Autonomous vehicles and street design: Exploring the role of medians in enhancing pedestrian street crossing safety using a virtual reality experiment

As traffic lanes and on-street parking spots can potentially be downsized with the introduction of autonomous vehicles (AVs), the possibility of additional spare road space becoming available arises in future urban streets. While discussions on converting the leftover space into pedestrian-friendly alternatives exist, allocating that limited space to which alternative is foreseen to be another practical issue shared in both urban and transportation planning. However, evidence-based guidance on the issue provided from the actual verification on whether or to what extent the proposed alternatives may have an effect seems to be absent. Therefore, with an emphasis on pedestrian safety, this study focused on the "median strip" alternative as a first example and, through a VR simulation experiment aimed at empirically examining its suggested role on enhancing street crossing safety and further exploring its possible influence on pedestrians' trust toward autonomous driving. With 99 participants, perceived safety (individual assessments of safety), performance-based safety (crossing success/abandonment and collision occurrence), and trust were either questioned or recorded for nine scenarios with varying crossing conditions. A combination of multilevel models and cross-tabulation results indicate that medians seem especially significant in ensuring the performance-based safety results of pedestrians even when AVs are driving at high speeds or with smaller gaps, thus suggesting it a win-win option for both. Insights and implications on the role and management of medians in future streets are further provided.

A least action principle for interceptive walking

The principle of least effort has been widely used to explain phenomena related to human behavior ranging from topics in language to those in social systems. It has precedence in the principle of least action from the Lagrangian formulation of classical mechanics. In this study, we present a model for interceptive human walking based on the least action principle. Taking inspiration from Lagrangian mechanics, a Lagrangian is defined as effort minus security, with two different specific mathematical forms. The resulting Euler–Lagrange equations are then solved to obtain the equations of motion. The model is validated using experimental data from a virtual reality crossing simulation with human participants. We thus conclude that the least action principle provides a useful tool in the study of interceptive walking.

Behavioral Dynamics of Pedestrians Crossing between Two Moving Vehicles

This study examines the human behavioral dynamics of pedestrians crossing a street with vehicular traffic. To this end, an experiment was constructed in which human participants cross a road between two moving vehicles in a virtual reality setting. A mathematical model is developed in which the position is given by a simple function. The model is used to extract information on each crossing by performing root-mean-square deviation (RMSD) minimization of the function from the data. By isolating the parameter adjusted to gap features, we find that the subjects primarily changed the timing of the acceleration to adjust to changing gap conditions, rather than walking speed or duration of acceleration. Moreover, this parameter was also adjusted to the vehicle speed and vehicle type, even when the gap size and timing were not changed. The model is found to provide a description of gap affordance via a simple inequality of the fitting parameters. In addition, the model turns out to predict a constant bearing angle with the crossing point, which is also observed in the data. We thus conclude that our model provides a mathematical tool useful for modeling crossing behaviors and probing existing models. It may also provide insight into the source of traffic accidents.

Age-related differences in the perception of gap affordances: Impact of standardized action capabilities on road-crossing judgements

Recent road-crossing literature has found that older adults show performance differences between estimation and perception-action tasks suggesting an age-related difficulty in accurately calibrating the information picked up from the surrounding environment to their action capabilities (Lobjois and Cavallo, 2009). The present study investigated whether participants could accurately perceive gap affordances via information that specifies the time-to-arrival of the approaching cars. To ensure the opportunities for action were the same across different age groups, independent of the actor's action capabilities, the action of crossing the road was standardised. A total of 45 participants (15 children, aged 10-12, 15 adults aged 19-39, 15 older adults aged 65+) were asked to judge, by pressing a button in a head-mounted display, whether the gap between oncoming cars afforded crossing. When the participant pressed the button, they moved across the road at a fixed speed. Adherence to a time-based variable (namely tau) explained 85% and 84% of the variance in both the children and adults' choices, respectively. Older adults tuned less into the time-based variable (tau) with it only accounting for 59% of the variance in road-crossing decisions. These findings suggest that, the ability to use tau information which specifies whether a gap affords crossing or not, deteriorates with age.