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

Accid Anal Prev. 2023 Aug:188:107092. doi: 10.1016/j.aap.2023.107092. Epub 2023 Apr 29.

Abstract

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.

Keywords: Autonomous vehicles; Future streets; Pedestrian safety; Street design; Urban and transportation planning; Virtual reality.

MeSH terms

  • Accidents, Traffic / prevention & control
  • Autonomous Vehicles
  • Humans
  • Pedestrians*
  • Safety
  • Virtual Reality*
  • Walking