Road user interactions in a shared space setting: Priority and communication in a UK car park

Appropriate communication between road users can lead to safe and efficient interactions in mixed traffic. Understanding how road users communicate can support the development of effective communication methods for automated vehicles. We carried out observations of 66 pedestrian-driver and 124 driver-driver interactions in a shared space setting. Specific actions and reactions of the road users involved were recorded using a novel observation protocol. Overall, results showed that pedestrians’ failure to look towards a driver created the greatest uncertainty in the interaction, with the driver slowing down, but not completely stopping, in response to pedestrians. Looking towards the driver also influenced which road user took priority in driver-driver interactions. Groups of pedestrians were more likely to be given priority than an individual pedestrian, and the use of vehicle-based signals were also associated with taking priority during an interaction. Our observations show the importance of non-verbal communication during road user interactions, highlighting it as an essential area of research in the development of automated vehicles, to allow their safe, cooperative, interactions with other road users. Observations were made on a limited number of interactions to inform challenges facing future automated vehicles. Further work should therefore be done to corroborate and extend our findings, to examine interactions between human road users and automated vehicles in shared space settings.     

Travel behavior changes and responses to advanced traveler information in prolonged and large-scale network disruptions: A case study of west LRT line construction in the city of Calgary

The objective of this study was the investigation of travel behavioral effects of the reduction in traffic capacity resulting from the construction of the West LRT (Light Rail Transit) line in the city of Calgary, Alberta, Canada. Travelers’ responses to real-time information providing traffic updates and advisory detours due to lane/road closures were also examined. The West LRT alignment extends approximately 8.2 km from downtown into the city’s southwest. Many road closures took place in the vicinity of the LRT line construction zones, inducing significant delays to traffic. Data on travelers’ behavioral responses and responses to real-time information were obtained by conducting a survey on a sample of users of the main road affected by the construction. The survey also investigated the effects of West LRT line construction on drivers’ daily commutes, including increases in travel times, mode choices, alternate route choices, and selection of sources of information on traffic conditions. A significant change in the selection of transportation mode was caused by West LRT construction. Throughout the construction period, there was a decrease in the percentage of respondents who reported private vehicles as their first choice and an increase in the percentage of respondents who preferred public transit as their first and second choices. Radio was found to be the most preferred source for traffic updates and detour advice, followed by variable message signs (VMS). The findings of the en-route information model showed that driving experience, employment status, travel time and purpose, and desire for pre-trip information had significant effects on traveler’s rerouting decisions after getting en-route information through VMS. The results from this study are of interest for understanding behavioral changes for the purposes of traffic management, mitigation schemes and design of advanced traveler information systems in response to network disruptions.     

Behavioural analysis of interactions between pedestrians and vehicles in street designs with elements of shared space

This paper describes the development and implementation of qualitative behavioural criteria in order to analyse the conduct of pedestrians and vehicles when they are required to interact with each other, with particular interest to street designs with elements of shared space. The new behavioural analysis technique is developed by identifying the fundamental principles that underpin existing traffic analyses, such as traffic conflicts techniques, and adapting those to a qualitative framework that describes the mindset and rationale of road users. The technique is then applied to a case study in London, using video data from periods before and after the redevelopment of the Exhibition Road site from a conventional dual carriageway to a modern design with some elements of shared space. With the main goals being to assess the pedestrians’ confidence and the vehicles’ tolerance/patience when forced to interact with each other, behavioural trends are related to instantaneous characteristics of the vehicle flow (vehicle approach speed and traffic density). The data produced are used to develop and validate qualitative behavioural relationships for pedestrian–vehicle interactions, as well as location-specific conclusions for the Exhibition Road site.     

Assessing driver acceptance of Intelligent Transport Systems in the context of railway level crossings

Intelligent Transport Systems (ITS) have the potential to substantially reduce the number of crashes caused by human errors at railway levels crossings. Such systems, however, will only exert an influence on driving behaviour if they are accepted by the driver. This study aimed at assessing driver acceptance of different ITS interventions designed to enhance driver behaviour at railway crossings. Fifty-eight participants, divided into three groups, took part in a driving simulator study in which three ITS devices were tested: an in-vehicle visual ITS, an in-vehicle audio ITS, and an on-road valet system. Driver acceptance of each ITS intervention was assessed in a questionnaire guided by the Technology Acceptance Model and the Theory of Planned Behaviour. Overall, results indicated that the strongest intentions to use the ITS devices belonged to participants exposed to the road-based valet system at passive crossings. The utility of both models in explaining drivers’ intention to use the systems is discussed, with results showing greater support for the Theory of Planned Behaviour. Directions for future studies, along with strategies that target attitudes and subjective norms to increase drivers’ behavioural intentions, are also discussed.     

Timing of early warning stages in a multi stage collision warning system: Drivers’ evaluation depending on situational influences

By means of car2x communication technologies (car2x) driver warnings can be presented to drivers quite early. However, due to their early timing they could be misunderstood by drivers, distract or even disturb them. These problems arise if, at the moment of the warning, the safety–critical situation is not yet perceivable or critical. In order to examine, when drivers want to receive early warnings as a function of the situation criticality, a driving simulator study was conducted using the two early warning stages of a multi stage collision warning system (first stage: informing the driver; second stage: prewarning the driver). The optimum timing to activate these two early warning stages was derived by examining the drivers’ evaluation of these timings concerning their appropriateness and usefulness. As situational variation, drivers traveling at about 100 km/h were confronted with slow moving traffic either driving at 25 km/h or 50 km/h at the end of a rural road.In total, 24 participants were tested in a within-subjects design (12 female, 12 male; M = 26.6 years, SD = 7.2 years). For both stages, drivers preferred an earlier timing when approaching slow moving traffic traveling at 25 km/h (first stage: 447 m, second stage: 249 m ahead of the lead vehicle) compared to 50 km/h (first stage: 338 m, second stage: 186 m ahead of the lead vehicle). The drivers’ usefulness rating also varied with the timing, spanning a range of 8 s for driver-accepted timing variations and showed correspondence to the drivers’ appropriateness ratings. Based on these results and those of a previous study, a timing function for each of the two early warning stages depending on the speed difference between the safety–critical object and the host vehicle is presented. Indirectly, similar adaptations are already implemented in current collision warning systems, which use the time-to-collision to give drivers acute warnings in a later stage, when an immediate reaction of the driver may still prevent a collision. However, this study showed that drivers also favor this kind of adaptation for earlier warning stages (information and prewarning). Thus, adapting the timing according to the drivers’ preferences will contribute to a better acceptance of these collision warning systems.     

Analysis of the factors affecting drivers’ queue-jumping behaviors in China

In China, drivers’ queue-jumping behaviors are very common. To explore the factors affecting drivers’ queue-jumping, first, a driving attitude scale, a risk perception scale and a queue-jumping behavior scale were designed, and an existing Type A behavior pattern scale and a driver skill scale were also introduced. Second, these scales were used to collect empirical data, and 202 valid samples were obtained. Third, the reliability and validity of the developed scales were verified, and a structural equation model of drivers’ queue-jumping behaviors was established to explore the interrelationships among the Type A personality trait, cognitions (including attitudes and risk perception), driver skills (including driving skill and safety motivation) and queue-jumping behaviors. The results showed that drivers’ cognitions significantly affected their queue-jumping behaviors; specifically, drivers’ attitudes toward queue-jumping and traffic violations positively correlated with their queue-jumping behaviors (β = 0.323, t = 3.470; β = 0.277, t = 3.072), while drivers’ risk perception toward queue-jumping negatively correlated with their queue-jumping behaviors (β = −0.297, t = −3.889). Drivers’ driving skill and safety motivation also significantly affected their queue-jumping behaviors (β = 0.198, t = 2.385; β = −0.355, t = −4.101). Although Type A personality trait had no significant effects on drivers’ queue-jumping behaviors, it had significant effects on drivers’ attitudes toward queue-jumping and traffic violations (β = 0.336, t = 4.720; β = 0.215, t = 2.873) and their risk perceptions toward queue-jumping (β = −0.232, t = −3.279). In other words, the Type A personality trait can indirectly affect drivers’ queue-jumping behaviors through drivers’ attitudes and risk perceptions toward queue-jumping. The results provided offer traffic administration departments a theoretical foundation for governing this behavior.     

The effect of speed limit credibility on drivers' speed choice

Credibility of speed limits is a key factor affecting drivers’ compliance with speed limits. Two experiments were conducted to investigate how credibility of speed limits affects judgments of appropriate speed. The first experiment aimed to establish speeds deemed appropriate by investigating Malaysians drivers’ judgments of the appropriate speed to drive based on photographs of roads with the speed limit sign erased. Drivers chose speeds which correlated with but were higher than the actual speed limits of the roads. Analysis of road characteristics suggested they based their decisions mainly on features of the road itself rather than of the roadside. The second experiment tested the impact of credibility of speed limit information on the speed drivers judged appropriate. Drivers judged the appropriate speed to drive for the same photographs as in Experiment 1 with speed limit information provided. Four conditions were included: two conditions where the speed limit posted was 10% higher or 10% lower than the appropriate speed established in Experiment 1 (credible speed limits), and two conditions where the posted speed limit was 50% higher or 50% lower than the appropriate speed (non-credible speed limits). Posted speed limits did affect drivers’ judgments about the appropriate speed to drive. Credibility also influenced judgments whereby drivers selected appropriate speeds consistent with the speed limits for the 10% lower condition, but not for speed limits that deviated highly from the appropriate speed judged in Experiment 1.     

Characterization of visual scanning while driving for the identification of drivers’ profiles

Assessing the driving skills of people with cognitive or visual impairments is often complex. The analysis of visual exploration strategies can be a good solution to identify the implementation or not of good strategies of information search in the visual scene (adaptation and compensation). In this study, we compared the visual exploration behaviours of 26 healthy, 19 glaucoma and 21 elderly participants. For this purpose, we used a driving simulator for which a visual field measurement test had been adapted to obtain measurements in static and dynamic conditions. The dynamics of the gaze was also measured. Our results showed that each of the three groups of participants had specific characteristics of visual exploration. Using a classification algorithm, we were able to show that it was possible to identify the group which a participant belonged to on the basis of the visual exploration’s characteristics. This finding opens the door to many applications in the context of driving assistance and training.     

Novel use of a virtual driving assessment to classify driver skill at the time of licensure

Motor vehicle crash rates are highest immediately after licensure, and driver error is one of the leading causes. Yet, few studies have quantified driving skills at the time of licensure, making it difficult to identify at-risk drivers before independent driving. Using data from a virtual driving assessment implemented into the licensing workflow in Ohio, this study presents the first population-level study classifying degree of skill at the time of licensure and validating these against a measure of on-road performance: license exam outcomes. Principal component and cluster analysis of 33,249 virtual driving assessments identified 20 Skill Clusters that were then grouped into 4 major summary “Driving Classes”; i) No Issues (i.e. careful and skilled drivers); ii) Minor Issues (i.e. an average new driver with minor vehicle control skill deficits); iii) Major Issues (i.e. drivers with more control issues and who take more risks); and iv) Major Issues with Aggression (i.e. drivers with even more control issues and more reckless and risk-taking behavior). Category labels were determined based on patterns of VDA skill deficits alone (i.e. agnostic of the license examination outcome). These Skill Clusters and Driving Classes had different distributions by sex and age, reflecting age-related licensing policies (i.e. those under 18 and subject to GDL and driver education and training), and were differentially associated with subsequent performance on the on-road licensing examination (showing criterion validity). The No Issues and Minor Issues classes had lower than average odds of failing, and the other two more problematic Driving Classes had higher odds of failing. Thus, this study showed that license applicants can be classified based on their driving skills at the time of licensure. Future studies will validate these Skill Cluster classes in relation to their prediction of post-licensure crash outcomes.