice to the driver by analyzing the last trip. The intrip system works with an idle mode and a moving mode: the moving mode displays information on the vehicle speed, road speed limit, optimal speed and optimal gear while the idle mode is replacing this information with general advice on ecodriving.

The post-trip system synthesize data from the whole trip and previous trips in order to provide a detailed analysis of the driving behavior (with GPS maps and graphics). The figure hereunder illustrates three situations of the application.

System and vehicle specification

System status ON

System action status The system is on and active when speed is above zero. At idle, the system switch to idle mode where synthetic advice are displayed.

Characteristics

The displayed advice are tuneable by the driver such that a personalized HMI can be created.

Interaction between systems Interactions between speed limit advice and speed advice when available

Partner Name IFSTTAR

Driver specification At IFSTTAR 10 drivers will be tested, therefore it will be difficult to group them into specific driver types. More qualitative analyses may be conducted.

Environmental conditions

Traffic conditions

The situation is expected to occur at several locations in the region of Paris. We expect to have very different traffic conditions (from free traffic to highly congested) that can be recorded with the traffic Android API.

Weather conditions There will be several weather conditions due to the duration of trials. However, all these conditions will be recorded using the weather Android API.

Geographical characteristics

Generally flat or slightly hilly areas.

Partner Name IFSTTAR Identification and description

Use case name Full system ecoDriver application Use case abbreviation EcoD-UC-41-IFSTTAR Connected systems Full system

Connected Hypotheses H01, H03, H04, H09, H16, H17-1, H17_2, H17_3, H18, H24, H25, H28, H29, H30

Description

Full system used in this study will be purely in-trip assistance system. It will provide real-time advice on optimal speed.

System and vehicle specification

System status ON

System action status The system is on and active all the time.

Characteristics

Interaction between systems Interactions between speed limit advice and speed advice when available.

Frequency Drivers will follow a short training on a test track on the use of the car and the application.

Driver characteristics and status

Driver specification

At IFSTTAR 40 drivers will be tested, therefore it will be difficult to group them into specific driver types. More qualitative analyses may be conducted.

Environmental conditions

Traffic conditions

The situation is expected to occur at a dedicated area around Paris. Traffic will generally be low with possibilities to encounter low congested areas. These situations will be recorded from radar sensors.

Weather conditions There could probably be several weather conditions due to the duration of trials. However, all these conditions will be recorded as they can have an impact on the speed advice.

Geographical characteristics

Mainly flat with a few portions of hilly sections.

Partner name CTAG Identification and description

Use case name Daily driving with ecoDriver system on urban area

Use case abbreviation EcoD-UC-42-CTAG

Connected systems

Information not available at this moment, the system is under development

Connected Hypotheses H01, H02, H03, H04, H08, H09, H16, H17.1, H17.3, H23 H25.1, H25.2, H25.3, H25.4, H25.5, H26, H29.2, H31, H32, H33, H34, H35, H36, H37, H38, H39, H40, H41, H42, H43, H44, H45, H46 Description Driving on roads with urban characteristics, the system provides feedforward information in order to support the driver in anticipatory driving. Among others, relevant traffic signs for this feature are traffic lights.

System and vehicle specification

System status

The system needs to be turned ON.

System action status

The system provides in-trip advice and information.

Characteristics Interaction between systems

Information not available at this moment, the system is under development

Frequency Continuously

Driver characteristics and status

Driver specification

No certain requirements on drivers.

Environmental conditions

Traffic conditions

The described feature works within regular traffic. High traffic densities except traffic jams are foreseen.

Weather conditions Regular weather conditions. Driving safety is not compromised.

Geographical characteristics

Not required.

Partner name CTAG Identification and description

Use case name Daily driving with ecoDriver system on rural area

Use case abbreviation EcoD-UC-43-CTAG

Connected systems

Information not available at this moment, the system is under development Connected Hypotheses H01, H02, H03, H04, H08, H09, H16, H17.1, H17.5, H23 H25.1, H25.2, H25.3, H25.4, H25.5, H26, H29.2, H31, H32, H33, H34, H35, H36, H37, H38, H39, H40, H41, H42, H43, H44, H45, H46 Description While driving on roads with rural characteristics, the system provides feed-forward information in order to support the driver in anticipatory driving. Among others, relevant points for this feature are crosses.

System and vehicle specification

System status

The system needs to be turned ON.

System action status

The system provides in-trip advice and information.

Characteristics Interaction between systems

Information not available at this moment, the system is under development

Frequency Continuously

Driver characteristics and status

Driver specification

No certain requirements on drivers.

Environmental conditions

Traffic conditions

The described feature works within regular traffic. Low traffic densities are foreseen.

Weather conditions Regular weather conditions. Driving safety is not compromised.

Geographical characteristics

Rural areas.

Partner name CRF Identification and description

Use case name Acceleration in the most economical way.

Use case abbreviation

EcoD-UC-47-CRF Connected systems Full system

Connected Hypotheses H01, H02, H03, H09, H10, H11, H12, H17, H18, H19, H20, H22, H24, H25.1, H25.2, H25.4, H27, H31, H32, H33*, H34*, H35*, H36*, H37, H38, H39, H40, H41, H42, H43, H44, H45* Note (*): hypothesis testability will depend on the system design Description Monitoring of driver acceleration and compliance to eventual ecooptimized acceleration suggestions.

System and vehicle specification

System status ON

System action status

The system provides ECO HMI suggestions (if needed) and evaluates the driver behaviour. The observed events/scenarios potentially triggering the use case are the following:  Traffic induced: overtaking, changing lanes  Traffic signal induced: leaving a red traffic light  Road induced: after a left or right turn, a sharp curve, a roundabout, a crossing, when joining a higher speed road.

Characteristics

Interaction between systems The complete EcoDriver system is active and will use all HW and SW resources, including the data acquisition system.

Frequency

The system is continuously active. Special scenarios to be observed will be selected based on route characteristics and Maps.

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions Traffic conditions are influencing the number of events that will be generated and logged.

Weather conditions

No influence assumed Geographical characteristics Road gradient and scenarios (e.g. crossings, curves,) are obtained from maps (real or estimated).

Partner name CRF

Identification and description

Partner name CRF

Use case name Deceleration in the most economical way.

Use case abbreviation

EcoD-UC-48-CRF Connected systems Full system

Connected Hypotheses H01, H02, H03, H09, H10, H11, H12, H17, H18, H19, H20, H22, H24, H25.1, H25.3, 25.5, H26, H28, H31, H32, H33*, H34*, H35*, H36*, H37, H38, H39, H40, H41, H42, H43, H44, H45* Note (*): hypothesis testability will depend on the system design Description Evaluates the driver compliance to eco-optimized deceleration suggestions.

System and vehicle specification

System status ON

System action status

The system provides ECO HMI advices (if needed) and evaluates the driver behaviour. The observed events/scenarios potentially triggering the use case are the following:  Traffic induced: overtaking, changing lanes  Traffic signal induced: approaching a red traffic light, entering a lower speed limit area, STOP sign.  Road induced: approaching a left or right turn, a sharp curve, a roundabout, a crossing, when leaving a high speed road.

Characteristics Interaction between systems

The complete EcoDriver system is active and will use all HW and SW resources, including the data acquisition system.

Frequency

The system is continuously active, special scenarios to be observed will be selected based on route characteristics and Maps.

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions Traffic conditions are influencing the number of events that will be generated and logged.

Weather conditions

No influence assumed Geographical characteristics Road gradient and scenarios (e.g. crossings and curves) are obtained from maps.

Partner name CRF Identification and description

Use case name

System and vehicle specification

System status ON

System action status

The system provides ECO HMI advices (if needed) and evaluates the driver behaviour. The driver does not always select the optimal gear. In this case the system will propose the optimized gear.

Compliance of the driver will be measured.

Characteristics

Interaction between systems The complete EcoDriver system is active and will use all HW and SW resources, including the data acquisition system.

Frequency

The system is continuously active, special scenarios to be observed will be selected based on route characteristics and Maps.

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions Traffic conditions are influencing the number of events that will be generated and logged.

Weather conditions No influence assumed

Geographical characteristics

Road gradient and scenarios (e.g. crossings, curves) are obtained from maps.

Partner name CRF Identification and description

Use case name

System and vehicle specification

System status ON

System action status The system does not provide HMI output, but the acquisition system is on and it measures the natural driving style in all the scenarios of the other use cases. It includes also the capability of the driver to maintain an optimal (eco) speed without the support of eco-driver system.

Characteristics

Interaction between systems The complete EcoDriver system is active and will use all HW and SW resources, including the data acquisition system except the HMI devices.

Frequency

The system is continuously active. Special scenarios to be observed will be selected based on route characteristics and Maps.

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions Traffic conditions are influencing the number of events that will be generated and logged.

Weather conditions

No influence assumed Geographical characteristics Road gradient and scenarios (e.g. crossings and curves) are obtained from maps.

Partner name CRF Identification and description

Use case name Optimal Speed

Use case abbreviation EcoD-UC-51-CRF Connected systems Full system

Connected Hypotheses H01, H02, H03, H09, H10, H11, H12, H17, H18, H19, H20, H22, H23, H24, H25, H26, H27, H28, H31, H32, H33*, H34*, H35*, H36*, H37, H38, H39, H40, H41, H42, H43, H44, H45* Note (*): hypothesis testability will depend on the system design Description Evaluates the driver's capability to follow the suggested speed.

System and vehicle specification

System status ON

System action status

The system provides as HMI output the optimal speed Characteristics Interaction between systems The complete EcoDriver system is active and will use all HW and SW resources, including the data acquisition system except the HMI devices.

Frequency

The system is continuously active, special scenarios to be observed will be selected based on route characteristics and Maps.

Driver characteristics and status

Driver specification Not relevant

Environmental conditions

Traffic conditions Traffic conditions are influencing the number of events that will be generated and logged.

Weather conditions

No influence assumed Geographical characteristics Road gradient and scenarios (e.g. crossings and curves) are obtained from maps.

Test scenarios

In the context of field operation tests, scenarios are defined as a use case in a specific situation (FESTA, 2008), and therefore one or more scenarios can be considered from each use case. The development of test scenarios is a critical element within ecoDriver, since it will determine the data to be collected and the ability to fulfil the objectives of the ecoDriver This document has been created as a working document in order to note down plans for scenario development. It summarizes the test scenarios planned by each partner and describes each one by different characteristics in order to identify overlaps and comparable procedures.

Additionally the template will be used throughout multiple SPs: within WP13, WP23 and WP33. In addition to the real world trial scenarios, scenarios for simulator studies, instrumented vehicles and simulations will be defined.

Test routes

The types of fleets being planned for the field tests at all the VMCs differ from partner to partner. In total four types of fleets had been identified: controlled fleet nomadic, controlled fleet trucks, controlled fleet busses and naturalistic driving. In controlled studies all the variables that affect driving conditions and interaction between vehicles are controlled, whereas in naturalistic studies the drivers operate in a normal day-to-day driving, data is collected contiguously and usually same drivers drive for long time (FESTA Handbook version 4, 2011).

The test route definitions and characteristics for the field trials are presented in Table 2. At this time it is difficult to estimate the type of environment and duration for the naturalistic fleets, however they will be estimated once the field trials are performed. Table 3 explains the type of suggested test routes, type of vehicles and the system within the vehicle for each partner.

By now each test site except the naturalistic environment has an idea where the test routes will take place. Some partners have already defined the route they will follow during the trial preparation. For the naturalistic studies, it is difficult to determine the routes that can be followed at this time. The maps in Table 4 show the test routes that has been identified so far for each VMC.

Road type

The road type is an environmental factor that has a significant influence on individual and collective driver behaviour, and hence impact on environment, safety, mobility and traffic efficiency within an FOT. It is highly dependent on the geographic area, as discussed above.

For the ecoDriver project three main categories of road are differentiated:

 Urban  Rural  Motorway
 The lists of the road types to be used by each partner are shown in the previous section.

Traffic conditions

Traffic conditions and interactions with other road users are important aspects to be analysed carefully in any FOT. The traffic, as a general entity, can be characterized using several dimensions.

The following traffic characteristics have been identified for the test scenarios.

 Density: expressed in terms of the number of vehicles travelling in a given space

The traffic density for each use case is dependent on the VMC, day and season of the year and requirements of the use case in consideration. The traffic conditions during the tests are expected to be in the range of very low density to a high density/congested.  Speed: the average speed of traffic  Maximum speed: the maximum speed allowed in the road considered.

 Composition: types of vehicle (light vehicle, heavy duty vehicle, van, motorcycle) and their relative proportions in a given traffic stream.

 The traffic conditions at which all the tests will be carried on by each partner are explained in the scenario description provided (see Section 3).

Weather conditions

In any field operational tests weather conditions are hard to predict or measure accurately. Data may be confounded due to abnormal weather, for example snowfall increasing driver headways and reducing traffic speed or bright sunshine causing glare on screens in vehicles, or momentary distraction to drivers. The type of weather conditions expected for each VMC during the real world trials are shown in the table for scenarios.

 The expected weather conditions during the tests for are described in the scenario description provided (see Section 3).

Time of day and seasonal effects

Temporal factors such as time of day, and seasonal effects have a considerable impact on the real world trials planned. The main issues to do with the time of day, week, and seasonal variations are:

 Influence on driver state (e.g. sleepiness)

 Influence on traffic levels  Seasonal confounding of data collection  Influence on route choice  The expected times of the day and seasonal variations at which the tests are to be performed are included in the scenario template provided (see Section 3).

Implications for the ecoDriver project

D32.1 describes the scenarios identified for the field trial tests, taking as a basis the use cases identified in SP1 (and briefly described in this document). The document summarizes all the work done in Task 32.1. Within Task 32.1, each VMC leader searched for the best possible routes and / or possible areas where to test the ecoDriver concept test in real life conditions. In some cases, these routes were associated with some test conditions and this information will determine possible candidates to participate in the test (e.g. in naturalistic tests, test drivers should cover the specified route) and will also be determined by the type of vehicles foreseen for each VMC. So, this document will provide useful information to take into account in the preparation of the field trials. At the same time, this document will be an input for SP4 and SP5, providing useful information about the routes and testing environment that will help in the planning of data analyses and impact assessment.

In this case, the document was delayed with respect to the initial planned delivery date, but this fact will not imply any negative effects in the evolution of the project, as the information was provided to the different tasks and SPs in sufficient time before the starting date of the trials and during the definition process.

Hypothesis ID

The mode via which the driver receives ecodriving information affects acceptance e.g. haptic are more acceptable than auditory H31

The amount of information given by the ecoDriving system to the driver affects acceptance (detailed versus aggregated info, merging rules of ecodriving versus an index)

H32

The type of information given by the ecoDriving system to the driver affects acceptance (e.g. (i) competitive info versus non-competitive or (ii) continuous versus sporadic information or (iii)diagnostic or advisory information is more acceptable than technical information)

H33

The timing (before/during/after) of the eco information affects acceptance H34

The adaptivity of the ecodriving system affects acceptance H35

The controllability of the interface affects acceptance (controllable more acceptable than a rigid one) H36

Acceptance changes with increased exposure to the ecoDriving system H37 Driver characteristics (age/gender/personality/attitudes) mediate acceptability of an ecoDriving system H38 ecoDriving systems reduce perceived safety by limiting velocity and acceleration ability which has a serious impact on its acceptance H39

An ecoDriving system reduces driving enjoyment and thus affects acceptance H40

An ecoDriving system appears distracting to the driver and reduces acceptance H41

An ecoDriving system alleviates stress which increases acceptance H42

An ecoDriving system alleviates fatigue which increases acceptance H43

A demonstrated fuel saving (or cost saving) increases acceptance of the ecoDriving system.

H44

Lower control complexity increases acceptance of the ecoDriving system. H45

Lower perceived acceleration and velocity by ecoDriving system influences current traffic flow and may reduce general acceptance (of following traffic) H46

Figure 1 :

 1 Figure 1: Trial countries...........................................................................................................................8 Figure 2: Interaction of tasks in WP32 with other WPs..........................................................................10

Figure 1 :

 1 Figure 1: Trial countries.



  Define and develop tools to be used during the trial tests and evaluation processes  Organise a range of trials across Europe in real traffic conditions, covering: o Wide geographical distribution (North, Central and South Europe) o Different types of vehicles (Passenger Cars, Light Commercial Vehicles, Heavy Trucks, Buses)

Figure 2 :

 2 Figure 2: Interaction of tasks in WP32 with other WPs.

  EcoD-UC-10-Daimler Driver Assessment Roll

  the accelerator pedal to roll towards a stop sign.

  the accelerator pedal to roll towards a red traffic light.

  the accelerator pedal to roll towards an intersection without priority or a roundabout.

Frequency

  Drivers will follow a short training on the use of their own smartphone (received as incentive from ecoDriver) with the ecoDriver application. Drivers will use their own cars. Driver characteristics and status `D32.1: Individual Use Cases and Test Scenarios Definition (version 13, 2014-02

  hypothesis testability will depend on the system designDescriptionEvaluates the driver compliance to eco-optimized gear shifting.

  , H03, H09, H10, H11, H12, H17, H18, H19, H20, H22, H23, H24, H25, H26, H27, H28, H31, H32, H33*, H34*, H35*, H36*, H37, H38, H39, H40, H41, H42, H43, H44, H45* Note (*): hypothesis testability will depend on the system designDescriptionEvaluates the driver basic driving style.

  . The main factors to define the test scenarios for each test site are:  geographical location/test routes  road type  traffic conditions and interactions with other road users  weather conditions  Time of day and seasonal effects.

Table 4 :

 4 Test routes N.B. the maps are not to scale Partner Route VTI `D32.1: Individual Use Cases and Test Scenarios Definition (version 13, 2014-02-25)

Table 1 :

 1 Summary of individual use cases..............................................................................................13 Table 2:Test route environment............................................................................................................79

Table 3 :

 3 Suggested Test Routes.............................................................................................................79

Table 4 :

 4 Test routes N.B. the maps are not to scale.............................................................................80

Table 1 :

 1 Summary of individual use cases.

Partner name IKA Identification and description Use case name Information on traffic signs

	Partner name Connected systems	Driver Assessment Shifting Driver Assessment Accelerator Pedal Usage IKA Driver Assessment Truck Check Powertrain model and ecoDriver system	EcoD-UC-15-Daimler EcoD-UC-16-Daimler EcoD-UC-17-Daimler
		Driver Assessment Feedback	EcoD-UC-18-Daimler
		Predictive Driver Coach Roll over Hilltop	EcoD-UC-19-Daimler
		Predictive Driver Coach Sink coasting	EcoD-UC-20-Daimler
		Predictive Driver Coach Curve Driving	EcoD-UC-21-Daimler
		Predictive Driver Coach Approaching Speed Limit	EcoD-UC-22-Daimler
		Predictive Driver Coach Approach Stop Sign	EcoD-UC-23-Daimler
		Predictive Driver Coach Red Traffic Light	EcoD-UC-24-Daimler
		Predictive Driver Coach Approaching	EcoD-UC-25-Daimler
		Intersection/Roundabout
		Predictive Driver Coach Approaching Vehicles	EcoD-UC-26-Daimler
		Driver Tips on Demand	EcoD-UC-27-Daimler
	Sweden	Glance behaviour test scenarios -feedforward	EcoD-UC-28-VTI
	(Partner responsible VTI)	Glance behaviour test scenarios -feedback Glance behaviour test scenarios -continuous	EcoD-UC-29-VTI EcoD-UC-30-VTI
	UK	eco-driving advice for buses based on road geometry	EcoD-UC-31-UNIVLEEDS
	(Partner
	responsible Uni.
	Leeds)
	Netherlands	Pre-trip general information	EcoD-UC-32-TomTom
	(Partner responsible TomTom)	Pre-trip general feedback Pre-trip personalized feedback (main screen) Pre-trip personalized feedback (specific menu) In-trip general feedback (moving map)	EcoD-UC-33-TomTom EcoD-UC-34-TomTom EcoD-UC-35-TomTom EcoD-UC-36-TomTom
		In-trip personalized feedback (moving map)	EcoD-UC-37-TomTom
		In-trip personalized feedback (specific menu)	EcoD-UC-38-TomTom
		After-trip personalized feedback	EcoD-UC-39-TomTom
	France	Smartphone trip information	EcoD-UC-40-IFSTTAR
	(Partner responsible	Full system ecoDriver application	EcoD-UC-41-IFSTTAR
	IFSTTAR)
	Spain ( Partner respons-ible CTAG)	Daily driving with ecoDriver system on urban area Daily driving with ecoDriver system on rural area Daily driving with ecoDriver system on interurban area	EcoD-UC-42-CTAG EcoD-UC-43-CTAG EcoD-UC-44-CTAG
		Daily driving with ecoDriver system on slopes	EcoD-UC-45-CTAG
		Daily driving with ecoDriver system on motorways	EcoD-UC-46-CTAG
	Italy (Partner respons-ible CRF)	Acceleration in the most economical way. Deceleration in the most economical way. Eco-Optimized gear-shifting	EcoD-UC-47-CRF EcoD-UC-48-CRF EcoD-UC-49-CRF
		Baseline driver assessment	EcoD-UC-50-CRF
		Optimal Speed	EcoD-UC-51-CRF
	Use case abbreviation	EcoD-UC-01-IKA

/Brake EcoD-UC-11-Daimler Driver Assessment Stop EcoD-UC-12-Daimler Driver Assessment Speed EcoD-UC-13-Daimler Driver Assessment Continuous Break Usage EcoD-UC-14-Daimler

D32.1: Individual Use Cases and Test Scenarios Definition(version 13, 2014-02-25)

`D32.1: Individual Use Cases and Test Scenarios Definition (version 13, 2014-02-25)

Couldn't be known at this time

Check section 1.2 `D32.1: Individual Use Cases and Test Scenarios Definition (version 13, 2014-02-25)

H14 and H15 were the exact replica of H12 and 13, hence they are removed and the numbering continues from H16. `D32.1: Individual Use Cases and Test Scenarios Definition(version 13, 2014-02-25)

The research leading to these results has received funding from the European Union Seventh Framework Programme under grant agreement n° 288611. FP7-ICT-2011-7: Information and Communication Technologies Low carbon multi-modal mobility and freight transport

Route #3 (Interurban) Route #4 (Motorway) http://goo.gl/maps/5TboK http://goo.gl/maps/rJP36 http://goo.gl/maps/mwc8g http://goo.gl/maps/Dn8xB CTAG Car After Market Route #1 (Urban) Route #2 (Rural) Route #3 (Interurban) Route #4 (Motorway) http://goo.gl/maps/5TboK http://goo.gl/maps/rJP36 http://goo.gl/maps/mwc8g http://goo.gl/maps/Dn8xB VTI car Full system Route #1 http://g.co/maps/j8yus IKA car Full system Route #1 http://g.co/maps/95nu3 Leeds buses Navigation system Route #3 http://goo.gl/maps/FH8mQ IFSTTAR car Full system Route #1 http://goo.gl/maps/VsMC IFSTTAR car After Market Route #1 http://goo.gl/maps/VsMC IFSTTAR car Navigation system Route #1 http://goo.gl/maps/VsMC

Partner name University of Leeds Identification and description

Use case name eco-driving advice for buses based on road geometry Use case abbreviation EcoD-UC-31-UNIVLEEDS Connected systems Possibly the system for the German truck trial Connected Hypotheses H01, H03, H04, H09, H16, H17-1, H17_2, H17_3, H18, H24, H25, H28, H29, H30  Using ecoDriver system will keep constant (or increase) the energy savings over time 3

Description

The ecoDriver system will provide continuous advice to the bus driver. The advice will take gradient into account. The effect of ecodriving advice will be investigated according to driver characteristics as well as temporal and environmental variables. Learning effect will also be analysed.

System and vehicle specification

System status This trial will consist of a baseline and treatment period System action status During the treatment period, the system will provide eco-driving advice (could be speed and throttle input)

Characteristics

Real time advice according to geometric information

Interaction between systems

No interaction with other on-board systems

Frequency

The system will be installed on the bus for driver's use all the time

Driver characteristics and status

Driver specification Approximately 30 bus drivers. Effort will be made to recruit different groups of drivers (age and experience) where possible.

Environmental conditions

Traffic conditions

Traffic conditions will vary especially between peak and off-peak period, which will be used as a factor for analysis.

Weather conditions

The system aims to work independent of weather conditions.

Weather conditions however will be obtained (through secondary sources) for analysis purpose.

Geographical characteristics

The routes will consist of a range of gradients, number of lanes in the carriageway, as well as various types of junctions. Part of the route also offers guided bus lane.

Partner name CTAG

Identification and description

Use case name

Daily driving with ecoDriver system on interurban area

Use case abbreviation

EcoD-UC-44-CTAG

Connected systems

Information not available at this moment, the system is under development Connected Hypotheses H01, H02, H03, H04, H07, H08, H09, H16, H17.1, H17.2, H17.3, H23 H25.1, H25.2, H25.3, H25.4, H25.5, H26, H29.2, H31, H32, H33, H34, H35, H36, H37, H38, H39, H40, H41, H42, H43, H44, H45, H46 Description While driving on roads with interurban characteristics, the system provides feed-forward information in order to support the driver in anticipatory driving.

System and vehicle specification

System status

The system needs to be turned ON.

System action status

The system provides in-trip advice and information.

Characteristics Interaction between systems

Information not available at this moment, the system is under development

Frequency Continuously

Driver characteristics and status

Driver specification

No certain requirements on drivers.

Environmental conditions

Traffic conditions

The described feature works within regular traffic. Normal traffic densities are foreseen. Higher traffic densities on rush hours.

Weather conditions Regular weather conditions. Driving safety is not compromised.

Geographical characteristics

Interurban areas.

Partner name CTAG Identification and description

Use case name Daily driving with ecoDriver system on slopes

Use case abbreviation EcoD-UC-45-CTAG

Connected systems

Information not available at this moment, the system is under development Connected Hypotheses H01, H02, H03, H04, H08, H09, H16, H18, H23, H25.1, H25.2, H25.3, H25.4, H25.5, H26, H29.2, H31, H32, H33, H34, H35, H36, H37, H38, H39, H40, H41, H42, H43, H44, H45, H46 Description While driving on roads with different slopes, the system provides feedforward information in order to support the driver in anticipatory driving.

System and vehicle specification

System status

The system needs to be turned ON.

System action status

The system provides in-trip advice and information.

Characteristics Interaction between systems

Information not available at this moment, the system is under development

Frequency Continuously

Driver characteristics and status

Driver specification

No certain requirements on drivers.

Environmental conditions

Traffic conditions

The described feature works within low and regular traffic. High traffic densities will cause the feature to be ineffective.

Weather conditions Regular weather conditions. Driving safety is not compromised.

Geographical characteristics

Roads with different slopes, mainly in rural areas.

Partner name CTAG Identification and description

Use case name Daily driving with ecoDriver system on motorways

Use case abbreviation EcoD-UC-46-CTAG

Connected systems

Information not available at this moment, the system is under development

Connected Hypotheses H01, H02, H03, H04, H09, H16, H17.3, H23, H25.1, H25.2, H25.3, H25.4, H25.5, H26, H29.2, H31, H32, H33, H34, H35, H36, H37, H38, H39, H40, H41, H42, H43, H44, H45, H46 Description Driving on roads with different slopes, the system provides feedforward information in order to support the driver in anticipatory driving.

System and vehicle specification

System status

The system needs to be turned ON.

System action status

The system provides in-trip advice and information.

Characteristics Interaction between systems

Information not available at this moment, the system is under development

Frequency Continuously

Driver characteristics and status

Driver specification

No certain requirements on drivers.

Environmental conditions

Traffic conditions

The described feature works within low and regular traffic. High traffic densities will cause the feature to be ineffective.

Weather conditions Regular weather conditions. Driving safety is not compromised.

Geographical characteristics Typical motorway environment

Annex A: List of ecoDriver Hypotheses

The list of ecoDriver hypotheses below have been contributed by workpackage 41 and are available in deliverable D41.1.

Hypothesis ID

Emissions

Using ecoDriver system will reduce the average energy consumption (megajoules per km or 100km).

H01

Using ecoDriver system will reduce the average fuel consumption (per 100km). H02

Using ecoDriver system will reduce the average CO2 emissions (per km or 100km). H03

Using ecoDriver system will reduce the average NOX emissions (per km or 100km). H04

Using ecoDriver system will decrease Energy consumption more for certain features of the system H05

Hypothesis related to the golden rules of ecodriving (see below) can also be tested depending on certain features of the HMI/system/algorithm/powertrain etc.

H06

Using ecoDriver will continuously decrease Energy consumption when penetration rate increase H07

Incorporating an engine stopping rule (at traffic lights for example) to the ecoDriver system leads to higher Energy savings H08

Behaviour and Side Effects

The workload of the driver will increase when (s)he has an ecoDriver system that gives in-car feedback H09

The driver is more distracted (eyes more 'off the road') with an ecoDriver system that gives in-car feedback H10

In-car feedback from the ecoDriver system cause inappropriate/dangerous visual behaviour, in terms of glances towards the device H11

The driver will look more at the speedometer/rev counter when using the ecoDriver system H12 There will be more visual distraction with nomadic devices (smart phones with small screens) than with an embedded system H13 6

Average velocity will be equal or lower when using an ecoDriver system H16

Speed will be higher when driving through/past locations were a low speed is recommended when using an ecoDriver system  Location: Intersections without traffic lights H17_1

 Location: Zebra crossings H17_2

Hypothesis ID

 Location: Speed reducing measures H17_3

 Location: Corners/sharp curves H17_4

 Location: Villages H17_5

There will be more occasions of speeding when driving downhill when using an eco-Driver system H18 There will be fewer occurrences where the vehicle in front is in the driver's safety zone when using an ecoDriver system H19

There will be shorter distances to following vehicles in/during safety critical locations/situations when using an ecoDriver system H20

There will be more red or amber light violations when using an ecoDriver system H21

There will be fewer overtakings when using an ecoDriver system H22

The average rpm when shifting up will be reduced when using an ecoDriver system H23

The weighted average engine rpm will be decreased when using an ecoDriver system H24

Driving will be more smooth when using an ecoDriver system  Subhypothesis: The variability of speed profiles will be decreased when using an ecoDriver system

H25_1

 Subhypothesis: The number of strong accelerations will be reduced when using an ecoDriver system

H25_2

 subhypothesis: The number of hard decelerations will be reduced when using an ecoDriver system

H25_3

 Subhypothesis: Acceleration in general will be smoother when using the ecoDriver system

H25_4

 Subhypothesis: Deceleration in general will be smoother when using the ecoDriver system

H25_5

The usage of the engine brake will be improved when using an ecoDriver system H26

Acceleration after standing still will be more aggressive when using an ecoDriver system H27 Deceleration when entering safety critical locations/situations will be less aggressive when using an ecoDriver system H28

The use of speed assistance systems will increase when using an ecoDriver system H29

 System: Adaptive cruise control (ACC) H29_1

 System: Cruise control H29_2

 System: Speed limiter H29_3

Hypotheses related to the type of feedback and the HMI H30

Acceptance

Annex B: Overview of fleets Connected hypotheses:  Using ecoDriver system will reduce the average Greenhouse effect gas (GEG) emissions  Using ecoDriver system will reduce the average energy consumption  Using ecoDriver system will keep constant (or increase) the energy savings over time  Workload and distraction: The workload of the driver will increase when (s)he has an ecoDriver system that gives in-car feedback  Driving behaviour and safety: Mean speed will be equal or lower when using an ecoDriver system  Driving behaviour and safety: Speed will be higher when driving through/past locations were a low speed is recommended when using an ecoDriver system  Driving behaviour and safety: There will be more occasions of speeding when driving downhill when using an ecoDriver system  Eco-driving behaviour: The weighted average engine rpm will be decreased when using an ecoDriver system  Eco-driving behaviour: Driving will be more smooth when using an ecoDriver system  Eco-driving behaviour: Acceleration after standing still will be more aggressive when using an ecoDriver system  Driving at very low speeds is inefficient, particularly for ICEs. It may thus be beneficial to accelerate swiftly from idling to cruising speed.  Eco-driving behaviour: Deceleration when entering safety critical locations/situations will be less aggressive when using an ecoDriver system  Eco-driving behaviour: The use of speed assistance systems will increase when using an ecoDriver system  Eco-driving behaviour: Hypotheses related to the type of feedback and the HMI Description Full system used in this study will be purely in-trip assistance system. It will provide real-time advice on optimal speed.

System and vehicle specification

System status ON System Action status

The system is on and active all time. Characteristics Interaction between systems Interactions between speed limit advice and speed advice when available. Frequency Drivers will follow a short training on a test track on the use of the car and the application.

Driver characteristics and status

Driver specification

At IFSTTAR 40 drivers will be tested, therefore it will be difficult to group them into specific driver types. More qualitative analyses may be conducted.

Environmental conditions

Traffic conditions

The situation is expected to occur at a dedicated area around Paris. Traffic will generally be low with possibilities to encounter low congested areas. These situations will be recorded from radar sensors.

Weather conditions

There could probably be several weather conditions due to the duration of trials. However, all these conditions will be recorded as they can have an impact on the speed advice.

Geographical characteristics

Mainly flat with a few portions of hilly sections.

For

Disclaimer

This document reflects the views of the author(s) alone. The European Union is not liable for any use that may be made of the information herein contained.