Baptiste Arati

Vincent Bley

Julio Brandelero

Gilbert Teyssedre

Self-healing encapsulation material for auto-repairable power module architectures

Keywords: Self-healing, vitrimers, epoxy, printed circuit board, power module, integration 1

A self-healing polymer intended to printed circuit boards (PCBs) insulation has been implemented. The applicability of this new material to PCB manufacturing and recovery of properties on mechanical and electrical standpoints are investigated. The research points to enhanced reliability for future architectures of integrated power modules.

Introduction

During their lifetime, power modules encounter several types of damages that can be critical for their operation. One of the most identified sources of damage is thermomechanical stress generated during thermal cycling, resulting from different thermal expansion coefficients between components, the substrate and the encapsulant. This leads to typical failure mechanisms, like bond wire lift-off, wire fatigue and solder degradations that drive the end of life of the device [START_REF] Stockmeier | 20th International Symposium on Power Semiconductor Devices & IC's[END_REF][START_REF] Ciappa | [END_REF][3].

Several studies have explored the role of the encapsulant in such failure mechanisms in order to mitigate their impact on the reliability of power modules. These results show that, in comparison with silicone gel, having a stiffer encapsulation material such as epoxy compounds has a beneficial effect on lifetime [START_REF] Boettge | IEEE 68th Electronic Components and Technology Conference (ECTC)[END_REF][START_REF] Naumann | 11th International Conference on Integrated Power Electronics Systems (CIPS)[END_REF][START_REF] Chen | 14th International Microsystems, Packaging, Assembly and Circuits Technology Conference (IMPACT)[END_REF][START_REF] Wagner | 20th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE)[END_REF].

Another path to explore hard encapsulation is the embedding of dies into printed circuit boards (PCBs). These architectures offer numerous advantages, such as better cooling solutions, higher efficiency and integrability [START_REF] Hou | [END_REF]9]. For this purpose, existing materials are not always suitable, creating new types of defects during production and operation [10,11].

Indeed, having a stiffer encapsulation leads to greater interfacial stresses during heat cycles. Ultimately, devices designed with stiffer embedding materials will develop interfacial cracks in the dielectric and eventually fail.

Finding a way to mitigate the prevalence and consequences of such mechanical damages is highly desirable. The solution may not be necessarily in making stiffer encapsulation, but instead design materials capable of accommodating mechanical stresses and restoring from induced damages. Hence, for the first time to our knowledge the development of materials with self-healing capabilities is explored with application to power integration and lifetime extension of power electronics devices in mind.

Intrinsic self-healing is the inherent ability of a material to recover from damages without the help on an external structure or reagent. These materials rely on chemical equilibria to dynamically reform their network on a molecular level by exchanging chemical bonds across the fracture plan.

Most of intrinsic self-healing solutions are based on weak intermolecular bonds and often exhibit very low mechanical and thermal properties that aren't suitable for an embedding substrate application [12][13][14][15]. However, higher energy bonds can also be used to create dynamic networks that show much higher mechanical and thermal properties. [16,17].

Fitting of these materials to the needs and requirements of integrated power modules deserves to be further studied as the ability to unite two surfaces back to a continuous volume seems very valuable for electrical insulation reliability, both from an early life and an end-of-life point of view.

Besides self-healing capabilities, a broad panel of properties will need to be assessed, ranging from processability, thermal stability, thermomechanical properties, dielectric strength and adhesion among others. Mechanical and thermomechanical properties of materials can often be accommodated by smart design. In the present work, we focus on some decisive aspects that are the processability, the thermal stability and the dielectric strength. The thermal stability is especially important at the manufacturing step. For instance, soldering operations can involve solder bath at up to 290°C in lead-free processes [START_REF] Coombs | Printed circuits handbook[END_REF].

As the main electrical insulator, the dielectric also needs to exhibit a high breakdown strength to avoid insulation failures in high voltage applications. This becomes especially true when aging occurs or when cracks propagate inside the encapsulation, decreasing the actual thickness of the insulator [START_REF] Kearney | [END_REF].

Our goal with this paper is to present the implementation of intrinsic self-healing materials suitable for PCB die embedding. Firstly, the material compatibility with the PCB application is investigated. Then, a PCB demonstrator will be produced from a developed Resin Coated Copper (RCC). Finally, recovery of the mechanical integrity and electrical insulation properties are achieved. The ultimate goal is to use this technology with embedded power die.

Vitrimers in PCB manufacturing

Choice of self-healing material

Vitrimers are a new family of polymers that rely on strong covalent bonds to achieve self-healing, often using trans-esterification reactions [20]. Trans-esterification involves ester and alcohol groups, reacting with each other and changing the crosslink distribution in the network. This reaction is reversible, theoretically allowing infinite reorganizations of the crosslinked network [21].

One of the simplest ways to obtain these chemical groups is to cure conventional epoxy resins with carboxylic acids in presence of a catalyst. This can be done with many epoxy resins already used in the electronics field.

Additionally, these polymers do not require depolymerization to activate their healing properties but on the contrary, rely on a state where all the chains are linked together in a metastable equilibrium before rearranging their structure and split. Maintaining a coherent network with a degree of stability during healing seems very valuable for such a technical field.

For these reasons, trans-esterification based vitrimers have been selected as the main strategy to produce selfhealing samples and demonstrators.

Material elaboration

Vitrimers are greatly aligned with the requirements of PCB manufacturing. They can be easily based off commercial epoxy resins, widely used in the electronic field, by curing them using carboxylic acids and an appropriate catalyst (Figure 1).

The elaboration process is based off Altuna et al.'s procedure [22]. Epoxy groups were introduced with a 10% excess regarding acid groups to ensure completion of the reaction and the catalyst content was set at 5% molar compared to acid groups.

Diglycidyl ether of bisphenol A (DGEBA, D.E.R. 332 -Epoxy equivalent = 178g.eq-1) and sebacic acid (99% purity -Acid equivalent = 101g.eq-1) were used as the main precursors and 1-Methylimidazole (99% purity) was selected as the catalyst. All reagents were purchased from Sigma-Aldrich and used without further purification.

Figure 1 Precursors and catalyst used in this work

Epoxy resin and fatty acids were heated to 150°C in disposable aluminium pans before being mixed and reacted for a few minutes. The low viscosity liquid was taken out of the convection oven and slightly cooled down (near 130°C) before addition of the catalyst and further mixing by hand, avoiding formation of bubbles in the resin.

The liquorish liquid was then casted and shaped by press-molding to produce different kinds of samples (bulk, films, resin coated copper RCC). The curing process was carried out in the mold at 150°C for 1h under 1MPa of pressure.

The reaction was separately followed by Differential Scanning Calorimetry (DSC) and showed no heat generation after 25 minutes and a complete return to baseline after 1h. This indicates that the majority of the reagents have reacted and that seldom modifications of the network should happen afterwards.

The final polymer was also analysed by Fourier-Transform InfraRed spectroscopy (FTIR) to assess the chemical nature of the end-product. Consumption of epoxy and acid groups could be observed while formation of ester and alcohol groups could be confirmed (Figure 2), which validates the formation of a vitrimer self-healing network.

Compatibility with PCB applications

Thermal degradation was assessed by Thermo-Gravimetric Analysis (TGA) using a NETZSCH TG209 TGA/DTA analyser, performed at 10°C/min from room temperature to 700°C. A drying step was introduced, stalling at 150°C for 15min before continuing the heating ramp. Measurements were achieved both in pure nitrogen and in dry air (Figure 3). The polymer response to cyclic heat treatments was monitored by Differential Scanning Calorimetry (DSC), using a TA DSC 2010 with a heating rate of 5°C/min from 0 to 300°C for a total of 4 successive cycles (Figure 4).

Figure 4 DSC thermograms of the vitrimer during heat cycles

These thermograms confirm the thermoset nature of the polymer and provide insight on the glass transition temperature (Tg), evaluated near 35°C. On the first cycle, one can observe endothermic events (downwards) attributed to recovery of physical aging as Tg is very close to the ambient temperature. Once energy has been provided to the system however, superposition of the curves can be observed and no reaction or significant modification of the glass transition were detected. These results ensure that the material will experience minimal change during its life cycles regardless of heat generation of power devices, that is usually capped below 150°C for most applications.

Breakdown strength determination was performed on a 300 µm thick film at 50 Hz with a Baur DPA-75C system, in a sphere-to-sphere configuration (1/2"diameter) immersed in a fluorinated dielectric liquid (Galden HT55). The electrical field is considered uniform in the material. A voltage ramp of 2kV/s was selected to obtain breakdown between 10 and 20 seconds, thus limiting the electrical aging of the material.

The breakdown strength was evaluated over 28 measurements at 67 ± 1.9 kV/mm at room temperature. These results show a very high breakdown strength, suitable for PCB insulation in high voltage applications such as power modules.

3

Manufacturing of a self-healing PCB

RCC manufacturing

To produce a self-healing PCB, it is necessary to first produce an object with several insulating and conductive layers, that can later be etched with the desired printed pattern. One way to do that is to prepare a Resin Coated Copper (RCC), that will be composed of two conductive copper layers, insulated by a dielectric coating resin.

Using press-molding as the main manufacturing technique, a sacrificial mold was designed using 35µm thick copper sheets for top and bottom covers and a 300µm thick spacer for the sides of the mold. The copper sheets were received surface-treated on one side (brown oxidation) to improve resin adhesion.

This mold receives the in excess liquid hot pre-polymer and is closed before going into the press for curing at 150°C for 1h under 1MPa of pressure. Once cooled down, the mold is removed from the press and directly cut to size, removing the spacer and the excess of copper and resin in the process (Figure 5). The obtained end-product is a cured RCC (15 x 10 cm²) with a self-healing insulating material that can be further processed into a PCB (Figure 6). At this stage, it is also possible to drill the RCC and perform the electrodeposition of copper to make through-hole or filled vias.

PCB etching process and conformity assessment

To ensure the dielectric material can withstand the complete manufacturing procedure, a cured RCC followed a conventional PCB etching process.

First the RCC was cut to size and laminated with a photoresist dry film in a Eurolam M300 laminator. This film polymerizes under UV light and resist chemical revealing and copper etching operations. The negative mask was printed and applied on the dry film before exposure of the film for several minutes. After revealing the pattern by dissolving the unpolymerized dry film, the exposed copper was etched in a Sprint 3000 Bungard chemical etcher, using a commercial iron perchloride solution. Then, the exposed dry film was removed in a dilute solution of sodium hydroxide (stripping). The final product was obtained after rinsing and drying (Figure 7). Figure 7 Developed PCB etching process on the self-healing RCC Visual conformity was assessed: the polymer didn't seem to suffer any degradation following the procedure and its apparent adhesion to copper remained very strong despite the numerous chemical baths and manipulations it was exposed to. A slight roughness is revealed since the polymer totally replicated the topography of the surfacetreated copper sheets.

FTIR spectra of the polymer before and after this process showed no modification in the chemical nature of the material, which ensured conservation of self-healing properties of the printed circuit board throughout the whole manufacturing process.

4

Material recovery

Recovery protocol

Recovery of fracture is very dependent of the conditions in which the recovery takes place.

Many studies use pressure in conjunction with temperature during the whole healing process to help surfaces match and merge together or to completely reform a new sample. This procedure dramatically helps chemical groups to enter into intimate contact and even helps diffusion and interlacing of mobile chain ends [23,24].

However, externally applying pressure to an operating power module is not realistic. Therefore, pressure application during the healing process was not used in this work. Instead, the shape memory properties of the material were used to ensure a good match of the fracture plans in 3D.

In the case of a completely severed sample, heating the material for 1min at 150°C recovers from plastic deformations, yielding perfectly matching surfaces. In addition, when a sample is not totally severed, shape memory can also help realigning and pressing the pieces together, without external help. In both cases, a very good match could be obtained.

Afterwards, the matching surfaces are put into contact with minimal force if necessary and are set free to heal for 1h at 150°C before being cooled down. This is therefore the worst-case scenario in this configuration, as confinement and thermal expansion could be used as a way to press the crack borders together by creating internal pressure.

Demonstration of mechanical properties recovery

Mechanical recovery was assessed using a Mecmesin Multitest-i in tensile configuration, performed at a strain rate of 20mm/min at room temperature (Figure 8). Dumbbell shaped bulk samples were designed by scaling down the type IV design proposed in the ASTM D638-14 standard to 85mm length. Samples were pre-heated for 10 min at 150°C to recover from physical aging naturally occurring at room temperature, before being cooled down and broken on the tensile bench. After the recovery process, the same samples were tested again on the same bench.

Results show an almost perfect recovery of the elastic modulus as well as a complete recovery of strength at yield. However, strain profiles show a shift in failure mode, from a ductile type of failure to a fragile one. Indeed, recovery of the fractured surface isn't perfect and once plastic deformation occurs, the fracture plan acts as a guide for new crack propagation, testing the toughness of the adhesive joint that abruptly yields.

Demonstration of dielectric strength recovery

Recovering from a proper breakdown isn't really feasible as the high energy plasma of the spark degrades the chemical groups of the polymer and most often transform it into carbon, which is not self-healing by itself. However, recovery can be expressed for any property following any damage, as long as the damage is in fact reducing or preventing the expression of the said property.

In the case of integrated power modules, mechanical damages can decrease the breakdown strength of the insulating material, by reducing the overall thickness or by creating initiation sites for partial discharges, which will trigger breakdown after some time. Therefore, the purpose of this test is not to repair a dielectric breakdown but to evaluate the rate of recovery of the breakdown voltage in repaired volumes, following a mechanical damage.

For breakdown voltage recovery evaluation, novel samples had to be designed, concentrating both mechanical and electrical stresses in the same area. Embedded electrode patterns were produced with a controlled 1mm gap using the PCB etching process before being encapsulated in a new batch of the polymer. A CO2 laser ablation was then used to remove some of the polymer for electrical contacts and cut notches for mechanical stress concentration (Figure 9). Figure 9 Tensile/breakdown tests sample manufacturing and geometry Crack propagation was channelled in between the electrodes using notches and stopped using an open void. This allowed to keep a small portion of the polymer intact and take advantage of the polymer shape memory to precisely self-realign the electrodes during the recovery process (Figure 10).

Mechanical damages were produced with a Deben Microtest tensile stage at a strain rate of 1mm/min at 20°C. After healing, breakdown strength tests were performed in a fluorinated dielectric liquid bath using a 2kV/s voltage ramp at 50Hz. The rate of recovery seems very satisfying as it only requires 5 minutes of healing to achieve at least 85% of the pristine breakdown voltage value. After one hour, the recovery increased to about 100%. These results seem ideal, however, there is a great dispersion of data points with the shortest healing times. Given the complexity and numerous steps required for providing these results, not so many samples could be tested to improve the statistics. Regardless, the lowest data point for any of these sets showed at least 65% recovery which is still a great figure for such large damages.

With this in mind, it appears that breakdown voltage recovery happens very quickly in the healing process, as long as the network has been reformed to some extent and that no gaps or thinned sections remained.

Discussion

While investigating such self-healing materials, the intent is not to entirely replace existing solutions but rather propose new design options that can be compatible with the same domain of use. Using these materials in conjunction with typical materials like FR-4 could be valuable as a strong interaction is expected with any epoxy/alcohol/ester group. Excellent bonding with most metals has also been observed but no quantitative data have been produced yet. Associating these materials with fillers/fibres is achievable and surface functionalization can even integrate the filler into the self-healing mechanism to increase bonding strength/repairability [25].

Conventionally, high-Tg thermosets are strongly favored for PCB manufacturing to reduce thermomechanical stresses, mostly because polymers often have a lower coefficient of thermal expansion (CTE) below their glass transition, thus reducing mismatches with other components such as copper or silicon. However, glassy polymers also exhibit a rather high and stable elastic modulus which is also a factor of thermal stress. In this regard, having a softer material capable of reducing the overall thermal stress above Tg could be suitable for strategies, from which selfhealing solutions emerge.

Indeed, vitrimer self-healing will only occur once chain mobility is achieved (above Tg) [26] and their mechanical moduli dramatically decrease near Tg. Overall, lower stress concentration could be expected above Tg.

Additionally, the ability of the network to reform dynamically can provide stress-relaxation above the topology freezing transition temperature (Tv) [22]. A smart behaviour could therefore be obtained, with a stiff low CTE material below Tg, a soft high CTE material above Tg, and a self-healing, stress-reliever material above Tv.

Conclusion

In this work, the applicability of a self-healing polymer (vitrimer) to the manufacturing of highly technical PCBs was investigated.

The vitrimer was successfully produced and its compatibility with the field of application was assessed. Results have shown that very high thermal stability and breakdown fields can be expected from such materials, two properties that are key in PCB design and manufacturing.

The ability to produce several semi-finished products (bulk samples, films, RCCs, PCBs) with satisfying conformity using press-molding was also demonstrated.

Self-healing of mechanical damages at 150°C for 1h was very efficient with most of the elastic properties recovered. Longer times or higher temperatures could help going a step further by recovering plastic properties.

Demonstration of dielectric breakdown voltage recovery after mechanical damage was provided. Longer heating times could increase the confidence on the selfhealing up to 99% of recovery after 1 hour against 85% after 5 minutes healing compared to a non-broken reference. This is encouraging for using these materials in a preventive strategy against voids formation that can trigger electrical events.

To complete this study, chemical formulation and implementation of fillers/fibres in the vitrimer matrix would allow to tune properties and thus improve the flexibility for the application field.

The creation of vias or multi-layered stacks are further steps for future PCB integration using these self-healing materials.

A study about healing of more relatable electrical events such as partial discharges has already been started.

Finally, gathering of more data could prove valuable to increase statistical power.

Figure 2

 2 Figure 2 FTIR spectra of precursors and the elaborated vitrimer

Figure 3

 3 Figure 3 Vitrimer thermal degradation in nitrogen and dry air Gathered in conditions close to the ASTM D3850, both curves show a very high thermal stability, with a 5% mass loss recorded at the temperature of 373°C in pure nitrogen and 362°C in dry air. Considering the temperature of 288°C used for delamination tests in IPC-TM-650 2.4.24.1,

Figure 5 A

 5 Figure 5 A) Pouring resin into the mold, B) Closing with copper foil, C) Pressing and curing, D) Cutting the RCC

Figure 6

 6 Figure 6 Left) End product, Right) RCC cross-section

Figure 8

 8 Figure 8 Tensile test of bulk samples before and after healing

Figure 10

 10 Figure 10 Stress concentration region. A) Pristine, B) Mechanical damage, C) Healed for 1h, D) After breakdown Results in Figure 11 compare the breakdown voltages of unbroken samples (Reference) with broken and repaired samples (Healed) that experienced different recovery times (5 min to 60min) at 150°C.The rate of recovery seems very satisfying as it only requires 5 minutes of healing to achieve at least 85% of the pristine breakdown voltage value. After one hour, the recovery increased to about 100%. These results seem ideal, however, there is a great dispersion of data points with the shortest healing times. Given the complexity and numerous steps required for providing these results, not so many samples could be tested to improve the statistics. Regardless, the lowest data point for any of these sets showed at least 65% recovery which is still a great figure for such large damages.

Figure 11

 11 Figure 11 Breakdown voltage recovery after mechanical damage and healing. Number of measurements in brackets

Acknowledgement

Authors would like to acknowledge the SCEL (Common Electronic Services) department for its support and expertise on PCB manufacturing.

Thanks to Céline Combettes and Sorin Dinculescu for their help and experience on press-molding, laser operations and breakdown tests


Murad M Shoman
email: murad.shoman@univ-eiffel.fr

Hocine Imine
email: hocine.imine@univ-eiffel.fr

Ennia Mariapaola Acerra
email: ennia.acerra2@unibo.it

Claudio Lantieri
email: claudio.lantieri2@unibo.it

Evaluation of cycling safety and comfort in bad weather and surface conditions using an instrumented bicycle

Keywords: Bicycle Instrumentation, Experimentation, Cycling Safety and comfort, Road characteristics, Cycling Risk Indicator

Understanding how vulnerable road users (cyclists and pedestrians) behave enables the construction of better roadways with adapted geometric and surface design which leads to improve cycling safety and comfort. This study examines the behavior of cyclists using an instrumented city bicycle that allows collecting exact data about bicycle dynamics, trajectory, and speed, as well as essential information to study the behavior of the cyclists, their reaction to the different features of the road surface and geometric design, and their interaction with other road users such as pedestrians, vehicles and other cyclists. 22 cyclists participated in an experiment following a predetermined route in Stockholm, Sweden. The route consisted of a circuit with different types of cycling facilities in order to study the different interactions (cyclistcar and cyclist-pedestrian), the circuit was divided into 3 zones: the first is mixed traffic, the second is a separate cycling lane and the third is shared pedestrian-cycling path. The results show significant data to evaluate cycling safety and comfort in snowy weather conditions and the perception-reaction behavior of cyclists; accordingly, the infrastructure-related risks were evaluated from subjective and objective points of view. In this paper, we propose a new concept to evaluate cycling behavior. This concept allows us to evaluate cyclists' behavior through the calculation of Behavioral Risk Indicator (BRI) based on different risk factors owing to weather, road and traffic conditions, interaction with other road users and reaction to infrastructure drawbacks. The applications of the proposed concept allow us to evaluate the risks caused by multiple traffic factors and infrastructural drawbacks and study cyclist-bicycle-road interactions and their influences on cycling safety. In addition, the concept provides a new foundation for establishing cycling safety measures that could be applied to improve the infrastructure and reduce traffic accidents in order to attract more people to ride bicycles.

I. INTRODUCTION

R OAD traffic crashes represent the eighth leading cause of death worldwide, with more than 1.35 million fatalities each year and up to 50 million injuries [START_REF] Organization | Global status report on road safety 2018[END_REF]. More than half of all road traffic fatalities are among vulnerable road users (pedestrians, cyclists, and motorcyclists); in fact, several countries reported an increased number of fatalities among cyclists in recent years, probably reflecting the increased popularity of this mode of travel [START_REF] Santacreu | Safer city streets global benchmarking for urban road safety[END_REF]; cycling fatalities represents 4% of traffic fatalities with more than 50 000 deaths per year [START_REF] Organization | Global status report on road safety 2015[END_REF]. A study by [START_REF] Haddak | Exposure-based road traffic fatality rates by mode of travel in france[END_REF] shows that the risk for a cyclist to be killed in a traffic accident is 3 times higher than for a car driver when considering the time spent in transportation. Cycling also poses a risk to other road users, in 2016, three pedestrians were killed in crashes with cyclists in the United Kingdom [START_REF] Reynolds | Reported road casualties great britain: 2016 annual report[END_REF].

In the European Union, more than 2000 cyclists are killed annually, which represents 6% of all traffic fatalities [START_REF] Fredriksson | Pre-crash motion and conditions of bicyclist-to-car crashes in sweden[END_REF]. In Sweden, 17 cyclists were killed in 2019 (8% of all traffic fatalities), in 2018, 921 persons suffered Maximum Abbreviated Injury Scale (MAIS) in-which 40% were cyclists [START_REF]Road safety report, sweden[END_REF]. In Norway, the risk of injury, expressed as fatalities per kilometer, for cyclists is about 7.5 times higher than for car drivers [START_REF] Pucher | Making walking and cycling safer. lessons from europe[END_REF], [START_REF] Elvik | The non-linearity of risk and the promotion of environmentally sustainable transport[END_REF]. In the Netherlands, bicycles cause around 5.5 times as many fatal injuries per kilometer as cars do [START_REF] Forum | Cycling Safety Summary and Conclusions[END_REF]. A study in Portland (US) reported that nearly one in five cyclists experienced an event leading to injury, regardless of gender, age, body mass index (BMI), or cycling skill level [START_REF] Hoffman | Bicycle commuter injury prevention: it is time to focus on the environment[END_REF]; injuries were mainly caused by 'slipping' (35%) or 'collision with a car' (19%). In 2015, in Japan, among 4117 traffic fatalities, 572 (13.9%) cyclists were killed [START_REF] Matsui | Features of fatal injuries in older cyclists in vehicle-bicycle accidents in japan[END_REF] where the most frequent cause of death was head injuries [START_REF] Oikawa | Traffic accidents involving cyclists identifying causal factors using questionnaire survey, traffic accident data, and real-world observation[END_REF]. In France, despite the fact that cycling represents 2.7% of all commuting trips, cyclists represent 5% of accidents mortality; in 2017, 173 cyclists were killed in road accidents (which represents an increase of 6.8% compared to 2016), 68 % of them were over 50 years old and 44% were over 65 years [START_REF]national Interministériel de la sécurité routière, La sécurité routière en France Bilan de l'accidentalité de l'année[END_REF]; this value has never been reached since 2006 (181 were killed). 93% of people killed or hospitalized in accidents involving a cyclist were cyclists; 12% of them were killed or hospitalized during self accidents and 3% in accidents with another cyclist. According to a survey in 2005, only 14.5% of cyclists in France wear helmets, despite the fact that helmets can help to reduce the severity of accidents. [START_REF] Richard | Evolution of bicycle helmet use and its determinants in france: 2000-2010[END_REF].

Looking at the causes of cycling accidents, the literature shows that the 'Imprudence' of the cyclist was the cause of the accident in 26% of reported cases, and 'Distraction' was responsible for 11% of accidents [START_REF] De Geus | A prospective cohort study on minor accidents involving commuter cyclists in belgium[END_REF]. In Belgium, a study showed that men have more accidents than women as they cycle more frequently for a longer time and larger distances. (83%) of the investigated accidents that occurred during a trip to or from work, 53% of the accidents took place during the morning peak hours and 17% during the evening peak hours [START_REF] De Geus | A prospective cohort study on minor accidents involving commuter cyclists in belgium[END_REF]; the morning peak hours are the most dangerous moment of the day to cycle to work [START_REF] Kim | Bicyclist injury severities in bicycle-motor vehicle accidents[END_REF], this could be explained by the aggressive behavior of both motorists and cyclists during the busy morning commute which increases the likelihood of having an accident [START_REF] Kim | Bicyclist injury severities in bicycle-motor vehicle accidents[END_REF].

Another study shows that a typical collision involving cyclists being hit by turning motorized vehicles occurred due to the cyclist's presence in the blind spot of the driver [START_REF] Schoon | The circumstances of blind spot crashes and short-and long-term measures: a crash analysis over the years 1997-2007, traffic observations, and surveys among cyclists and lorry drivers[END_REF]. Cycling accidents may also occur due to the combined effect of low visibility near intersections and the cyclists' behavior in terms of their velocity [START_REF] Jacobsen | Safety in numbers: more walkers and bicyclists, safer walking and bicycling[END_REF]. The safest areas tend to be where people cycle the most and where cycling infrastructure is most developed [START_REF] Forum | Cycling Safety Summary and Conclusions[END_REF]; this is known as the "safety in numbers" effect, and applies to both cyclists and pedestrians: The greater the number of cyclists, the more they are expected and observed, and so the risk decreases [START_REF] Jacobsen | Safety in numbers: more walkers and bicyclists, safer walking and bicycling[END_REF]. According to the literature review, bicycle instrumentation could be used for different purposes and contexts such as: determining the trajectory classes for cyclists, collecting naturalistic cycling data, studying the bicycle's dynamics, and defining cyclists' behaviors. For example, a bicycle was instrumented with gyroscope, accelerometer, absolute encoder, and hall effect sensors to determine the trajectory of cyclists in London [START_REF] Miah | An innovative multi-sensor fusion algorithm to enhance positioning accuracy of an instrumented bicycle[END_REF]. In [START_REF] Escalona | A bicycle model for education in multibody dynamics and real-time interactive simulation[END_REF], [START_REF] Escalona | Validation of multibody modeling and simulation using an instrumented bicycle: from the computer to the road[END_REF] the researchers used an instrumented bicycle to validate a multi-body model. The bicycle was equipped with five sensors i.e. an inertial measurement unit (IMU), an inclinometer, and incremental rotary encoders. In [START_REF] Etemad | Using an instrumented bicycle to help understand cyclists' perception of risk[END_REF] the researchers used a bicycle equipped with GPS, video camera, accelerometer, compass, and gyroscope to discover and characterize conflict points between cyclists and other road users.

In Gothenburg (Sweden) a bicycle was equipped to collect naturalistic cycling data, the instrumentation consists of two cameras (one facing forward and the other facing the cyclist's face), a GPS, two inertial measurement units (IMU), two pressure brake sensors, a speed sensor, and a push-button (to allow the cyclist to report any risks) [START_REF] Dozza | Piloting the naturalistic methodology on bicycles[END_REF]. The outcomes reveal that cycling near crossings increases the danger, particularly when there is sight blockage (e.g., buildings and hedges), whereas poor maintenance and road surface condition raised the risk by ten times [START_REF] Dozza | Introducing naturalistic cycling data: What factors influence bicyclists' safety in the real world?[END_REF], [START_REF] Dozza | Using naturalistic data to assess e-cyclist behavior[END_REF]. [START_REF] Walker | The influence of a bicycle commuter's appearance on drivers' overtaking proximities: An on-road test of bicyclist stereotypes, high-visibility clothing and safety aids in the united kingdom[END_REF] have studied the effect of the appearance of cyclists on drivers' overtaking proximity, it was found that overtaking distance decreases when vehicles pass a male cyclist, a cyclist wearing a helmet, or a cyclist cycling away from the road's edge. Whereas in [START_REF] Chuang | The use of a quasi-naturalistic riding method to investigate bicyclists' behaviors when motorists pass[END_REF], the results show that the passing distance decreased when motorcycles overtake a cyclist compared to cars and small trucks. Cyclists appeared unstable when a bus (longer passing time) passed them. Another study by [START_REF] Parkin | Estimation of the determinants of bicycle mode share for the journey to work using census data[END_REF] shows that vehicle drivers do not provide a comfortable passing distance to cyclists in the adjacent cycling lane.

To shed light on the safety of vulnerable users, this study analyzes how the infrastructure affects the behavior of weak users and in particular how their interaction takes place. An on-site test was conducted in Stockholm with 22 cyclists, using an instrumented bicycle to trace the kinematic parameters during the route. This paper presents an innovative approach that deals with an objective evaluation of behavior related to the use of sensors, and a subjective one that is extrapolated by questionnaires answered by each participant. The paper is structured as follows: the second part is devoted to the experimenting procedure; the third part describes the experimentation conducted using the instrumented bicycle and discusses the results of all participants; the fourth part is dedicated to the analysis of the eye-tracker videos and the behavior of cyclists and their interaction with the road infrastructure and other road users; the fifth part shows the analysis of the questionnaire answered by the participants regarding their evaluation of cycling safety and comfort, and finally the conclusion.

II. EXPERIMENT PROCEDURE

A. PARTICIPANTS

22 cyclists were involved in the study, 14 male (Mean age =37.9, SD=±13.4 ) and 8 female(Mean age =32.4, SD=±14.1). They were recruited by sending emails to the students and employees of the Royal Institute of Technology in Stockholm (KTH) and the Research Institutes of Sweden (RISE) and posting on the social media groups of Stockholm. Participants represented a homogeneous sample, which had an average cycling experience of 30.9 years (SD: ±15.9) for males and 26 years (SD: ±15.8) for females, an average cycling frequency of 4.9 trips/week (SD:±2.3) for males and of 3.1 trips/week (SD: ±2.2) for female and an average cycling distance of 43.9 km/week (SD:30.5) for males and 34.4 km/week (SD: 25.5) for females. 64% of the users are familiar with the experiment route (57% of males, 75% of females).

B. EXPERIMENT ROUTE

The route (3.6 km) was located in the north of Stockholm, it begins and ends at the Integrated Transport Research Lab (ITRL). The circuit is divided into three zones considering the different use of the road and the geometric design (Fig. 1):

1) zone 1 consists of a mixed-traffic street with a 30 km/h speed limit without a separate cycling lane; 2) zone 2 includes an on-street separate cycling lane without a physical barrier for most of it and a shared bicycle-bus lane for the rest; 3) zone 3 consists of a shared pedestrian-cyclist way passing between trees and parking lots that separate the path from passing traffic.

C. PROCEDURE

In the beginning, the participants signed a standard consent form including brief details about the experiment, the data collected, and the following analysis. After the adjustment of the sensors, they were asked to wear a helmet and a reflective vest (optional) and to follow the predetermined cycling path using GPS map displayed on a mobile mounted on the handlebar. The test was composed of two sessions: 1. in the first session, the temperature was -3 to -11 degrees, and the road surface was a mix between snow sludge and ice along the experiment route; 2. in the second session, the temperature was 3 to 9 degrees, and the surface was wet in some places and dry in others with accumulated snow sludge at some spots like intersections. During the test, each participant passed through eleven traffic lights, four of them intersected major roads (main crossings), whereas the rest intersected secondary roads. After the cycling task finished, the participant completed a questionnaire related to personal general information such as age, gender, weight, and cycling experience; and their evaluation of the experiment route regarding safety and comfort.

D. INSTRUMENTATION

The participants had to use two definite instruments: an instrumented bicycle and a mobile eye tracker. The special glasses called Tobii Pro-Glasses 2 is a Mobile Eye-Tracker created to record the gaze of the participant during the experiment, a visual angle of 82°horizontal and 52°vertical, a microphone to record the ambient sounds, and protective lenses.

A city bicycle with winter tires and a single-speed transmission system was used in this experiment (Fig. 2), the following sensors and devices were installed on the front and rear parts of the bicycle: 1. Hall Effect Sensor to count the number of rotations per minute (RPM) for the front wheel to calculate its angular velocity. 2. A triaxial accelerometer. 3. Garmin Edge 130 plus includes a positioning system and internal memory to save data from other Garmin sensors. 4. A potentiometer to measure the steering angle. 5. Inertial Measurement Unit (IMU) unit and a GPS. 6. A laser scanner. 7. Power source. 8. A speed sensor. 9. Power meter pedals. 10. Cadence sensor.

III. RESULTS AND DISCUSSION

In order to study the different factors influencing cycling safety, a specific data analysis has been carried out. In fact, the cyclist's behavior was studied in both an objective view, evaluating the results of the instruments used, and a subjective one, by analyzing the questionnaire given to the participants.

A. KINEMATIC OUTPUTS ANALYSIS

The use of Garmin system allowed us to quantify the behavior of cyclists in terms of speed, power, and cadence. All these factors have been 'normalized', i.e. zero values were eliminated (when the cyclist was stationary). Fig. 3 shows the average normalized speed for all participants for the complete experimental route, and separately for each zone in both snowy and dry surface conditions. Comparing cycling in both conditions, it is noticed that the speed decreases by 15% (from 15.73 km/h in dry conditions to 12.45 km/h in snowy conditions). This speed reduction could be explained by the cyclists' cautiousness to avoid slipping and other weather-related risks. The average speed when cycling on a dry surface matches the universal average cycling speed, which is 16 km/h [START_REF] Boufous | The impact of environmental factors on cycling speed on shared paths[END_REF].

The highest average speed for all participants was recorded in zone 2 with 13 km/h on snow and 17 km/h on dry surface conditions, this could be explained by the existence of a separate cycling lane on a flat-straight street. In zone 3, where the geometry is similar to zone 1 but surface and traffic conditions are different, the average speed decreased to 12 km/h in snowy and 15 km/h in dry surface conditions; this could be due to the increase of conflict when sharing cycling path with pedestrians; this complies with the results found in the literature [START_REF] Eriksson | An analysis of cyclists' speed at combined pedestrian and cycle paths[END_REF]. On the other hand, the effect of slopes on cycling speed appears when comparing zone 1A (snow: 12.4 km/h, dry: 17.2 km/h) where the slopes are mostly downhill, and zone 1B (snow: 11.6 km/h, dry: 14.4 km/h) where the slopes are mostly uphill. The average maximum speed for all participants was recorded in zone 2 with 20.2 km/h on snowy and 24.4 km/h on dry surfaces, whereas the maximum individual speed is 26.2 km/h on snowy and 29.9 km/h on dry surfaces. Moreover, in zone 3, the legislation suggests a speed limit of 10 km/h for the cycle-pedestrian shared path [START_REF] Short | Estimating bicyclist into pedestrian collision speed[END_REF]; this limit was not respected by cyclists, particularly when the surface is dry. The average normalized speed on the snowy surface for male participants is 13.8 km/h and 10.8km/h for females, the maximum speed recorded was around 17.5 km/h for a 46-year-old male, while the minimum speed of 7.2 km/h was recorded for 58 years old female.

Fig. 4 shows a difference between cycling on dry or snowy surface conditions; comparing the data for each zone, it can be seen that the average normalized power for zone 1b is the highest in both dry and snowy conditions; this is explained by the uphill slope at the beginning of the zone, on contrary, the power consumed in zone 1A is the lowest since the slope was mostly downhill. In some cases, the consumed power does not reflect the correspondent speed, for example, in zone 2 where the highest average and maximum speed were Fig. 5 shows the average cadence in different zones and surface conditions. The average cadence for the complete route on the snowy surface is 50 RPM, whereas it rises to 60 RPM in dry conditions, as users gain confidence in driving due to increased wheel-road grip. The cadence recorded in zone 2 which records the lowest value, shows an opposite trend to the speed, which records the highest average compared to other zones, this shows that the increase in speed is not necessary due to the cadence rate. Zone 1B recorded the highest cadence and power and the lowest speed; this could be explained because of the slipperiness between the wheel and the road surface and the negative impact of the uphill slope.

B. ANALYSIS OF PERCEPTION-REACTION LOOP USING THE EYE-TRACKER VIDEOS

19 videos were recorded using the mobile eye-tracker, 16 of them on snowy surface conditions and 3 on dry surface conditions. These videos were analyzed in detail to study cyclists' behavior and their interaction with different features of the infrastructure and with other road users. The results show that when cyclists approach the two-way cycling path in zone 1 and 3, 62% of the participants cycled on the right side, whereas in 33% of the cases, they cycled to the middle or left side of the path, opposing cyclists possibly approaching from the opposite side. This could be explained by the lack of vision of the markings and the separating line due to the snow accumulation, in one case the cyclist had to use the left lane to avoid collision with pedestrians walking on the cycling path. It is also noticed that in 5% of the cases, the cyclists did not use the cycling path, due to the lack of attention to the traffic vertical signs and the absence of on-street marking that leads to it.

Analyzing the interaction with cars, the results show that in zone 1, when cycling on-street without a dedicated cycling area, 50% of the participants cycled in the middle of the street, unless when a car was approaching from behind, they slide to the right allowing it to pass; 31% cycled on the right side of the street and 19% cycled behind cars without passing them. This risky cycling behavior is explained by the lack of space on the right side because of the snow accumulation. On the other hand, the video analysis shows that in 3 cases there was a risk of collision with parked cars leaving their spots, where the cyclist braked heavily and stopped shortly before the car. In zone 2, there were 3 risks of collision because of the heavy traffic and cars blocking the cycling lane. When encountering a red traffic light, the results show that in 14% of the cases, the cyclists slowed down until waiting for the signal to turn green, while in 11% of the cases they broke the traffic light without slowing down. In the case of stopping, the majority (62%) stopped at less than 1 m from the traffic light (Fig. 6). On the U-turn between zone 2 and 3, where the zebra crossing is painted and a traffic signal is absent, the results show that 61% of the participants looked back to check the traffic and then turned left and crossed the street, whereas in 11.1% of them crossed with looking back (Fig. 7), this behavior may put them in danger, as depending on hearing is not sufficient, especially with the spread of electric cars which have silent motors. Studying the interaction of cyclists with pedestrians crossing the street shows that in only 4% of the cases the cyclists stopped when realizing the pedestrians were waiting to cross. In 44% of the cases, the cyclists continued cycling in front of pedestrians, after they started crossing the street, whereas in the rest of the cases (52%) the cyclists slowed down allowing pedestrians to cross, then accelerate again when the crossing is clear. The videos analysis shows that in zone 1, there was a risk of collision with pedestrians in 7 cases, mainly because the cyclist did not stop. In zone 2 there was a collision risk with one pedestrian for the same reason. In other cases, some cyclists crossed the street between pedestrians at the traffic light, which caused discomfort for both sides. In zone 3, where the cycling path is shared with pedestrians, 28% of the cyclists passed the pedestrians from the left, 67% switched between passing from right or left, and 5% passed always from the right side. When the cyclists crossed the streets going through the cycle-pedestrians zone, in 28% of the cases they did not give attention to the crossing traffic and contained cycling normally, whereas in the rest of the cases they checked for oncoming traffic before crossing.

When interacting with buses in zone 2, in 43% of the cases, cyclists passed the bus from the left while giving attention to their left and checking for passing cars, whereas in 43% of the cases, they stayed behind the bus, and in 14% of the cases they passed the bus from the right side when they got enough space from empty parking spots. One cyclist said he would rather not cycle on a bus lane since he can not hear the bus sound.

C. SUBJECTIVE EVALUATION OF CYCLING SAFETY AND COMFORT

After the end of the experiment, the participants filled out a questionnaire in regard to their cycling experience and their evaluation of cycling safety and comfort during the experiment. They were handled a map showing the different zones of the experiment in order to help them to answer the questionnaire properly. Table 1 summarizes the general data collected by the participants and some of their responses about the risks facing them when cycling in cold weather and snowy surface condition.

It is noticed that the cyclists, who were using winter tires before the experiment, felt a higher grip, especially on ice patches. The cyclists who use them for the first time confirmed this and reported they felt a better grip and were more stable (7 out of 11 agreed on that). However, some participants felt that they consumed more effort compared to regular tires. One participant commented: 'The winter tires were better than regular ones on the ice and hard-packed snow, but no difference on looser snow; however, the friction on the dry road is higher compared to regular tires.' In regards to the effect of wind on cycling comfort, 6 participants experienced a negative impact of the wind, not only due to the effort increase but also the discomfort felt when the cold wind blows on their faces and eyes.

Fig. 8 shows the response of all the participants regarding their evaluation of safety for each zone along the experiment route. The results show that 13 participants (59%) chose the 3rd zone as the safest. They explained their choice by the absence of passing vehicles; the wide separation to the carriageway; the flatness of the road; and even though the surface was covered with snow, it was hard and covered with gravel which reduce slipperiness. These outcomes are consistent with the literature that confirms that safety is associated with protected and separated bike facilities [START_REF] Marshall | Why cities with high bicycling rates are safer for all road users[END_REF]. Contrary to the fact that most participants chose zone 3 as the safest, 5 of them (23%) ranked it as the least safe due to the existence of pedestrians, and the lack of traffic lights at some intersections. 12 participants (55%) chose zone 2 to be the least safe, this is mainly because of its stance on the carriageway without a physical barrier with passing traffic; the constraint to cycle on the carriageway as the cycling lane was covered by snow and ice (as seen in the recorded videos; the snow was evacuated from the carriageway and accumulated on the cycling lane); and the sharing the lane with buses, which were not loud enough to be detected; one of the participants commented 'The bike lane was very icy and I had the feeling I could fall quite unexpectedly, and cars overtake me at a quite high speed.' On the other hand, zone 1 (A+B) was ranked the safest 7 times (32%) and the second safe 16 times (73%), this significance is explained by better surface conditions (less snow and ice); and low and slow traffic. On contrary, the participants who chose it as the least safe explained their feeling by the steep slopes towards the end of the zone and the absence of a separate cycling lane.

Considering cycling comfort, 17 participants (77%) chose zone 1B as the most power-demanding among the three zones; they explained this mainly because it is located on an uphill street with steep slopes, however, 3 of them mentioned it was because it locates towards the end of the experiment route where they got exhausted. On contrary, the 3 who chose zone 1A said they consumed more power because it was downhill. 20 participants said that cycling on snow sludge is the hardest, whereas 2 said it is harder to cycle on ice (Fig. 9). Fig. 10 shows the evaluation of the participant of comfort when cycling on different surfaces and different traffic sections; it is noticed that 9 of them (50%) chose zone 2 as the most comfortable and 9 (41%) as the second most comfortable. The reasons behind that according to them are the scariness of snow sludge, the smooth and flat surface, and the separate cycling lane. Zone 3 was chosen to be the least comfortable by 9 participants due to the unevenness of the surface caused by small stones spread on top to reduce slipping, the accumulation of snow-sludge mixed with dirt coming from the unpaved surface, and the existence of pedestrians. 8 (36%) chose zone 1B to be the least comfortable due to the steep slopes and the snow accumulation. Regarding the participants' perception of cycling on a snowy surface, the results show that all participants increased their effort and reduced their speed to avoid slipping, besides, they experienced steering difficulty when cycling on snow sludge and ice, with the possibility to get stuck in dips and grooves left by previous bikers, walkers, and prams. 6 participants experienced foot-slip upon stopping especially at the red lights, 3 of them anticipated this to happen and slowed down before stopping. Considering the weather conditions, 9 participants evaluate the test as less safe for the cold situation besides the discomfort due to wearing special clothes and thick gloves which limits body movements and impairs visibility.

D. EVALUATION OF INFRASTRUCTURE RELATED RISKS AND ASSOCIATED CYCLIST' BEHAVIOR

After the analysis of the different outputs of the sensors (details published in [START_REF] Shoman | Bicycle instrumentation and analysis of the output signals[END_REF]), the eye-tracker videos, and the post-experiment questionnaire, the effects of road surface characteristics and geometric design on the behavior of cyclists and their interaction with other road users were studied. In the following points, we present different evaluated risks, caused by the geometric misdesign or lack of maintenance of the road surface, the associated behavior of cyclists, and the type of accident related to these risks. A comprehensive summary is shown in Appendix A. 1) The decreased low adhesion, due to the icy/snowy surface condition, may lead to the sliding of the bicycle's wheels or foot slipping when the cyclist stops. The analysis of the videos and the questionnaire show that 6 participants experienced foot slippery when stopping and all of them experienced wheel slippery because of the ice and snow accumulation. In order to reduce the impact of low road adhesion, cyclists need to increase attention, reduce their speed, use winter tires for their bicycles, and wear appropriate winter shoes to improve contact when stepping on a slippery surface. 2) By analyzing the output signals of the IMU, the triaxial accelerometer, and the laser scanner, it is possible to correlate vertical acceleration, lateral acceleration, and yaw rate to the calculated road profile. The analysis of the signals shows that the unevenness of the road, caused by the misimplementation or damage of the road surface, leads to an increase in the vertical acceleration, this increase of the vertical acceleration -besides affecting cycling comfort [START_REF] Niska | Determination of riding comfort on cycleways using a smartphone app[END_REF], [START_REF] Koike | Unevenness of intersection pavement and bicycle safety[END_REF]-leads to an increase in the lateral acceleration and roll rate. This lateral instability of the bicycle may subsequently lead to rollover or lane departure. The analysis of the eyetracker videos revealed the reaction of cyclists when encountering road surface defects such as cracks and potholes; the cyclists react in three different ways: the first is avoiding the defects in the road surface which leads to lane departure, the second is reducing their speed to minimize the impact on their stability and comfort, and the third is continuing cycling at the same speed when they do not notice the defect or have limited time to react; this behavior may put them in risk of rollover. In order to avoid the risks associated with road surface damage, cyclists are advised to repeatedly check the road surface to detect any defects at an early stage to take the right decision whether by avoiding them without conflicting with other vehicles or slowing down in case they are unavoidable. This finding is correlated to the outcomes of [START_REF] Gadsby | Understanding the influence of pavement conditions on cyclists' perception of safety and comfort using surveys and eye tracking[END_REF] which shows that potholes were the most significant pavement distress for perceived comfort and safety; the eye-tracker data analysis showed that unevenness of the road surface drew the greatest fixations for the longest period, potentially raising a safety risk. Another research shows that building better surfaces will improve safety feeling and encourage more people to ride bicycles [START_REF] Niska | Determination of riding comfort on cycleways using a smartphone app[END_REF].

3) The increase of conflict points with pedestrians at intersections and on the shared pedestrians-cycling path increases the possibility of collision with them, especially when exceeding the speed limit when sharing the cycling path with pedestrians. In order to reduce this conflict, it is recommended to separate cyclists' crossings from pedestrians' by adding a distance of 1 or 2 m between them; moreover, it is safer and more comfortable to build special infrastructure for cycling independent from walking areas and separate them with barriers or clearance zone. 4) The existing vertical and horizontal traffic signs and road markings did not properly direct the cyclists to follow the cycling lanes, the analysis of the eye-tracker videos and the subsequent questionnaire show that some cyclists failed to follow the bicycle lane in zone 1 as they did not detect it due to the absence of appropriate signs and unfamiliarity with the experimental route, this increased the conflict with vehicles, as cyclists were forced to cycle on-street, which may lead to a collision with other vehicles. In order to better direct cyclists, it is recommended to increase the number of traffic signs and place them within the field of view of the cyclist; to paint directional arrows on the pavement; use a different pavement color for cycling lanes, and channelize the intersection to separate the different types of traffic. Previous research showed that the reduction in conflicts leads to remarkable safety improvement after conducting smart channeling [START_REF] Ghasemi | Longitudinal motion cueing effects on driver behaviour: a driving simulator study[END_REF], [START_REF] Zheng | Application of extreme value theory for beforeafter road safety analysis[END_REF]. 5) The low radius of curvature, due to inappropriate design and limited space, leads to an increase in lateral acceleration and roll rate as noticed when analyzing the date of IMU, the potentiometer, and GPS signals, for example, we can notice the increase in steering angle on sharp curves and its impact on roll rate and lateral acceleration. In order to better understand cyclists' turning behavior, the intersection between zone 1 and 2 was analyzed for all participants where they had to turn left on a low-radius-of-curvature curve (angle of curvature less than 90 ). By analyzing the steering angle signal, it was found that at the maximum steering angle the lateral acceleration and roll rate severely increased for all participants. It is also noticed that some participants did not follow the cycling path in order to increase the radius of curvature and reduce the steering angle, for example, one participant steered the handlebar at an angle of 23 but he left the cycling lane which led to a dramatic increase of in lateral acceleration (18 m/s 2 ). The increased lateral acceleration and roll rate are indications of rollover risk, as found in [START_REF] Joo | A new approach to analyzing cycling stability using an inertial measurement unit sensor[END_REF] where the analysis shows that lateral stability decreases when maneuvering a bicycle handlebar in either right or left directions. However, some cyclists did not follow the cycling lane in order to increase their turning radius and maintain their speed, this lane departure may lead to a collision with other vehicles passing by. To solve this issue, the radius of curvature should be designed to accommodate the cyclists' needs, or a physical barrier should be added to force cyclists to follow the cycling path and reduce their speed. 6) The absence of any physical barrier between cycling lanes and other modes of traffic leads to an increase in conflict points and may cause a collision, in addition, other road users may invade the cycling space and decrease the feeling of safety as mentioned by some participants who experienced a risky situation because of cars parking or driving on the cycling lane. A study implemented in Toronto, Canada shows the impact of protected cycle tracks. The results showed a decreased risk of collision for cyclists following its construction, besides the added benefit of increasing the number of cyclists using cycling facilities in these areas [START_REF] Ling | Cyclist-motor vehicle collisions before and after implementation of cycle tracks in toronto, canada[END_REF]. 7) Sharing cycling facilities with pedestrians increases the risk to collide with them and reduces their comfort and safety feeling. On the other hand, cyclists have to reduce their speed to adapt to the pedestrians and maneuver amongst them as their walking behavior is unpredictable. 8) Cycling on a shared bus-bicycle lane reduces the safety feeling of cyclists, especially when buses are electric, they become less predictable as they have silent motors. The conflict occurs when the bus stops. The cyclist has to decide to pass or stop waiting for the bus to move again. The passing decision is harder as the passing time increases, and loss of attention may lead to a collision with other passing vehicles when invading the carriageway. In order to reduce this risk it is recommended to add a separate passage for cyclists behind the bus stop to avoid conflict with pedestrians and stopping buses; in addition to smooth passing for cyclists. 9) The increase of longitudinal slopes leads to increased speed when cycling downhill, and decreased speed and increased power when cycling uphill. In order to mitigate the effect of high slopes, road designers should consider, when designing cycling paths, the physical abilities of cyclists when cycling uphill and the required stopping distance in case of breaking downhill. 10) Breaking red traffic lights by cyclists without keeping attention may lead to collisions, especially on intersections with reduced sight distance, due to existing buildings limiting the sight of cyclists and the drivers approaching from the transversal street. 11) Cycling in narrow spaces between cars or other road furniture increases the chance of collision and limits cyclists' field of view. The analysis of the eye-tracker videos shows that some cyclists were cycling very close to cars, especially in parking lots, and sometimes they had to heavily break to avoid collisions with cars leaving the parking zone. In order to avoid this it is recommended to construct cycling paths away from parking lots or add physical barriers between cycling paths and on-street parked cars. 12) Lack of attention when crossing the street: it was noticed in zone 3 when cyclists cross multiple streets that they do not look around and seem they only depend on their hearing, even though hearing is very important to detect passing vehicles, looking around still necessary especially with the emerge of elect-silent vehicles. The combination of infrastructure parameters drawbacks and the associated cyclists' behavior, which are listed in Appendix B, were used to calculate RI by applying (1):

RI = B.S n (1)
Where B represents the errant behavior of the cyclist when interacting with the infrastructure or other road users, S is the severity of the possible accident, and n is the number of parameters under investigation. The different parameters used to calculate the safety indicator are attached in Appendix B. The risk indicator (BRI) ranges between 0 and 10 (0 the safest and 10 the riskiest); the cyclist's behavior is considered 'Risky' if the behavioral risk indicator (BRI) is above 5, whereas it is considered 'Safe' if BRI is equal or less than 5. The analysis of the cyclists' safety profiles (Fig. 11) shows that 30% of the participants have risky behavior, their ages range between 22 and 32 years, 45% of males and 17% of females have risky behavior.

IV. CONCLUSION

This paper shows an important study of cycling safety in extreme weather and surface conditions, considering the design and maintenance of the infrastructure and the behavior of cyclists. The evaluation of cycling safety and comfort in snowy conditions was investigated through a case study in the city of Stockholm, where an instrumented bicycle was used to conduct an experiment involving 22 cyclists. The experimentation results for all participants, the subsequent questionnaire, and the eye-tracker videos were analyzed. The findings indicated some of the dangers that cyclists face, particularly in risky weather conditions; in many cases, the accumulation of snow drove riders to leave their cycling paths putting them at risk of collision, for example, in zone 2 where the cyclists were forced cycle closer to passing vehicles. It was also found that cyclists' risky behavior may put them and other road users in danger; examples include breaking red lights, passing pedestrians from the right side, and crossing streets without paying enough attention. The subjective evaluation of cycling safety shows that the participants felt safer in zone 2, where there is a separate cycling lane, even A direct impact of road surface characteristics and infrastructure geometric design was observed on cyclists' behavior. The reaction of cyclists to the drawbacks of the infrastructure was evaluated to calculate the Behavioral Risk Indicator (BRI) for each cyclist and classify the behavior as risky or safe. This indicator could be used more broadly in testing cycling infrastructure adequacy and its impact on cyclists' behavior. Based on the analysis of the behavioral risk indicator (BRI) for the experimental route in Stockholm, different measures are recommended to improve cyclists' behavior and reduce the probability of accidents including:

• Maintaining the road surface to make it more even and smooth for cyclists, in fact, a well-maintained cycling facility encourages more people to cycle, as it is essential for the safety, accessibility, and riding comfort of cyclists.

• Removing the accumulated snow from the cycling lane will improve road adhesion provide more space for cyclists, and reduce the risk of sliding or slipping. • Installing a physical barrier between cycling lanes and carriageways reduces the conflict, and the risk of collision with other vehicles, besides improving the feeling of safety which encourages people to cycle more. • Separate cycling and pedestrian paths, which may improve comfort and reduce the risk of collision with pedestrians.

• Improving the communication between the road designer and cyclists through the proper installation of vertical and horizontal signs will help to give the right directions to cyclists, warn them of possible risks, and advise them to take the right actions. In the future, the output signals and the behavior of cyclists will be compared to the outputs of PICS-L bicycle simulator after the reproduction of the same environment and scenario in virtual reality. This comparison will further be used to study the behavioral, physical, and subjective validity of the simulator. The validity of the simulator will allow for conducting more experiments to test different scenarios and measures to improve cycling safety in a secure environment inside the lab before applying them on-street.

FIGURE 1 .

 1 FIGURE 1. The predetermined route of the experiment in Stockholm.

FIGURE 2 .

 2 FIGURE 2. Schematic of the instrumented bicycle, more details about the different sensors following the correspondent numbers below.

FIGURE 3 .

 3 FIGURE 3. The mean normalized speed using Garmin speed sensor, the data categorized according to gender and different zones of the experimental route.

  recorded.

FIGURE 4 .

 4 FIGURE 4. The mean normalized power extracted from the pedaling power meter from Garmin.

FIGURE 5 .

 5 FIGURE 5. Cadence extracted from the cadence sensor of Garmin.

FIGURE 6 .

 6 FIGURE 6. The reaction of cyclists when encountering red traffic lights.

FIGURE 7 .

 7 FIGURE 7. U-turn crossing behavior between zone 2 and 3 with the absence of traffic light.

VOLUME 4, 2016 5

 2016 This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2023.3242583

FIGURE 8 .

 8 FIGURE 8. The evaluation of the participants of the safety for the different zone of the experiment route, the numbers on the bars represents the number of the participants who voted for the mentioned zone.

FIGURE 9 .

 9 FIGURE 9. The response of the participants about where they consumed more power comparing between zones.

FIGURE 10 .

 10 FIGURE 10. The response of the participants about where they felt more comfortable comparing between zones.

VOLUME 4, 2016 7

 2016 This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2023.3242583 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/

FIGURE 11 .

 11 FIGURE 11. The behavioral risk indicator for the cyclists who participated in the Stockholm experiment.

VOLUME 4, 2016 9

 2016 This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2023.3242583 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ though a physical barrier between the cycling lane and other vehicles is missed.

TABLE 1 .

 1 Descriptive characteristics of the study group (means ± SD or N %)

	Characteristic	Male	Female	Total
	N	14 (64%)	8 (36%)	22
	Age (yrs)	37.9 (±13.4) 32.4 (±14.1) 35.9 (±13.3)
	Wight (kg)	78.8 (±9.0)	62.5 (±12.5) 72.9 (±12.6)
	Cycling experience (yrs)	30.9 (±15.9)	26 (±15.8)	29.1 (±15.3)
	Cycling frequency (trips/week)	4.9 (±2.3)	3.1 (±2.2)	4.2 (±2.3)
	Cycling distance (km/week)	43.9 (±30.5) 34.4 (±25.5) 40.5 (±27.9)
	Cycling on snowy/icy surface	10 (71%)	7 (87%)	17 (77%)
	Usage of winter tires	7 (50%)	3 (37.5%)	10 (45.4%)
	familiarity with the experiment route	8 (57%)	6 (75%)	14 (64%)
	foot slippery when stopping	3 (21%)	3 (37.5%)	6 (27%)
	feeling less safe when cycling in cold weather	7 (50%)	2 (25%)	9 (41%)
	the comfort of eye-tracker (positive)	8 (57%)	3 (37.5%)	11 (50%)
	increasing effort because of the wind	5 (35.7%)	1 (12.5%)	6 (27.3%)

VOLUME 4, 2016 This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2023.3242583 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/

This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/

VOLUME 4, 2016 This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2023.3242583 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS

This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS

VOLUME 4, 2016 This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2023.3242583 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/

VOLUME 4, 2016 This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2023.3242583 This work is licensed under a Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/

VOLUME 4, 2016 This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2023.3242583 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS

books, over 80 technical papers, and several industrial technical reports.ENNIA MARIAPAOLA ACERRA Civil engineer specializing in road infrastructure and transport, from 2020 PhD in automotive for intelligent mobility at the University of Bologna. Author of 6 articles of magazines and conferences indexed on scopus and teaching tutor for the course 'Roads, Railways and Airports Design' and for the secondlevel international master 'Sustainable and integrated mobility in urban regions'. The research topics include: study of the road-vehicle-driver interaction for connected and autonomous mobility. In particular: road safety; the study and analysis of the critical points of the road infrastructure (pedestrian crossings); the interactions between drivers and weak road users; the analysis of the visual behavior of man, in the different roles he holds in the road environment.VOLUME 4, 2016

VOLUME 4, 2016 This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2023.3242583 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/

V. ACKNOWLEDGEMENTS

The authors gratefully acknowledge the contributions of the Transportation Infrastructures section of the Department of Civil, Chemical, Environmental and Materials Engineering (DICAM) at the University of Bologna for designing and casting the asphalt specimen used to simulate road surface; and SimTeam represented by Stephane Caro for installing the actuators and the assistance during the preparation of the experiment.

This work is funded by Marie Skłodowska-Curie actions (H2020 MGA MSCA-ITN) within the SAFERUP project under grant agreement number 765057.

APPENDIX A ACCIDENT RISKS

The evaluation of risks related to the interaction between cyclists and road infrastructure.