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• Cognitive psychology principles are used to explain task switching during driving. • Cognitive overload and underload impair subsequent driving performance. • Attentional switch costs following a takeover response can persist for 5 min. • Suggestions are given for improving the safety of Level 3 automated driving. As the semi-automation of motor vehicles advances, the prevalence of multitasking and task switching while driving has increased. In the next phase, known as conditional automated driving (level 3 automation), drivers will be able to fully engage in distracting tasks, yet they must be prepared to promptly resume control of the vehicle and maintain safe driving if requested to by the vehicle. In such situations, the driver's ability to flawlessly switch between the distracting task and the driving task becomes vitally important. This narrative review discusses conditional automated driving within the framework of cognitive psychology concepts of attention and task switching. Delayed reaction time and deteriorated driving performance are attributed to cognitive overload and switch cost. Factors that contribute to driving switch cost are identified and categorized, and several road safety concerns are raised, including: i) switch cost may last for between 20 s to 5 min; ii) inexperienced drivers may be unable to adequately control the vehicle after resuming manual control; and iii) low- and high-intensity non-driving tasks have a greater impact on takeover performance. To minimise the risk to road safety, suggestions have been provided to vehicle manufacturers, road users and regulatory authorities. [ABSTRACT FROM AUTHOR]

• Automated vehicles require inclusive analysis of justice and safety disparities. • We analyse the acceptance of CAV deployment for drivers and pedestrians. • Individual differences shape CAVs' acceptability to adopt advanced automotive technologies. • Participants support CAVs but emphasise potential harm to vulnerable road users. • Economic barriers: Cost and benefits significant for CAVs' acceptance. As technological development towards connected and automated vehicles (CAVs) continues to rise, addressing the challenges associated with their integration is crucial, especially regarding public acceptance. This study explores the acceptability of CAVs, focusing on their potential role in enhancing safety and justice within the transport system. Semi-structured interviews were conducted with a diverse participant group, including 18 car drivers (aged 20–79, M = 48.3, SD = 18.77) and 12 pedestrians (aged 18–61, M = 36.0, SD = 12.94). Thematic analysis was employed to identify and contextualise factors influencing CAV acceptability, encompassing usefulness, ease of use, effectiveness, affordability, and social acceptability. Results emphasised safety as a top priority for both drivers and pedestrians. Trust and system reliability were also common concerns, varying with participants' roles and transport experiences. Both drivers and pedestrians identified cost and economic benefits as significant barriers to CAV acceptance. Moreover, shared apprehensions about justice in adopting CAVs acknowledged the imperfections inherent in technological advancements. Participants supported CAVs but raised concerns about potential harm to vulnerable road users. Both car drivers and pedestrians expressed concerns that introducing CAVs could exacerbate existing injustices these road users face. This study offers valuable insights into how individual differences influence CAV acceptability, contributing to understanding their preparedness to adopt advanced automotive technologies. [ABSTRACT FROM AUTHOR]

• Cooperative behaviors among road users, such as predicting and compensating for another road user's mistakes, were investigated. • A 12-day traffic observation with stationary mounted cameras was conducted at an urban T-intersection in Germany, where cars with priority appearing from the right encountered cars or bikes without priority coming from the left. • Cyclists were found to disregard the "priority-to-the-right" rule more often than motorists. • Road users with priority are more likely to yield when turning right and arriving at the intersection later. • Road users who disregard the "priority-to-the-right" rule are more likely to stay near the center of the road, while those who yield tend to move closer to the roadside. The integration of autonomous driving into mixed traffic environments poses unique challenges, especially at unsignalized intersections where communication and cooperation with human road users is necessary. This study addresses a critical research gap by investigating the adherence to the "priority-to-the-right" rule at an urban unsignalized intersection, comparing behavioral patterns of cyclists and motorists. Utilizing stationary mounted cameras, a 12-day traffic observation of an urban T-intersection in Braunschweig, Germany, was conducted. The class and the trajectory of road users as well as their scenarios were identified. In 202 cases, cars appearing from the right (ego, with priority) encountered cars or bikes coming from the left (foe, without priority). The study analyzed the impact of variables, ego's direction, foe's class and lateral position and their arrival time on their passing order through descriptive statistics and logistic regression. The findings reveal that cyclists disregard the "priority-to-the-right" rule more often than motorists. Additionally, road users who have the priority are more likely to yield when turning right, arriving at the intersection later, and encountering an opposing road user who is close to the center of the road. This study highlights the importance of implicit communication in traffic and provides essential benchmarks for developing more human-like autonomous driving systems, capable of interpreting and responding to nuanced road user interactions at unsignalized intersections. [ABSTRACT FROM AUTHOR]

• Three- stage least squares (3SLS) estimation was employed to model the data. • Significant associations between VRU's perceived safety and road user characteristics. • Significant associations between VRU's perceived safety and the presence of an eHMI. • No significant associations between VRU's perceived safety and road environment. • eHMIs are achieving their goal of successfully communicating to vulnerable road users. Research has demonstrated the benefits of external human–machine interfaces (eHMIs) in increasing vulnerable road users' (VRU) feeling of safety in interactions with automated vehicles (AVs). However, two key gaps exist in the literature. First, existing studies examined AV-VRU communication aspects in the context of conventional roads with traffic controls, but not for shared spaces where VRU-AV interaction is reliant on communication between the two parties. Second, limited knowledge is available on the differences between cyclists and pedestrians when interacting with AV. This paper aims to address these gaps through an online questionnaire among 254 cyclists and pedestrians in Australia and the UK. Perceived safety was measured in terms of willingness to cross in front of an AV, feeling of security, and feeling of relaxation. Results from a three-stage least square regression analysis identified differences in the factors for pedestrians and cyclists. Pedestrians that were male, over the age of 35, not regular cyclists, or residents of the UK reported lower feelings of safety, relaxation, and willingness to cross than their counterparts. Similar results were found cyclists who are older than 45 years, and UK residents compared to other cyclist participants. Both pedestrians and cyclists reported more willingness to cross and higher feelings of security and relaxation when an eHMI was present. These findings indicate that for effective use and understanding of eHMIs targeted interventions are needed to address the specific concerns of different demographic groups, as identified in this research. By increasing public understanding and acceptance of AVs – as well as eHMIs – across all demographic groups, researchers can promote a smooth integration of these technologies into shared spaces. [ABSTRACT FROM AUTHOR]

• AVs can be a suitable mobility option for unaccompanied child transportation for a majority of parents in our study. • Parents wanted to train their children and gain first-hand experience with the autoELF vehicle before allowing them to use the autoELF vehicle unaccompanied. • Parents would like to replace most of the previously accompanied car journeys to the children's leisure activities with the autoELF vehicle. • Only two parents cited school commuting as a use case for the autoELF vehicle and AVs in general. • Parents cited self-responsibility and the ability to regulate emotions as the two most important skills for children to be able to use the autoELF vehicle unaccompanied. Driverless or autonomous vehicles (AVs) have the potential to address children's mobility disadvantage by enabling them to become more independent from their parents and other adult drivers before they reach the legal age for obtaining a driver's license. In an online contextual interview study, we interviewed N =22 parents of underage children from Germany to investigate their willingness to use AVs for unaccompanied transportation of their children. The goal of the interview study was to investigate whether AVs are a suitable option to support unaccompanied transportation of children from the parents' perspective and how these AVs should be designed considering the parents' concerns and needs. In contrast to former acceptance studies, we familiarized the participants with an existing AV concept called autoELF. We created a user scenario to enable the parents to better imagine the situation. In the study, parents first described their children's current mobility in a normal week. Parents were then asked about the expected benefits, concerns, child-related prerequisites and technical requirements for using AVs, as well as the possibilities for integrating AVs into their family's mobility. Results showed that AVs can be a solution to provide children with unaccompanied transportation. In contrast to previous studies, the majority of parents interviewed in this study were willing to use the AV for the transportation of unaccompanied children, but only after parents had gained initial experience with the vehicle and trained their children in its use. Regarding the unaccompanied use by their children, parents based their consent to use the AV on their children's emotional and cognitive abilities rather than on their age. In their children's daily mobility, parents intended to replace most of the previously accompanied car journeys during leisure time with the autoELF vehicle without compromising their children's active mobility, such as walking or bicycling. In contrast to previous literature, only a few parents cited school commuting as a use case for the autoELF vehicle. Our qualitative interview study highlights the potential of AVs for unaccompanied child transportation. Moreover, it stresses the importance to use specific, tangible concept when investigating family AVs. In the next phase of the research project, a physical prototype of the autoELF vehicle was tested with children and older adults as the primary user groups. [ABSTRACT FROM AUTHOR]

• Link drivers and pedestrians in real-time distributed simulation. • Present driver's bimodal braking strategies. • Identify lateral movements as implicit cues in road user interactions. • Showcase pedestrians' behavioural adaptations to kinematic cues. • Highlight decisions of both actors shaped by time gaps and road infrastructure. As we move towards a future with Automated Vehicles (AVs) incorporated in the current traffic system, it is crucial to understand driver-pedestrian interaction, in order to enhance AV design and optimization. Previous research in this area, which has primarily used naturalistic observations or single-actor virtual reality simulations, has been limited by its inability to draw causal conclusions, also due to a lack of real human–human interactions. Our study addresses these limitations by employing a high-fidelity distributed simulation setup that links drivers in a motion-based simulator with pedestrians in a CAVE-based environment. This method allows for the examination of real-time and reciprocal interactions across a range of road-crossing scenarios. Using thirty-two pairs of drivers and pedestrians, we investigated how different factors, such as the presence of zebra crossings and varying time gaps of the approaching vehicle, influence driver behaviour and pedestrian crossing decisions. The effect of drivers' control of the vehicle during such crossings (e.g., braking behaviour and lateral deviation) on pedestrians' crossing decisions were also analysed. We found that the distribution of drivers' average deceleration values were bimodal, where drivers either markedly yielded to pedestrians, or continued in their path, with very few instances of intermediate behaviour. We also found that pedestrian decisions were seemingly influenced by the different braking strategies adopted by the driver, with pedestrians crossing before the vehicles in response to soft and early, or late and hard braking, while late and soft braking often resulted in the vehicle passing first. We also observed a slight lateral movement of the vehicle away from pedestrians when drivers were not yielding, but more of a lateral deviation towards them when yielding. This may be because drivers subconsciously transfer their walking interaction habits to their driving behaviour, to avoid a collision with pedestrians. Finally, our results showed a stronger influence of these kinematic cues on pedestrian crossing decisions, when compared to zebra crossings. As well as highlighting the value of a novel approach for investigating vehicle–pedestrian interactions, this study illustrates how vehicle cues can assist pedestrian decisions, adding new knowledge in the development of human-like behaviour for future AVs. [ABSTRACT FROM AUTHOR]

• We conducted a systematic review on the topic of road traffic suicides. • 51 studies were identified and their content summarized in 12 topic areas. • We concluded that road traffic suicides are not a well-researched phenomenon. • The prevalence and consequences of this method, together with who uses it and why, deserve more research attention. • More efforts are needed to develop potential preventive measures for this suicide method. Suicide on the road network is a recognized suicide method. We conducted a systematic review with the main aim of summarizing the existing research literature on road traffic suicides covering all road users who attempt or die by suicide in road traffic. A secondary and more specific aim was to examine the consequences for possible secondary participants. Our ultimate aim was to identify prevention measures. Relevant publications (N = 48) were identified in Medline , PsycInfo , Scopus , and Web of Science databases and supplemented with three studies from a personal database. We covered and discussed the following twelve topics: Countries where the data has been collected; Publication years – a historical overview; The main purpose of the studies; Data sources; How suicide was confirmed/defined (Differences between decisions by crash investigators and those of official forensic examinations); The proportion of suicides on roads; Types of crashes; The second party; Who dies by suicide in road traffic? (Age and gender, Mental health history, and Other background factors); Why people choose this method of suicide; The prevention of road suicides; An overview of issues regarding quality of studies. We conclude that road traffic suicides are not a well-researched phenomenon, especially concerning the reasons why people choose this specific method, the consequences for the possible second party, and specific preventive measures. [ABSTRACT FROM AUTHOR]

• Motorists preferred when the traditional division between protected and unprotected road users was recreated. • Vehicles' mean maximum speed decreased when the traditional division was recreated within the shared space. • Distribution of vehicles decreased when the traditional division was recreated within the shared space. • Vehicles' mean maximum speed decreased with high pedestrian density. Shared spaces are intended to constitute an attractive urban space for everyone by blending protected and unprotected road users. However, our previous study showed that pedestrians prefer the traditional division between protected and unprotected road users, at the same time as elderly pedestrians focused less on traffic when the division was recreated by large flowerpots. This follow-up study aimed to examine the effects of external factors, such as alternative design and pedestrian density, on motorists' subjective experiences, and the speed and placement of their vehicles within a shared space. To investigate this, Q-methodology was used to examine 32 motorists' subjective experiences, and video recordings were analysed to measure the speed and placement of 150 vehicles on Fisherman's Square in Västervik, Sweden, both without (75 vehicles) and with (75 vehicles) large flowerpots deployed. The motorists preferred when the large flowerpots were deployed to recreate the traditional division. The results also showed that both the large flowerpots and high pedestrian density decreased vehicles' mean maximum speed. The deployment of large flowerpots also decreased the distribution of vehicles over the square. Recreating some type of division between protected and unprotected road users appears to be preferred. Further studies are required to ascertain whether this solution works for all road user groups, including cyclists and e-scooter riders. [ABSTRACT FROM AUTHOR]

• Contrasting colours were used to enhance e-scooter rider visibility for drivers. • Detection time was lower with contrasting colours on both the e-scooter and rider. • Conspicuity ratings were higher for e-scooters with contrasting aids than grey clothes. • Contrasting visibility aids can reduce accidents from poor e-scooter visibility. This study explores how different visibility aids of contrasting colours could enhance the e-scooter riders' conspicuity under daylight conditions. With the rise in popularity of shared e-scooter services, an increase in incidents involving e-scooter riders and motorized counterparts was noticed. 48 licensed drivers (mean age = 24.6 years) detected the e-scooter riders in the videos and images featuring a simulated urban road environment in daylight, while performing a secondary task (n-back). The time to detect standing and moving e-scooter riders and subjective conspicuity ratings were assessed in three visibility aid conditions: Control (grey clothes and grey backpack), Patterned Jacket (jacket and backpack with checkerboard black and yellow pattern) and Wheels-Backpack (yellow stripes on the e-scooter wheels and on a dark backpack). Improved detectability was observed for e-scooter riders in the Wheels-Backpack condition, resulting in a minimum 168 ms increase in detection time compared to other two conditions. In terms of conspicuity ratings, participants gave higher scores to riders wearing Wheels-Backpack and Patterned Jacket (6.02 and 6.31, respectively, on a Likert 10-point scale), with no significant difference between them. Detection from videos or images showed similar effects. For all of these analyses, Bonferroni post-hoc tests followed a Repeated-measures ANOVA. Distributing contrasting colours across the e-scooter and the rider enhanced their daylight conspicuity better than when contrasting colours were located on the riders' upper body. However, drivers did not realise that these two visibility aids were not equal in terms of conspicuity benefits. [ABSTRACT FROM AUTHOR]

• A cycling simulator was used to recreate the cyclists' interaction scenarios with motorized vehicles. • The effect of the difference in time to arrival at the intersection and visibility distance was observed on the interaction. • Cyclists' behavioral patterns were investigated in response to independent variables. • Eye contact and communication with the driver plays an important role in cyclists decision-making. Introduction: With cycling gaining more popularity in urban areas, it is vital to obtain accurate knowledge of cyclists' behavior to develop behavioral models that can predict the cyclist's intent. Most conflicts between cyclists and vehicles happen at crossings where the road users share the path, especially at unsignalized intersections. However, few studies have investigated and modeled the interaction between cyclists and vehicles at unsignalized intersections. Method: A bike simulator experiment was conducted to scrutinize cyclists' response process as they interacted with a passenger car at an unsignalized intersection. An existing unsignalized intersection in Gothenburg was simulated for test participants. Two independent variables were varied across trials: the difference in time to arrival at the intersection (DTA) and intersection visibility (IV). Subjective and quantitative data were analyzed to model the cyclists' behavior. Results: When approaching the intersection, cyclists showed a clear sequence of actions (pedaling, braking, and head turning). The distance from the intersection at which cyclists started braking was significantly affected by the two independent variables. It was also found that DTA, looking duration, and pedaling behavior significantly affected cyclists' decisions to yield. Finally, the questionnaire outputs show that participants missed eye contact or communication with the motorized vehicle. Conclusions: The kinematic interaction between cyclists and vehicles, along with the cyclist's response process (visual and kinematic), can be utilized to predict cyclists' yielding decision at intersections. From the infrastructural perspective, enhancing visibility at intersections has the potential to reduce the severity of interactions between cyclists and vehicles. The analysis of the questionnaire emphasizes the significance of visual communication between cyclists and drivers to support the cyclist's decision-making process when yielding. Practical applications: The models can be used in threat assessment algorithms so that active safety systems and automated vehicles can react safely to the presence of cyclists in conflict scenarios. [ABSTRACT FROM AUTHOR]

• Daily diary method (DDM) was used to explore how state mindfulness affects daily mobile phone usage while walking (MPUWW). • State mindfulness negatively predicts daily MPUWW via phone dependence at the within-person level. • Risk perception (at the between-person level) weakens the relationship between phone dependence and MPUWW. Introduction : Pedestrians are a particularly vulnerable group of road users. Mobile phone usage while walking (MPUWW) is a significant contributor to pedestrians' involvement in road crashes and associated injuries. The current study aims to explore the effect of state mindfulness on daily MPUWW via phone dependence (at the within-person level), and the moderating role of risk perception (at the between-person level) in the phone dependence-MPUWW relationship. Method : We utilized a fine-grained method, the daily diary methodology (DDM) to explore the aforementioned model. A total of 88 Chinese college students participated in a consecutive 12-day study, yielding 632 daily data. Unconflated multilevel modeling was used to analyze the data. Results : After trait mindfulness being controlled, state mindfulness has a negative impact on MPUWW via phone dependence at the daily level. Furthermore, risk perception as an individual difference variable moderates the relationship between phone dependence and MPUWW, in which a weaker effect observed in individuals with higher levels of risk perception. Conclusions : State mindfulness can decrease the frequency of daily MPUWW by reducing phone dependence, and risk perception is a crucial factor in mitigating the negative effects of phone dependence on MPUWW. Practical applications : To lower MPUWW and thereby minimize the risk of road crashes and associated injuries, it is beneficial to foster present-moment awareness of individuals, encourage individuals to use mobile phones in a balanced and sensible manner, and integrate the enhancement of risk perception into road safety education. [ABSTRACT FROM AUTHOR]

• This study shows the actual features of the risky behaviour of pedestrians when crossing the road and walking on the street. • The formation of social responsibility of citizens during walking will contribute to the elimination of the human factor among the causes of traffic accidents. • Nowadays, the complexity of the interaction of intensive traffic and pedestrian flows requires proactive safety-based management of these flows. As vulnerable road users, pedestrians are the object of research in various areas of road safety. One of the ways to reduce the level of risky behaviour of pedestrians is to increase their social responsibility by applying the "traditional" 3 E: engineering, education, and enforcement. Social responsibility involves a focus on responsibility for both actions related to personal safety and actions that benefit society. This paper deals with the results of a survey of pedestrians regarding their risky behaviour while walking, namely, violation of crossing rules and distraction by using a smartphone or listening to music through headphones. It was found that risky behaviour depends on the age of pedestrians, and listening to music through headphones also depends on the person's gender. It was established that respondents' assessment of the safety of transport modes does not correlate with data on mortality in road traffic accidents using different types of transport. It is proposed that social responsibility of pedestrians can be increased by analyzing the causes and events that lead to traffic accidents during the study of safety disciplines in higher education institutions. [ABSTRACT FROM AUTHOR]

• A Pedestrian Behaviour Questionnaire (PBQ) validated for Jordanian population, spanning all ages. • Jordanian pedestrians do not distinguish between violations and errors. • Positive behaviour scale had acceptable internal reliability (α > 0.7) in Jordanian PBQ. • Males and young people tend to commit higher rates of risky behaviours while walking. • Lack of alternatives to walking was positively associated with unsafe behaviours. A variety of self-reported questionnaires have been developed worldwide across to classify pedestrians' behaviours. However, to the best of our knowledge, no pedestrian behaviour questionnaire has been validated to investigate Jordanian pedestrians' behaviour. Thus, this study aimed to develop and validate a self-reporting pedestrian behaviour questionnaire for the Jordanian population (JPBQ), spanning all ages. Our JPBQ consisted of 40 items describing pedestrian behaviour, whilst the validation study itself included 400 participants (45.25% females). Principal component analysis (PCA) revealed a four-factor structure: transgressions, lapses, positive behaviours, and aggressive behaviours for both Long (31-item) and short (20-item) versions of the JPBQ, confirming validity (significant association with p < 0.05) and reliability (Cronbach's alpha > 0.7) for each factor. This addressed the reliability issue with positive behaviour factor found in previous self-reported questionnaires by incorporating effective questions concerning positive behaviours while walking. Across the four factors, the highest mean scores that pedestrians reported were for positive behaviours, while the least commonly reported behaviours were aggressive behaviours and lapses. Male participants were found to declare higher rates of violations and aggressions, while young participants reported more violations and fewer lapses. The lack of alternatives to walking was positively associated with unsafe behaviours (violations, errors, lapses). Income level was negatively associated with aggressive behaviours towards other road users. Divorced individuals were found to self-report lower rates of lapses and positive behaviours. Overall, this study contributes to understanding pedestrian behaviours in Jordan, providing a reliable validated questionnaire for research and road safety initiatives. [ABSTRACT FROM AUTHOR]

• Assess the properties of the Pedestrian Receptivity Questionnaire for FAVs (PRQF) on a French sample. • The results showed different dimensions than those found in other validation studies. • The results showed mixed receptivity to FAVs among French respondents. • Receptivity to FAVs and self-declared pedestrian behaviors explain behavioral intention and acceptance of FAVs. • Age, familiarity with FAVs, and with new technologies also explain acceptance of FAVs. One of the biggest challenges facing the human-centered design of fully automated vehicles (FAVs) is their interaction with vulnerable road users. Measuring pedestrians' perceptions is particularly important to know whether they will be receptive to the introduction of FAVs on the road. In this context, the present study aimed to examine and validate the structure of the Pedestrian Receptivity Questionnaire for FAVs (PRQF) in France. A second objective was to explore the receptivity of French pedestrians towards FAVs, its effects on behavioral intention when interacting with FAVs, and acceptance of FAVs. To meet these objectives, 474 participants living in France answered an online survey (age range: 18–83 years; 39 % of males), which included the PRQF, the behavioral intention to cross the road in front of a FAV and their acceptance, as pedestrians, of the introduction of FAVs on the road. Several scales and items were also included to measure familiarity with FAVs and new technologies, as well as self-reported pedestrian behavior using the pedestrian behavior scale (PBS) and sociodemographic information. A series of statistical analyses indicated a three-dimensional factor structure in the answers of the French respondents to the PRQF, i.e., Positive Attitude, Supportive Social Norms, and Compatibility. These dimensions differed from those revealed in earlier questionnaire validation studies. However, in line with other studies on automated vehicle acceptance, these dimensions were influenced by several sociodemographic factors (age, sex, level of education, walking frequency, location, possession and duration of driving license). The results also indicated a mixed receptivity of the French respondents to FAVs. Their behavioral intentions to cross the road in front of an approaching FAV were further explained by the Positive Attitude dimension of the PRQF and their self-declared behaviors as pedestrians, particularly in terms of positive and violation behaviors. Acceptance of FAVs in the respondents' living area was predicted by the Positive Attitude dimension and by self-declared behaviors as pedestrians (in terms of aggressive behaviors particularly). The respondents' age and familiarity with FAVs and new technologies were also predictive of their FAV acceptance. Several research and practical perspectives are proposed accordingly. [ABSTRACT FROM AUTHOR]

• Study examined how safety alerts should be communicated to cyclists. • Following a field trial with 38 cyclists, a technology acceptance survey was conducted. • Alerts for high crash-risk locations and nature of risk were preferred in auditory, visual, and haptic modalities. • Alerts should reflect real-time traffic conditions and unpredictable movements of other road users. • App should run in background and communicate with other cycling and navigational apps. Bicycle-mounted crash avoidance technologies have been developed to improve cyclist safety. However, their effectiveness in alerting cyclists of potential dangers and the preferences of cyclists regarding the types and mechanisms of receiving alerts have not been examined extensively in field trials. To address this gap, this paper aims to understand how safety alerts are best communicated to cyclists. This aim was achieved by undertaking a field trial of a smartphone app, which was the user interface of an innovative Intersection Safety Alert System (ISAS). A total of 38 participants rode bicycles equipped with the ISAS in a 2-day field trial in downtown Melbourne, Australia, and then completed a technology acceptance survey. The survey data were analysed using statistical and thematic analysis methods to derive insights on how cycling safety technologies should be designed to ensure a good level of user acceptance. Results showed that cyclists would be willing to use or recommend a safety app that is free from privacy or security concerns, be able to provide alerts that can effectively notify about dangerous situations, and be effective in improving the safety for the whole cycling community. Cyclists preferred to receive simple and clear safety alerts that provided information on high-risk locations and the nature of dangers through an easy-to-use user interface that runs in the background and communicates with other cycling and navigational apps. They wanted the alerts to convey real-time and non-obvious traffic conditions and unpredictable movements of other road users. Preferences and comments regarding auditory, visual and haptic modalities of presenting alerts differed among riders. [ABSTRACT FROM AUTHOR]

User acceptance is essential for successfully introducing automated vehicles (AVs). Understanding the technology is necessary to overcome skepticism and achieve acceptance. This could be achieved by visualizing (uncertainties of) AV's internal processes, including situation perception, prediction, and trajectory planning. At the same time, relevant scenarios for communicating the functionalities are unclear. Therefore, we developed EduLicit to concurrently elicit relevant scenarios and evaluate the effects of visualizing AV's internal processes. A website capable of showing annotated videos enabled this methodology. With it, we replicated the results of a previous online study (N=76) using pre-recorded real-world videos. Additionally, in a second online study (N=22), participants uploaded scenarios they deemed challenging for AVs using our website. Most scenarios included large intersections and/or multiple vulnerable road users. Our work helps assess scenarios perceived as challenging for AVs by the public and, simultaneously, can help educate the public about visualizations of the functionalities of current AVs. • EduLicit –a method to elicit user-chosen driving scenarios and educate on automated vehicle functionalities and challenges. • Applying neural networks to scenario videos to visualize vehicles' detection, prediction, and trajectory planning functionalities. • Website implementation of EduLicit , where users upload in-the-wild driving videos for automated visualization and education. • User-chosen driving scenarios primarily include large intersections and/or multiple vulnerable road users. • Users perceive vulnerable road users as more unreliable, unpredictable, and harder to detect by sensors than vehicles. [ABSTRACT FROM AUTHOR]

• Drivers' willingness to stop is influenced by distractions. • Distractors on the part of drivers strongly decrease the willingness to yield. • Distractions on both sides results in the lowest willingness to yield priority. • Drivers' behavior is influenced by the characteristics of pedestrians. • The factors were examined using a discrete choice model. The safety of vulnerable road users is one of the most important aspects of road safety. One of the most critical points for pedestrian traffic is the pedestrian crossing, where pedestrians and vehicles interact. Due to the speed and weight of vehicles, sufficient attention by drivers and pedestrians is essential for accident-free crossing. Our research aimed to identify the parameters that influence drivers' willingness to yield the right of way. The focus of our research was on the distractors of pedestrians and drivers. Our study involved on-site investigations. The measurements were taken at designated pedestrian crossings, with a road sign and road markings. During the measurements, we recorded all situations where there was a pedestrian-vehicle interaction. We recorded several parameters about drivers and pedestrians. The data were analyzed using both descriptive statistics and a discrete decision model. We have shown that the drivers' willingness to stop depends on distractions. We showed that distractors on the part of pedestrians slightly increase the drivers' willingness to stop, while distractors on the part of drivers strongly decrease the willingness to yield. In addition, we have shown that distractions from both sides result in the lowest willingness to yield the right of way. We have also shown that driver behavior depends on the gender, age, and behavior of pedestrians. Our results are valuable and useful in many ways in the field of road safety and the analysis of traffic behavior. [ABSTRACT FROM AUTHOR]

• Attitudes of different VRU Groups towards AVs in urban traffic were studied. • Interaction with AVs and AVs in mixed traffic with CVs was explored. • Some VRUs are concerned that mixed traffic could lead to more aggression from human drivers and make traffic participation more complex. • VRUs share similar evaluations, intentions, and AV requirements in urban traffic. • VRUs want AV identification, explicit communication, and strict traffic rules. In today's urban traffic, vulnerable road users (VRUs) have a somewhat ambivalent relationship with human drivers. The introduction of automated vehicles (AVs) that are no longer controlled by such human drivers could impact this relationship, both in positive and negative ways. Five focus groups (pedestrians, cyclists, e-scooter riders, individuals with walking disabilities, and older adults) were conducted to investigate how different VRUs evaluate the participation of AVs in urban traffic and whether they hold specific requirements or concerns. The discussions focused on exploring potential interactions with AVs and the effects of mixed traffic scenarios (encompassing AVs and conventional vehicles (CVs)) on the well-being of VRUs in urban traffic. The results revealed that the concerns and expectations about AVs in urban traffic were quite similar among the various VRU groups. Regarding their interaction with AVs, participants expressed advantages (e.g., eliminating human errors) and disadvantages (e.g., lack of communication possibilities). In the context of mixed traffic, especially cyclists and individuals with walking disabilities feared aggressive behavior from CVs taking advantage of rule-abiding AVs. They also saw the risk of increasing complexity in mixed urban traffic, as AVs are likely to behave differently from CVs. In addition to the increased caution described by most VRUs, a few participants could imagine taking advantage of the defensive driving style of AVs. The cyclist group discussed the possibility of sabotaging AVs to make a general statement against cars in urban traffic. Furthermore, essential requirements were gathered for vehicle manufacturers (e.g., external Human-Machine Interfaces) and policies (e.g., stringent regulation enforcement for car traffic in the city) that could enable successful coexistence between VRUs and AVs in urban traffic. [ABSTRACT FROM AUTHOR]

• Distractions caused by fellow drivers (DFDs) have received little attention. • Associations between DFDs and other latent factors were evaluated using SEM. • DFDs are positively associated with stress among recipient drivers. • Stress is positively associated with anxiety-based performance deficits. • DFDs and stress are positively associated with crash propensity. Introduction: Aggressive behavior of drivers is a source of crashes and high injury severity. Aggressive drivers are part of the driving environment, however, excessive aggressive driving by fellow drivers may take the attention of the recipient drivers away from the road resulting in distracted driving. Such external distractions caused by the aggressive and discourteous behavior of other road users have received limited attention. These distractions caused by fellow drivers (DFDs) may agitate recipient drivers and ultimately increase crash propensity. Aggressive driving behaviors are quite common in South Asia and, thus, it is necessary to determine their contribution to distractions and crash propensity. Method: Our study aimed to evaluate the effects of DFDs using primary data collected through a survey conducted in Lahore, Pakistan. A total of 801 complete responses were obtained. Various hypotheses were defined to explore the associations between the latent factors such as DFDs, anxiety/stress (AS), anxiety-based performance deficits (APD), hostile behavior (HB), acceptability of vehicle-related distractions (AVRD), and crash propensity (CP). Structural Equation Modeling (SEM) was employed as a multivariate statistical technique to test these hypotheses. Results: The results supported the hypothesis that DFDs lead to AS among recipient drivers. DFDs and AS were further found to have positive associations with APDs. Whereas, there was a significant negative association between DFD, AS, and AVRD. As hypothesized, DFD and AS had positive associations with CP, indicating that distractions caused by aggressive behaviors leads to stress and consequently enhances crash propensity. Practical applications: The results of this study provide a statistically sound foundation for further exploration of the distractions caused by the aggressive behaviors of fellow drivers. Further, the results of this study can be utilized by the relevant authorities to alter aggressive driving behaviors and reduce DFDs. [ABSTRACT FROM AUTHOR]

• What is already known on this topic: During the early pandemic phase, some cities experienced a drop in nonfatal road traffic collisions but a surge in fatalities, potentially linked to increased speeding in lighter traffic with reduced law enforcement. • What this study adds : Over an extended period beyond the first year of the COVID-19 pandemic, the findings show a decrease in pedestrian injuries since April 2020, and an increase in non-MVC bicyclist injuries leading to more ED visits and hospitalizations. • How this study might affect research, practice or policy : Non-MVC bicyclist injuries increased, raising important questions for further investigation. Background : The COVID-19 pandemic altered traffic patterns worldwide, potentially impacting pedestrian and bicyclists safety in urban areas. In Toronto, Canada, work from home policies, bicycle network expansion, and quiet streets were implemented to support walking and cycling. We examined pedestrian and bicyclist injury trends from 2012 to 2022, utilizing police-reported killed or severely injured (KSI), emergency department (ED) visits and hospitalization data. Methods: We used an interrupted time series design, with injury counts aggregated quarterly. We fit a negative binomial regression using a Bayesian modeling approach to data prior to the pandemic that included a secular time trend, quarterly seasonal indicator variables, and autoregressive terms. The differences between observed and expected injury counts based on pre-pandemic trends with 95% credible intervals (CIs) were computed. Results: There were 38% fewer pedestrian KSI (95%CI: 19%, 52%), 35% fewer ED visits (95%CI: 28%, 42%), and 19% fewer hospitalizations (95%CI: 2%, 32%) since the beginning of the COVID-19 pandemic. A reduction of 35% (95%CI: 7%, 54%) in KSI bicyclist injuries was observed, but However, ED visits and hospitalizations from bicycle-motor vehicle collisions were compatible with pre-pandemic trends. In contrast, for bicycle injuries not involving motor vehicles, large increases were observed for both ED visits, 73% (95% CI: 49%, 103%) and for hospitalization 108% (95% CI: 38%, 208%). Conclusion: New road safety interventions during the pandemic may have improved road safety for vulnerable road users with respect to collisions with motor vehicles; however, further investigation into the risk factors for bicycle injuries not involving motor vehicles is required. [ABSTRACT FROM AUTHOR]

• Social categorization among e-scooter riders and cyclists was studied. • Higher dispositional attribution ratings for ingroups than outgroups emerged. • Fine severity was higher for the ingroup than the outgroup. • Situational attribution ratings were higher for e-scooter riders than cyclists. • Results imply considerate coexistence among cyclists and e-scooter riders. Problem: In many countries, a new road user group, e-scooter riders, share the existing cycling infrastructure. The study aimed to investigate if an individual's status as a cyclist or e-scooter rider affects their social identity and whether it results in ingroup favoritism or outgroup discrimination. Method: An online experiment involving 179 cyclists and 64 e–scooter riders was conducted, where they rated the behavior of ingroup or outgroup members in six traffic scenarios. Results: Participants rated dispositional attributions as more causally relevant than situational ones across all traffic scenarios. Cyclists and e–scooter riders were inclined to judge ingroup members' rule violations more harshly than those of outgroup members in terms of dispositional attribution ratings and punishment severity. For situational attributions, few indications of ingroup favoritism were observed for the e–scooter rider group. Summary: Findings suggest initial indications of considerate coexistence, from the perspective of social identity theory, between the two modes of transport, supporting current regulations on the use of cycling infrastructure by e–scooter riders. Indications of ingroup discrimination, however, suggest that safety campaigning may target to promote courtesy within the cyclist and e-scooter rider groups. [ABSTRACT FROM AUTHOR]

• A comprehensive review of existing literature on child pedestrian behavior and safety on roads. • Identification of parameters considered, data analysis techniques, and models used in the analysis of child pedestrian behavior and safety. • Discussion of the limited evidence available on child pedestrian behavior and safety in the Indian context and the need for further studies. Children are regarded as the most liable road users as pedestrians because of their specific traffic behaviours, which demand close investigation. The present study conducts a comprehensive systematic review aiming to draw attention to the need for a thorough understanding of child pedestrian safety, especially in the Indian context, and to provide insights that can guide the implementation of evidence-based initiatives to safeguard children on roads. Using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, the study searched Google Scholar, Semantic Scholar and Scopus for relevant literature. Finally, 78 research papers and 8 reports were examined and reviewed. The review analysed the literature on the basis of study locations, methods of data collection, parameters affecting child pedestrian behaviour and safety, and existing techniques and models for analysing child pedestrian behaviour and safety. Additionally, worldwide strategies adopted to improve child pedestrian safety were reviewed. The findings across the literature revealed a significant contribution of studies from China, with limited representation from India. Numerous studies have employed questionnaire surveys as a means of data collection and regression analysis to model the behaviour and safety of child pedestrians. The findings of the study sheds light onto the parameters influencing child pedestrian behaviour and safety, with special emphasis on socio-demographic characteristics, peer influence, adult supervision, distractions, disabilities, socio-economic factors, and human factors. The study establishes a foundation for targeted interventions that can reduce pedestrian risks and create a safe environment so that children can navigate independently. The study also discusses limitations and the scope for further research on child pedestrians' behaviour and safety on streets, especially in Indian context. [ABSTRACT FROM AUTHOR]

• The role of situational factors known to elicit anger in autonomous driving takeover was examined. • Motive consistency, control potential, and agency impact autonomous driving takeover. • Data clustering revealed four distinct driver profiles. • Anderson's scenario-based method is useful in studying autonomous driving takeover. • Roseman's theory of emotions applied to autonomous driving takeover. Motor vehicle accidents, in part due to human error, continue to cause significant fatalities, a situation that automated vehicles can address when users relinquish driving. However, when the human behind the wheel decides to take over the driving activity, human error is back in the loop. In the context of improving the safety of motorized transportation, this study examines the role of anger in the willingness to take over the driving activity of an automated vehicle classified as levels 4 to 5 according to the Society of Automotive Engineers (SAE). Our study indirectly induces anger by strategically manipulating factors such as motive consistency, agency caused by others, and control potential - factors that are well documented for their role in eliciting anger. Using a scenario-based approach where participants were instructed to catch an emergency train, we manipulated combinations of four factors selected for their association with anger (e.g., late departure × delayed train × reduced speed due to fog × road blocked by another vehicle). Participants (N = 313) were asked to rate their willingness to take over the driving activity as if they were the protagonist. The results showed that the willingness to take over the driving activity aboard a highly automated vehicle could be influenced by emotions, especially anger, elicited by the evaluation of the driving environment. Participants were more willing to take over driving when they judged the driving environment to be inconsistent with the goal of their trip. However, interaction analyses revealed that increasing motive consistency could moderate the negative influences of control potential and other-caused agency on willingness to take over driving. Cluster analysis revealed four distinct subgroups of drivers: High Takeover Willingness, Low Takeover Willingness, Influenced by Other Road Users, and Goal-Directed drivers, each of which showed a unique response to the driving scenarios. This study suggests that understanding the impact of emotions on the willingness to take over driving will help prevent this type of behavior and improve safety. [ABSTRACT FROM AUTHOR]

• Investigating cyclist discomfort in shared spaces. • Varied discomfort in passing and meeting events among demographics. • Cycling experience enhances comfort for older adults. • Younger adults with e-scooter experience have lower cycling comfort. Shared spaces for active mobility prioritize the safety and comfort of vulnerable road users by segregating them from motorized vehicles. However, the diverse speed regimes of pedestrians and cyclists can lead to encounters that may affect their comfort. In addition, the very perception of comfort may vary across individuals depending on their demographics, and therefore the determinants of comfort and their effects may not be fixed across all individuals. Despite these complexities, there is limited research in understanding the heterogeneous interactions between cyclists and other road users in shared spaces. To bridge this gap, we conducted an intercept survey complemented by an experimental section involving 594 cyclists in Sweden. This study focuses on gaining insights into cyclists' experiences, particularly their comfort levels during 'passing' and 'meeting' events with other road users in shared spaces. We then used the collected data to develop a random effect latent class ordered probit model to scrutinize the determinants of cycling comfort in passing and meeting scenarios. The latent class specification is employed to account for unobserved heterogeneity in the data. Findings reveal that female cyclists generally perceive less comfort compared to their male counterparts in both scenarios. Passing events have a more negative impact on older adults, leading to less comfort compared to younger cyclists. We also found that previous cycling experience increases comfort in shared facilities, particularly for older adults. These results highlight the intricate nature of perceived comfort in interactions, particularly concerning demographic characteristics, contributing to the promotion of user diversity in shared spaces. [ABSTRACT FROM AUTHOR]

• Investigation of pedestrians' road-crossing decisions and gaze patterns in response to scalable AVs with the same vs different eHMIs. • Comparison of 16 unique eHMI combinations across two AVs (originated from four eHMI manipulations for each AV). • Differences in eHMIs across AVs resulted in prolonged road-crossing decision times, diminished perceived clarity, and intensified visual attention. • Integration of pedestrian symbol-based eHMIs garnered superior clarity ratings, facilitated time savings, and reduced visual engagement. • This study highlights the significance of integrating interpretable, intuitive, and consistent eHMI design for future AVs. To enhance the efficiency and safety of interactions with pedestrians, numerous external Human-Machine Interfaces (eHMIs) concepts for automated vehicles (AVs) have been proposed and evaluated, predominately based on singular pedestrian-AV interaction scenarios. This leaves a gap in comprehending the efficiency and robustness of eHMIs during interactions with scalable AVs. To bridge the gap, this study pioneers an exploration of pedestrians' road-crossing decisions, perceived clarity, and gaze behaviour during synchronous interactions with multiple AVs equipped with different eHMIs. An eye-tracking experiment was conducted, involving 48 video stimuli depicting two AVs (with yielding patterns and eHMIs manipulated) approaching a predetermined road-crossing location from the same side of a two-way, four-lane, un-signalized road. Each yielding AV will present one of four eHMI manipulations (i.e., light band, smiling expression, pedestrian symbol, and no eHMI as baseline), resulting in 16 unique eHMI combinations and video stimuli. Eighty-seven participants were recruited and tasked to respond to approaching AVs, during which their road-crossing decision time, perceived clarity, and gaze metrics were recorded. Findings revealed that different eHMIs across AVs were associated with prolonged road-crossing decision times, diminished perceived clarity, and intensified visual attention as evidenced by increased fixation counts and durations. Regarding AVs equipped with the same eHMIs, the pedestrian symbol-based eHMIs resulted in heightened clarity perception, reduced crossing decision times and visual engagement, in contrast to eHMIs presented in abstract light bands or smiling expressions. Furthermore, for eHMI-different AVs, those featuring only one eHMI within AVL-AVR pairs were perceived as less clear, eliciting heightened visual cognitive load and decision times. Integration of a pedestrian symbol-based eHMI in AVL-AVR configurations garnered superior clarity ratings and facilitated time savings. These findings of this pioneering study provide insights for eHMI design for future AVs in complex traffic scenarios with scalable road users. [ABSTRACT FROM AUTHOR]

• We provide a list of road elements that may reduce driving speed for inner and outer city roads. • We provide a new method to estimate the effects of road measures on driving speed. • We show that the lay-out of the environment immediately generates an estimation of a credible speed choice. • The results are consistent with the notion of Self-Explaining Roads. One of the leading principles for road design is the notion of Self-Explaining Roads (SER). According to this notion, the design and layout of the road environment should automatically elicit behavior that is appropriate for that type of road. The current study investigated the effects of the road environment (i.e., the presence of particular road elements such as the presence/absence of edge lines, and a physical separation between driving lanes) on driving speed choice in the Netherlands for roads in- and outside the city limits (ICL and OCL). A total of 462 participants (all car drivers) were exposed to either 152 ICL or 152 OCL pictures of road environments for either a short (300 ms in Experiment 1, 200 ms in Experiment 2) or long duration (1500 ms) and indicated as fast as possible which speed they would drive given the road environment they viewed. All images were labeled with respect to the presence or absence of particular road elements. A linear mixed model was used to determine the effects of road elements on speed choice and response time. The results showed that the presence of certain road elements impacted the speed chosen. For example, inside the city limits, relative to no bicycle lane, a bicycle lane painted on the road reduced driving speed while a separate bike lane increased the speed chosen. Also, central line markings (relative to no line marking) and a road made of asphalt (relative to pavers) were associated with higher speeds. Outside city limits, having multiple lanes (versus one lane) was related to higher speeds and having two driving directions without separation (versus a one-way road) was related to lower speed choices. Importantly, exposure duration (200 /300 ms versus 1500 ms) only had a marginal effect, indicating that road users generally only need a brief glimpse of the road to be able to decide what speed to drive. Consistent with the principles of SER, we conclude that categorization and the associated speed decision is fast, operating within a single glance and is impacted by the road elements present in the environment. Finally, we believe our method constitutes a valuable tool in road design, as it allows one to efficiently and effectively gauge the impact of various road elements in large population samples. [ABSTRACT FROM AUTHOR]

• The road user experience is defined as the subjective perception of the road traffic environment that road users experience when participating in urban road traffic. • Car drivers' road user experience integrates the experience of static with perceptions of dynamic, and describes the overall road traffic environment experienced by car drivers. • Car Drivers' Road User Experience Scale comprises four factors: travel experience, road condition experience, road sign experience, and road network experience. • Car drivers' road user experience is closely related to the amount of tasks they experience while driving and traffic climate. • Investigation of such experience can avoid the limitations of the human–computer interaction model, and help to develop a virtuous cycle of driving experience improvement and road system optimization. Urban roads serve a wide variety of road users, and the content and level of urban road user experience is an important part of evaluating and improving the service quality of road traffic. The study aim was to increase understanding of the road user experience of car drivers by developing and validating the Car Drivers' Road User Experience Scale. Using web-based questionnaires, three studies were conducted with three independent samples of Chinese car drivers to develop and validate the measurement scale. The results showed that the scale comprises four factors: travel experience, road condition experience, road sign experience, and road network experience. This study explored the theory and characteristics of car drivers' road user experience and provided a new scientific measurement tool. This tool could provide new data to support strategies to improve driver road user experience and promote the development of the urban road traffic environment. [ABSTRACT FROM AUTHOR]

• Highway user risk perception on varying curve geometry consists of horizontal, vertical and a combination of horizontal and vertical curves. • Effects of human factors on the user behavior and their perception of traffic safety. • Structural Equation Modeling approach to model the user risk behavior/perception on varying curve geometry. • Ranking the user risk perception using Garrett's ranking method. • Comparison of qualitative and quantitative risk perception for the same set of curve geometry data. Driver risk perception ability depends on how they perceive and interpret information from different sources to safely and comfortably operate their vehicles based on the highway features ahead. The present study is divided into two parts to review these aspects: (a) identifying the factors that influence driver risk-taking behavior, and (b) evaluating the soundness of the identified factors by comparing them with quantitative risk perception. For that, 1075 user perception data were collected using a developed questionnaire form through face-to-face interviews. A questionnaire form consists of a total of 33 questions/variables. After applying the factor reduction techniques, namely principal component analysis, the most significant variables (19 questions/variables) influencing the user's perception are identified. Then, considering these significant variables, five separate risk perception models were developed using the Structural Equation Modeling technique for five varying curve geometries. The results revealed that the user's risk perception changes for the same user for varying curve geometry. It is also identified that male drivers have more risky behavior (lower risk perception) than female drivers. Besides, Garrett's ranking technique is also adopted to rank the user risk perception for the varying curve geometry to identify the dangerous curves by assigning the rank. Lastly, to check the feasibility of the results, the risk perception score is also compared with the quantitative risk score. Based on the study results, it is concluded that the study findings will be helpful for highway planners and authorities to introduce some safety measures to alert users of the potential hazards on the roadside and increase their capacity for taking risks on complex curves; hence, the likelihood of crashes can be minimized. [ABSTRACT FROM AUTHOR]

In recent years, vehicle traffic has become a major issue, with a significant increase in the number of vehicles leading to congestion on urban roads and motorways. This has resulted in an increase in accidents, causing more injuries and fatalities. In particular the cases with seriously injured road users who may not survive due to traffic congestion delaying emergency services. This paper tries to analyse the importance of the response time of the emergency services during road accidents, using real data from a hybrid environment (motorway and urban road). The presented model in this research aims to identifying the traffic problems, where the traffic lights are found to cause congestion issues and high travel times, even with low traffic volumes. The implementation of a traffic lights optimization system can be a crucial element in survival chances. The study also shows that an increase in traffic volume leads to drastic traffic congestion, highlighting further the importance of the traffic light optimization system. [ABSTRACT FROM AUTHOR]

Nowadays, road safety is a major concern for public authorities on national, secondary and classified roads in developing countries. This paper looks at the problem of non-compliance with road signs and the deteriorating state of roads, which are the cause of many accidents. Road users sometimes miss roadside signs because their attention is focused on the road. At other times, they regularly miss certain road markings or road deformations in unfamiliar areas, which is dangerous for travelers. Ideally, therefore, drivers should be able to be alerted to road signs or deformations from a distance without having to divert their attention. This would make it possible to avoid accidents, especially on national roads between regions of a country and between countries in sub-Saharan Africa. In this paper, we propose a model for the detection and recognition of road signs and deformations using deep learning. The dataset for this model will consist of a hybrid dataset that includes Kaggle data and data from AGEROUTE (Autonomous Agency for Works and Road Management) in Senegal. In addition, the proposed model is trained on two datasets; one for training 80% and the other for testing 20%. Experimental results showed that the proposed model achieved an accuracy of 95.34% for the datasets. [ABSTRACT FROM AUTHOR]

The frequency of potholes and speed bumps on the roads has linearly increased due to ageing, inadequate maintenance, and a growth in the number of vehicles. We have discussed a prototype for the identification of potholes and speed bumps in order to guarantee safe mobility. Such critical road quality data may be made public or shared with local governments and other government agencies for the purpose of corrective action and road maintenance. A pothole detection system using image processing and cloud storage can be used to detect potholes from footage provided by a device, store the information into a cloud database, and analyze the data to identify areas that need repair. The system can also send alerts to users about upcoming potholes and notify road maintenance authorities of new pothole detections. In brief, the system uses image processing to detect potholes and cloud storage to store and analyze the data. It can also send alerts to users and road maintenance authorities. The model was built using YOLOv5 and trained on 70% of the dataset images. It was able to detect potholes with good accuracy in the output images. [ABSTRACT FROM AUTHOR]

Two-lane rural roads require management that integrates all road users, especially cyclists, who have reached significant traffic levels. Management measures must focus on increasing safety and, wherever possible, also improving traffic operation. Speed limit management can be a solution, however it has to be based on scientific criteria. In this study, various speed limits were simulated on a narrow rural road using a traffic microsimulation model and considering a set of scenarios combining motor and cycle traffic levels. As a results of simulations, performance measures were obtained to characterise safety and traffic operation. The optimal speed limit for each traffic level was obtained by a Multi Criteria Decision Making method, using performance measures as criteria. The results point to the groups of cyclists to ride two-abreast, and to a dynamic management of the road speed limit, reducing the speed during periods of peak motorised and bicycle traffic. It is recommended to adapt the study to each rural road considering its traffic and geometric characteristics, calibrating the traffic microsimulation model and obtaining a specific dynamic speed limit management model. • Cycle traffic on rural roads means a reduction in safety and traffic operation. • On rural roads a management integrating all road users is needed. • Dynamic speed limit management is recommended on rural roads with mixed traffic. • Low speed limits are safer and more operational for high cycle traffic levels. [ABSTRACT FROM AUTHOR]

• The results show much variation in how well people understand traffic signs. • Utilizing ergonomic concepts can increase how well people understand traffic signs. • Familiarity is the criterion that is likely to determine how well someone understands traffic signs. • Before installation, traffic signs should be evaluated among a diverse target audience. Road signs are an essential component of a safe driving environment. Understanding road signs is vital to road safety. This paper reviews many earlier investigations into how well drivers understand road signs, considering ergonomic principles. Articles from 2012 to 2023, indexed by Web of Science, Scopus, Google Scholar, IEEE, Semantic Scholar, Science Direct, Cambridge Core, and JSTOR, were used to evaluate the literature on ergonomics and road signs comprehension. The analysis reveals that some evaluation techniques have been created to measure how well road signs are understood. Based on International Standard Organization (ISO, 3846 and 39001), 268 road signs were reviewed out of which, 112 (41.79 %) road signs are associated with lower comprehension scores and may pose a higher risk to road users who many not fully understand their meaning. 156 (58.21 %) road signs associated with higher comprehension scores and likely understood by road users. In conclusion, human traits, cognitive sign design and ergonomic principles are crucial for understanding and producing road signs. It was suggested that applying ergonomic ideas to the design of road signs can increase user comprehension. [ABSTRACT FROM AUTHOR]

• This works confirms the interest of differentiating car drivers and motorcyclists. • The results show an effect of both the type of vehicle and the health crisis on the rules respected. • This wok allows for theoretical reflection on the construction of the relationship to social and legal rule. The aim of this article is to examine the construction of the relationship with rules, their links in individuals throughout their lives and their possible interactions. More precisely, this paper looks at the impact of the health crisis, COVID 19, on compliance with road rules among three categories of road user: car drivers, motorcyclists with a cylinder capacity of no more or more than 125 cm3. A questionnaire was designed and distributed to 4382 car users, motorcyclists with a cylinder ca-pacity of more or no more than 125 cm3. representative of the French population. The results show an effect of both the type of vehicle and the health crisis on the frequency and number of safety rules respected. These results confirm the value of differentiating the road-user population by showing the differences between motorists and motorcyclists, which are not due solely to the mode of travel used. In terms of road safety policy, they show the importance of prevention campaigns targeting different modes of travel, and taking into account the specificities of their users in terms of perception of rules and the factors involved in their observance. [ABSTRACT FROM AUTHOR]

• A simulator-based study investigates the effects of monitoring requests and voluntary non-driving related tasks on young drivers' fatigue and performance. • Engaging in non-driving related tasks can keep drivers alert but no difference in take-over performance. • The monitoring requests stimulate drivers to respond faster and take-over better in prolonged conditional automated driving. • The design of monitoring requests is positively assessed by workload, acceptance, and trust. Introduction: L3 automated vehicles can perform all dynamic driving tasks unless a take-over occurs due to operational limits. This issue is potentially important for young drivers who are vulnerable road users since they have skill deficits and easily evolve into aberrant driving. However, drivers lacking active involvement may be fatigued and drowsy. Previous research indicated that performing a voluntary non-driving-related task (NDRT) could keep drivers alert, but there was no difference in take-over performance with or without NDRT. Providing a monitoring request (MR) before a possible take-over request (TOR) exhibited better take-over performance in temporary automated driving. Therefore, the study aimed to investigate the effects of MR and voluntary NDRT on young drivers' fatigue and performance. Method: Twenty-five young drivers experienced 60 min automated driving on a highway with low traffic density and a TOR prompted due to a collision event. A within-subjects was designed that comprised three conditions: NONE, TOR-only, and MR + TOR. Drivers were allowed to perform a self-paced phone NDRT during automated driving. Results: The PERCLOS and blink frequency data showed that playing phones could keep drivers vigilant. The take-over performance on whether taking phone had no difference, but with MRs condition exhibited better take-over performance including the shorter reaction time and the longer TTC. Subjective evaluations also showed the advantages of MRs with more safety, trust, acceptance, and lower workload. Conclusions: Taking MRs had a positive effect on relieving fatigue and improving take-over performance. Furthermore, MRs could potentially improve the safety and acceptance of automated driving. Practical Applications: The MR design can be used in the automotive industry to ensure the safest interfaces between fatigue drivers and automation systems. [ABSTRACT FROM AUTHOR]

• The study evaluated effects of the speed limit reduction on crash severity in Seattle. • The speed limit reduction was associated with significant reductions in odds of a crash involving KAB injury among all crashes and crashes on arterials in downtown Seattle. • There were smaller and not significant reductions outside the downtown in Seattle. • The study adds to the limited research in the United States that examines crash effects of lowering speed limits in large, populous urban areas. Introduction : Effective November 2016, the default speed limit in Seattle was lowered from 25 to 20 mph on nonarterial streets and from 30 to 25 mph on arterial streets, unless otherwise posted. In the downtown area, signs indicating the new speed limit were installed on arterials when the lower default limit took effect. Outside the downtown, new speed limit signs were installed on some arterials starting in 2018. The study evaluated effects of the speed limit reduction on crash severity in Seattle. Method: Police-reported crashes in Seattle and three control cities in Washington before and after the speed limit change were examined. Logistic regression analyses evaluated effects of the speed limit reduction on odds that a crash involved a fatal (K), disabling (A), or evident (B) injury inside and outside Seattle's downtown. Separate analyses were performed for all crashes (except those occurring on interstates and freeways), for crashes on arterials, and for crashes on nonarterial roads. Results: The speed limit reduction was associated with a significant 17.2% reduction in odds of a crash involving KAB injury among all crashes and a 19.9% reduction for crashes on arterials in downtown Seattle. There were smaller reductions outside the downtown (7.4% for all crashes and 10.7% for crashes on arterials), but they were not significant. Conclusions: Communities should consider lowering speed limits to improve safety for all road users. When doing so, they should not wait too long to modify speed limit signs to remind drivers of the new speed limits to maximize the safety benefits. [ABSTRACT FROM AUTHOR]

• Riders moved significantly further away from overtaking vehicles equipped with Adaptive Headlamp Systems (AHS) compared to a control condition. • AHS has the potential to improve bicycling safety in nighttime conditions when lighting conditions are poor. Introduction : The risk of motor vehicle-bicyclist crashes and fatalities is greater during nighttime than daytime lighting conditions, even though there are fewer cyclists on roadways at night. Vehicle Adaptive Headlamp Systems (AHS) aim to increase the visibility of bicyclists for drivers by directing a spotlight to illuminate bicyclists on or near the roadway. AHS technology also serves to alert bicyclists to the approaching vehicle by illuminating the road beneath the rider and by projecting a warning icon on the roadway. Method: Here, we examined how bicyclists respond to different AHS designs using a large screen, immersive virtual environment. Participants bicycled along a virtual road during nighttime lighting conditions and were overtaken by vehicles with and without an AHS system. The experiment included five treatment conditions with five different AHS designs. In each design a box of white light was projected beneath the rider; in four of the designs an icon was also projected on the road that varied in color (white or red) and position (to the left of the rider at midline or to the left of the front wheel). Participants in the control condition experienced only non-AHS vehicles. Results: We found that riders in all AHS treatment conditions moved significantly farther away from overtaking vehicles with AHS systems, whereas riders in the control condition did not significantly move away from overtaking vehicles without AHS systems. Practical Applications: The experiment demonstrates that AHS has potential to increase bicycling safety by influencing riders to steer away from overtaking vehicles. [ABSTRACT FROM AUTHOR]

• The study aimed to investigate factors influencing risky driving behavior and potential solutions to the problem. • Road users engage in risky behavior due to problems, including qualitative, geometrical, traffic, and operational issues. • Perceived problems and accident history have a positive and direct impact on the risky behaviour of road users. • Providing fully automated RRGCs with minimum gate blockage duration emerged as the most influential mitigation strategy. • The findings would assist policymakers in developing evidence-based strategies to improve the safety and credibility of RRGC. [ABSTRACT FROM AUTHOR]

The rapid expansion of ride-hailing service has imposed a huge amount of additional traffic on urban transportation systems. To reduce congestion, different regulatory policies have been announced to control the number of ride-hailing vehicles in metropolitan areas around the world. However, these measurements, shooting at ride-hailing vehicles only, deprive non-car owners of their private-car mobility rights (endowed by ride-hailing services), therefore are debatable in themselves. Instead of imposing specialized restrictions on ride-hailing vehicles, we propose to cure the deteriorating traffic conditions with classic traffic regulation policies implemented on all road space users. In this study, in a simple one corridor scenario with two different types of ride-hailing services, i.e., ride-sourcing and ride-sharing, we model travelers' mode choices at user equilibrium under no policy intervention to reveal the negative impacts of ride-hailing on urban transportation efficiency, and compare the different system optimum states with and without ride-hailing to demonstrate the great potential of ride-hailing in mitigating congestion. Based on the model, we then examine the impacts of three traffic regulation policies, i.e., road space rationing, congestion pricing and tradable credit schemes, and investigate the existence of traffic regulation policies that can achieve system optimum in the presence of ride-hailing. • This paper studies the impacts of two ride-hailing services on traffic condition. • This paper shows that ride-hailing services may increase or decrease congestion. • This paper studies the effectiveness of three classic traffic regulation policies. • This paper reveals the existence and properties of system optimal policies. [ABSTRACT FROM AUTHOR]

• Public transport users were interviewed during Covid-19 pandemic in Ankara, Türkiye. • Thematic analysis revealed 4 overarching and 15 sub-themes. • Changes in transportation patterns during Covid-19 habits were reported. • Future directions for better transport planning were noted. • Transportation inequity that becomes more visible after the pandemic has been discussed. Due to the COVID-19 outbreak, people refrained from crowded places; public transport is one of them. The need for movement was restricted as part of governmental precautions. However, some people continue to go to workplaces as usual, and the ones who do not have personal vehicles continue using public transportation. The current study aims to investigate the experiences of public transport users (i.e., passengers) in Türkiye during the COVID-19 pandemic. Semi-structured interviews were conducted with ten people living in Ankara. As a result of thematic analysis, four overarching themes and fifteen sub-themes were determined. These overarching themes include changes in travel behavior during COVID-19, factors influencing transportation preferences, suggestions for better planning of public transport services, and suggestions for better crisis management. The results suggest significant policy implications at the municipal and governmental level, emphasizing the need for transparent risk communication, timely measures, and enforcement. Additionally, the study highlights transportation inequity, which becomes visible after the pandemic. We believe that qualitative data provided valuable insight to road authorities about road users' transportation experiences during the pandemic and, thus, how to manage better the pandemic's effect on the transport system based on the mobility needs of the citizens. We hope the results could benefit road authorities in developing effective policies and plans for all countries in the world, especially for the ones having a specific need to improve safety in traffic settings. [ABSTRACT FROM AUTHOR]

• Evaluation of a system warning cyclists against safety critical events trimodally. • Cyclist warning system using real time information provided by connected traffic. • Earlier braking reactions for rides with vs. without warning system. • System can enhance cyclists' situation awareness in safety critical situations. • Increased perceived safety and stable workload for rides with vs. without system. Problem: Increasing numbers of crashes involving pedelecs, and particularly older pedelec users, induce a need to enhance cycling safety. We evaluated a prototype cyclist warning system (CWS) that aims to increase situation awareness (SA) by alerting to safety critical events (SCE) with trimodal (auditory, visual, tactile). Method: To investigate the effects of CWS usage, we conducted a 2x2 mixed design bicycle simulator study with factors (1) CWS usage (within: rides WITH vs. WITHOUT CWS) and (2) age group (between: younger vs. older cyclists) on braking reaction time, gaze behavior, mental workload, and perceived safety. In sum, N = 64 participants (n = 32 younger, 18–40 years; n = 32 older, ≥ 55 years) took part in the study and experienced two balanced blocks of short rides including SCE of particular relevance for cycling safety. Results: CWS usage resulted in earlier braking reactions to all investigated SCE and partly earlier fixation on the critical interaction partners (CIP) indicating increased cyclists' SA. Consistently to behavioral measures, participants' assessments regarding perceived safety further supported the safety improvements derived from CWS independently of age group. Moreover, CWS usage did not add to mental workload ratings. Age effects were selectively found for gaze data showing that across all SCE, older adults fixated longer and more frequently on street alignment, and less frequently on other road users. Discussion: Taken together, the CWS evaluation showed promising results indicating the potential of the tested CWS to increase SA and enhance cyclists' safety both on a behavioral level and regarding subjective assessments. Further research should address the systems' safety potential under real-world conditions and for situations of higher complexity. Practical Applications: Understanding the potential impact of road safety measures such as CWS is important to contribute effectively to reducing SCE. [ABSTRACT FROM AUTHOR]

• The criteria Mental Comfort, Interaction, Environment, Ease of Use, and Physical Comfort can be used to assess cyclists' route evaluations and preferences. • Interactions with pedestrians or motor vehicles differ in concentration and mental comfort. • Route attributes and criteria vary in their impact on the overall evaluation. Problem: Previous research on cyclists' route evaluations and preferences already identified influencing factors and relevant evaluation criteria, but studies mostly focused on selected aspects like safety or comfort. This study examined the evaluation of routes more comprehensively considering five evaluation criteria, and further aims to compare the evaluation with the preference of routes. For this, we used the experimental approach of a bicycle simulator. Method: Our participants cycled route segments that varied in certain route characteristics. Each segment was rated in total and on five criteria generated in a previous study, namely Mental Comfort , Interaction , Environment , Ease of Use , and Physical Comfort. At the end, all route segments were ranked according to their quality. Results : Results showed that separated paths were rated the best, while busy footpaths and uphill segments were rated the worst. Interestingly, interacting with pedestrians was described to be more attention-demanding but not as mentally uncomfortable as interacting with motor traffic. The evaluation and preference of routes mostly went hand in hand but differed for the footpath, which was ranked better than it was rated. Results further indicated that gradient has such a strong impact on the physical comfort of a route that it even influenced the overall evaluation. Discussion: Our findings suggest that the evaluation and preference of routes is influenced by the degree of separation, traffic volume, the type of the road user that the cyclists may need to interact with, but most importantly, it is influenced by the interaction of these three aspects. Practical Implications: The five criteria we used can reliably assess the evaluation and preference of routes. They help to differentiate the reason for negative evaluation of routes. This differentiation is crucial to improve cycling routes, as different causes for dissatisfaction among cyclists require different consequences. [ABSTRACT FROM AUTHOR]

• Study analyses fatal injuries to cyclists caused by single-bicycle crashes (SBCs) • SBCs commonly involved people aged 60–79, males, and cyclists not wearing a helmet. • Males were more often involved in SBCs than other cyclist crashes. • Underlying illness and use of alcohol were highlighted in SBCs. • Human factors were the most identified underlying factor in SBCs. Problem: Increasing the role of cycling is necessary to reduce physical inactivity. While promoting cycling, attention should also be given to traffic safety. Hence, a better understanding on the underlying factors and safety recommendations of cyclist crashes is needed. This study aims to increase knowledge on fatal single-bicycle crashes (SBCs), where other road users are not collided with. Method: Data from in-depth investigated fatal cyclist crashes in Finland is analyzed from 2010 to 2019. The study presents descriptive analysis of the characteristics, underlying factors, and safety recommendations of SBCs (n = 82) and other cyclist crashes (n = 151). Logistic regression analysis and chi-squared tests were performed to identify significant characteristics for SBCs. Results: Fatal SBCs commonly involved people aged 60 or older, males, and cyclist not wearing a helmet. Cyclist's health issues influenced the crash in 62.2% of the SBCs. Compared to other cyclist crashes, health issues, alcohol, males, other crash locations than intersections, and weekends were highlighted in SBCs. Safety recommendations emphasized human factors, such as informing cyclist about underlying factors and the use of safety equipment. Discussion: In addition to human factors, the safety recommendations included suggestions regarding the bicycle, the traffic environment, and traffic regulations. This highlights the need to focus on different safety improvement actions to reduce SBCs. This study identified key characteristics of SBCs, which may help traffic safety authorities address this road safety issue and ultimately help to promote cyclist safety. Practical Applications: Cooperation between the actors including health care providers and the police is also proposed to address cyclists' health issues that contribute to SBCs. [ABSTRACT FROM AUTHOR]

• Being familiar with a road scene is the default mode of how we behave in traffic. • Four consecutive empirical studies revealed a pattern of increased automaticity. • Familiarity led to disengagement, monitoring rather than attending the road. • When studying what is seen this common cognitive mode impacts research methodology. • It is proposed to regard route familiarity as a context that enables distraction. Most trips are made, and most travel is done on roads and paths well-known. To provide insight in the cognitive processes involved in visual information processing of familiar traffic environments this paper considers a series of four consecutive empirical studies. The aim of this paper is 1) to discuss the implications of these insights on research methodologies used to measure driver attention and distraction and 2) to provide recommendations for policymaking, road design and vehicle design. This line of work consists of three studies on car driver behaviour (two driving simulator studies and a video-based study) and an observational study on pedestrian behaviour. The recurring theme in the results of these studies is that the progressive exposure to the same traffic environment enables participants to automatise their behavioural performance in traffic up to the point that it could be executed at skill-based level. As a result, attention is easily diverted away from traffic participation, while participating in traffic. Participants could act without thinking about it, so they didn't always even remember what they had done. People get used to familiar traffic environments so much that they don't have to think about walking or driving with much conscious focus. Hence, when studying road user behaviour and particularly driver distraction, it is crucial to mimic these natural circumstances as closely as possible. It is therefore proposed that within driver distraction research, route familiarity should be regarded as a context that enables distraction. What is more, is that the results point in the direction of a familiarity paradox : deviating from what is very familiar likely results in involuntary distraction, but being very familiar may lead to underload resulting in (voluntarily) diverting attention elsewhere. [ABSTRACT FROM AUTHOR]

• Video observation of pedestrian behaviour in integrated street design was conducted. • Discernible features and revealed pedestrian choices were analysed mesoscopically. • Speed and crossing on red incidence were modelled before and after redevelopment. • Pedestrians were found to walk less hastily and more confidently post-redevelopment. • Effects were stronger for pedestrians walking alone and walking to work. Recent trends in urban design have called for more equal treatment of all road users and have effected a shift away from the traditional concept of segregation and towards more integration. This usually translates to more pedestrian-friendly layouts with wider footways, fewer protective guardrails and lower (or even no) kerbs. Following-on from previous research on the topic, this study explores changes in pedestrian behaviour in response to integrated street design. A "mesoscopic" level of analysis is adopted, whereby the actions and revealed choices of individual pedestrians are modelled probabilistically, but without a detailed investigation into their attitudes and perceptions. Video footage from London's Exhibition Road site during periods before and after its conversion from a conventional layout to a more integrated pedestrian-oriented design is used, and an observation scheme focusing on pedestrian actions and discernible characteristics is devised. Inferential statistics methods are used to derive models expressing two behavioural traits: walking/crossing speed, and crossing on red incidence. The results suggest that the additional space provided and the reduced crowding post-redevelopment results in pedestrians walking less hastily and close to their desired speed, while the friendlier conditions created by the street layout increase their confidence to enter the road space and cross, sometimes even on a red signal. In particular, those walking alone (rather than in a group) and walking to work (rather than leisure) appear to walk faster and are also more likely to cross on red. [ABSTRACT FROM AUTHOR]

• An Extreme Value Theory approach is used to model autonomous vehicle–pedestrian interactions and estimate crash risk. • A Bayesian hierarchical structure incorporates several behavioral covariates. • A comparison between pedestrian behavior in interactions with Autonomous and HumanDriven Vehicles is conducted. • Data collected from Autonomous Vehicles in four cities (Boston, Las Vegas, Pittsburgh, and Singapore) is used. • The crash risk varies across different interaction types and traffic environments. Autonomous Vehicle (AV) technologies are expected to result in significant safety and mobility benefits to the road system. However, one of the most important issues that autonomous vehicle technology faces is ensuring safe interactions with active road users such as pedestrians who can have unpredictable behavior. Moreover, road user behavior varies considerably across different traffic environments, which might represent a challenge to implementing AVs as they lack the intuition common in human-driven vehicles (HDV). This study proposes an approach to evaluate crash risk in vehicle–pedestrian interactions. An Extreme Value Theory (EVT) Peak Over Threshold (POT) model is used to compare the crash risk of AV-pedestrian and HDV-pedestrian interactions in four different cities, namely Boston, Las Vegas, Pittsburgh, and Singapore. A Bayesian hierarchical structure is used to incorporate the effect of several behavioral covariates, which enables estimating the crash risk of each interaction. Results show that the risk varies considerably depending on the type of interaction and the environment. For example, the impact of behavioral covariates (i.e., minimum distance between road users and maximum pedestrian speed) on the risk of AV-pedestrian interactions is greater when compared to the risk of HDV-pedestrian interactions in Boston, Las Vegas, and Singapore. This might indicate that, in busy and congested environments, road users may not be entirely comfortable with the presence of AVs. In addition, Singapore presented a higher percentage of riskier AV-pedestrian interactions when compared to the other cities. Finally, this study offers significant insights into the challenges of introducing AVs in diverse environments as behavior plays a crucial role in traffic and can influence conflict occurrence. [ABSTRACT FROM AUTHOR]

• Seven predictors for HP in older adults have been investigated. • Driving experience and auditory distraction were consistent predictors of HP. • Advancing age, declining cognitive and visual function are not consistent predictors of HP. • Training has been shown to significantly improve older adult HP drivers. • Limited research has been done in the factors that predict HP in non-drivers. Background : Older adults are more likely to be at-fault and killed in road crashes, and this has been argued to be due to their declining hazard perception (HP). There has been no comprehensive review on what factors predict this decline in HP ability for older adults. Objectives: The aim of this systematic review is to identify any predictors of HP in older adults across all road-user types. Data Sources: The search was indexed in the Medline, PsycINFO, and Scopus during January 2022. Studies had to be peer reviewed and written in English language. Participants had to be road-users over the age of 60. Studies had to investigate a relationship between a predictor and HP. Results: 21 articles met the inclusion criteria, 20 for drivers and one for pedestrians. Seven predictors were examined. Results suggested that driving experience and auditory distraction were the most consistent predictors of HP. HP training for drivers significantly improved HP. Results were mixed for visual abilities, cognitive abilities, and age. Training for pedestrians was not a significant predictor of HP. Limitations: Grey literature was not reviewed. Conclusions: Whilst results related to age were mixed, most studies suggested that advancing age is associated with HP decline. Driving experience appeared to be a protective factor against decline in HP. Contrast and motion sensitivity may be important in identifying at-risk drivers. Cognitive function was not a consistent predictor of HP. Auditory distractors consistently negatively impacted HP. Results indicated that there could be potential benefits of HP training. There is a dearth of research into HP in vulnerable road user types. Implications: By identifying the predictors of HP, road safety strategies such as holistic training programs could be developed to assist with keeping older adult road-users safe. Future research is necessary to explore HP in older pedestrians, cyclists, and motorcyclists. [ABSTRACT FROM AUTHOR]

• Simulator study of the impact of pedestrian crossing infrastructure on road crossing behaviour around an automated vehicle. • The automated vehicle's yielding behaviour was the most important source of information for pedestrians, followed by crossing infrastructure. • eHMI had the most impact in the absence of a zebra crossing. • Results show the importance of eHMIs for situations associated with uncertainty about right-of-way between an automated vehicle and other road users. • Results highlight the interaction between formal traffic infrastructure and explicit forms of communication for future automated vehicles. Previous research has shown that the use of an eHMI can lead pedestrians to make earlier, and more, crossing decisions in front of an automated vehicle (AV). However, there has been little exploration of the impact of crossing infrastructure or AV approach direction on pedestrian behaviour. This CAVE-based pedestrian simulator study investigated the individual, and combined, effects of a pedestrian crossing, AV approach direction, AV yielding behaviour, and a novel external Human Machine Interface (eHMI) on pedestrian crossing decisions at a four-way crossroads. Thirty eight participants took part in a multi-method study consisting of a pedestrian simulator experiment, an online interview, and a short questionnaire. The main independent variables were: (1) presence or absence of a zebra crossing; (2) the direction from which the AV approached (oncoming/right); (3) the AV's yielding behaviour (yielding/not yielding); and (4) the presence or absence of a light-based eHMI. The AV's yielding behaviour was the most important source of information for pedestrians, followed by the crossing infrastructure. Participants showed a greater willingness to cross in front of yielding than non-yielding vehicles, and were more likely to cross in the presence of a zebra crossing. The eHMI had the most impact in the absence of a zebra crossing, promoting earlier crossings, and encouraging more participants to cross while the approaching AV was still moving. The results of this study show the importance of eHMIs for situations associated with uncertainty about right-of-way between an AV and other road users, and highlights the interaction between formal traffic infrastructure and explicit forms of communication for future AVs. This knowledge increases our knowledge of when and where explicit communication from AVs can reduce the likelihood of pedestrian misunderstanding of AV intentions, thus reducing the likelihood of accidents occurring around these vehicles. [ABSTRACT FROM AUTHOR]

• 15 359 pedestrians received healthcare after a fall or collision accident. • There was a higher proportion of women and older age pedestrians. • Of all injured pedestrians, 22% had a new sickness absence. • Falls on snow or ice were associated with a higher odds ratio for sickness absence. • Construction, health & social care had the highest odds ratios for sickness absence. Objectives : This study explores pedestrian fall accidents and collisions with other road users in the Swedish road transport system, and sickness absence (SA) in relation to accident type, injury, and occupation. Further, it studies the associations between accident type, occupation, and duration of SA. Methods: Data from several national registers were used that included 15,359 working age pedestrians (20–64 years) receiving healthcare after a fall or collision throughout 2014–2016. Individual characteristics, accident type, injury, and occupation were presented and related to SA. Logistic regression was used to estimate odds ratios (OR), with 95% confidence intervals, for associations between accident type, occupation, and SA duration. Results: About 11,000 pedestrians (72%) were involved in fall accidents in the road traffic environment and well over 4,000 in collisions with another road user; 22% of all injured pedestrians had a new SA. The population had a higher proportion of women and individuals in older age groups (≥45). Of the falls, 31% were due to snow or ice, and these were associated with a higher OR for both short SA (<90 days) 1.76 (95% CI 1.56–1.98) and long SA (≥90 days) 1.81 (95% CI 1.51–2.18), compared to the group slipping, tripping, and stumbling. The working sectors health & social care, and construction had the highest ORs for SA. A higher OR was found for health & social care, short SA 1.58 (95% CI 1.38–1.81), long SA 1.79 (95% CI 1.45–2.20) and for construction, short SA 1.56 (95% CI 1.24–1.96), long SA 1.75 (95% CI 1.26–2.44), compared to the sector finance, communication, & cultural service. Conclusions: The OR for having short and long SA was higher in falls due to snow or ice and differed between occupational sectors. Practical implications: This information contributes to the knowledge base for planning a safe road transport system for pedestrians. [ABSTRACT FROM AUTHOR]

Connected and automated vehicles (CAVs) leverage emerging vehicle connectivity and automation technologies to enhance traffic safety. Extensive research has been done to examine the safety impacts of CAVs on road users (including vehicle occupants and vulnerable road users). Still, the impacts on first responders, who respond to traffic incidents and assist road users, are under-discussed. Road users show growing interest in CAVs, but it is uncertain whether first responders would feel the same way. First responders face the risk of being struck by passing vehicles when they perform their duties on road or roadside. In addition, it is unknown whether CAVs can or will do a better job than human drivers in conventional vehicles when passing an incident scene. This study conducted a national survey among first responders in the US to understand their knowledge and incident management experiences related to CAVs, as well as their attributes and concerns towards CAV technologies, including advanced driver assistance system (ADAS), connected vehicle (CV) and self-driving or autonomous vehicle (AV) technologies. Over 1000 first responders participated in the survey, and the survey had representation from all 50 states, Washington DC, and US Territories. The survey results showed that 82% of first responders have not received any CAV-related safety training, and 41% of first responders self-reported having little knowledge about CAVs. Regarding the roles of AVs in emergency responses, only a tiny portion (3%) of first responders would trust AVs more than human drivers passing an incident scene, and the majority (86%) of first responders do not think AVs will outperform human drivers. Only 1% of first responders said they trust AVs, and 44% stated that they do not trust AVs at all. A statistical model was developed to identify the correlates of first responders' trust in AVs. Modeling results showed that education positively correlates to the likelihood of trusting AVs. This study found significant differences in perceptions towards CAVs across emergency response agencies and geographic regions. Law enforcement officers exhibit higher trust in AVs compared to firefighters; responders from DOT or public works are associated with the lowest levels of trust among all emergency response agencies. FEMA Region 3, which includes Maryland, Pennsylvania, and Virginia, shows the lowest levels of trust in AVs compared to human drivers among all regions in the country. This study provides valuable information for stakeholders to prepare responders for next-generation transportation emergency responses. • National survey conducted among US first responders to assess their knowledge and perceptions towards CAVs. • 82% of first responders lack CAV-related safety training, and 41% have limited knowledge about CAVs. • 86% of first responders do not trust CAVs more than human drivers passing incident scenes. • Significant variations in CAV perceptions observed among incident response agencies and geographic regions. • Strong recommendation for the development of safety training programs focused on CAV technologies. [ABSTRACT FROM AUTHOR]