Promoting pedestrian safety in Bangladesh: Identifying factors for drivers' yielding behavior at designated crossings using behavior change theories.

OBJECTIVE: In Bangladesh, drivers' failure to yield to pedestrians at designated crossings poses a significant safety risk and discourages their use of such crossings. The use of behavior change theories could be more appropriate in such complex situations where the interdependent behaviors of drivers and pedestrians interact. While many studies have identified factors that affect drivers' yielding behavior in the literature, fewer efforts have been made to apply behavior change theories in exploring and validating these factors, and to reach a consensus among competing road users. This study is among the first to utilize behavior change theories in Bangladesh to identify pedestrians' safety factors that could promote drivers' yielding behavior, upon which a consensus between drivers and pedestrians could be established. METHODS: A self-reported attitudinal survey was administered to 202 drivers on two highways in Bangladesh with a questionnaire using the capability, opportunity, motivation, and behavior (COM-B) model for the comprehensive coverage of behavior change theories. The focus group interviews were also conducted with 40 pedestrians and 19 drivers who have experience with four crossing sites on the selected highways. The collected data were analyzed using a regression model to identify significant factors influencing the drivers' yielding behavior. These factors were then justified using a deductive thematic coding framework based on behavior change theories. RESULTS: The regression model explained the variance in drivers' yielding by 45.1% with eight factors. The model found seven positive significant contributory factors in the drivers' yielding that could promote pedestrian safety. Of them, the motivation factors were avoiding random crossing by pedestrians, vulnerable groups, assertiveness, and facial fear expressions; and the opportunity factors were traffic signs or advanced yield lines, crossing in groups at specific times, and enforcement. CONCLUSIONS: The study's findings have practical implications for policymakers, highway designers, and other stakeholders involved in promoting pedestrian safety by acknowledging their stake in making any decision that might impact them. Highway designers can use the thematic coding framework to recommend any contributory factors involved, where competing drivers' unwillingness to yield is the primary threat to pedestrians' safety.

Drivers' Evaluation of Different Automated Driving Styles: Is It Both Comfortable and Natural?

OBJECTIVE: This study investigated users' subjective evaluation of three highly automated driving styles, in terms of comfort and naturalness, when negotiating a UK road in a high-fidelity, motion-based, driving simulator. BACKGROUND: Comfort and naturalness play an important role in contributing to users' acceptance and trust of automated vehicles (AVs), although not much is understood about the types of driving style which are considered comfortable or natural. METHOD: A driving simulator study, simulating roads with different road geometries and speed limits, was conducted. Twenty-four participants experienced three highly automated driving styles, two of which were recordings from human drivers, and the other was based on a machine learning (ML) algorithm, termed Defensive, Aggressive, and Turner, respectively. Participants evaluated comfort or naturalness of each driving style, for each road segment, and completed a Sensation Seeking questionnaire, which assessed their risk-taking propensity. RESULTS: Participants regarded both human-like driving styles as more comfortable and natural, compared with the less human-like, ML-based, driving controller. Particularly, between the two human-like controllers, the Defensive style was considered more comfortable, especially for the more challenging road environments. Differences in preference for controller by driver trait were also observed, with the Aggressive driving style evaluated as more natural by the high sensation seekers. CONCLUSION: Participants were able to distinguish between human- and machine-like AV controllers. A range of psychological concepts must be considered for the subjective evaluation of controllers. APPLICATION: Insights into how different driver groups evaluate automated vehicle controllers are important in designing more acceptable systems.

Effectiveness of visual warnings on young drivers hazard anticipation and hazard mitigation abilities.

Previous studies have demonstrated that young drivers fail both to scan for and mitigate latent hazards mostly due to their cluelessness. This study aims to investigate whether these skills could be improved by providing young drivers with alerts in advance of the upcoming threat using a driving simulator experiment. In particular, the warning was presented on the head-up displays (HUD) either 2 s, 3 s or 4 s in advance of a latent threat. The hazard anticipation, hazard mitigation and attention maintenance performance of forty-eight young drivers aged 18-25 was evaluated across eight unique scenarios either in the presence or in the absence of latent threat alerts displayed on a HUD. There were four groups overall: one control group (no alert) and three experimental groups (2 s alert, 3 s alert and 4 s alert). The analysis of the hazard anticipation data showed that all three experimental groups with HUD warnings (2 s, 3 s, 4 s) significantly increased the likelihood that drivers would glance towards latent pedestrian and vehicle hazards when compared to the control group. The hazard mitigation analysis showed that in situations involving a pedestrian threat, HUD alerts provided 3 or 4 s in advance of a potential threat led drivers to travel significantly slower than the control group or the 2 s group. No significant effect of a HUD alert on drivers' speed was found when the latent hazard was a vehicle. An analysis of eye behaviors showed that only 7 out of 597 glances at the HUD were longer than 2 s safety-threshold, indicating that the warnings do not seem to distract the driver.