Predicting pedestrians’ intention to cross the road in front of automated vehicles in risky situations

Due to the absence of a human driver, the introduction of fully automated vehicles (FAVs) may bring new safety challenges to the traffic system, especially when FAVs interact with vulnerable road users such as pedestrians. To ensure safer interactions between pedestrians and FAVs, this questionnaire-based study aims to understand Australian pedestrians’ intention to engage in risky road-crossing behaviors when they interact with FAVs vs. human-driven vehicles (HDVs). A 2 × 2 between-subject design was utilized, in which two risky road-crossing scenarios were designed and took into account the vehicle type (FAV vs. HDV) and vehicle speed (30 km/h vs. 50 km/h). A total of 493 participants (aged 18–77) were randomly assigned to one of the four experimental conditions and completed an online questionnaire based on the extended Theory of Planned Behavior (TPB). This questionnaire measured pedestrians’ intentions to cross the road in the assigned scenarios as well as the motivational factors behind these intentions in terms of attitude, subjective norm, perceived behavioral control, perceived risk and trust in the vehicle. The results show that pedestrians had significantly higher intentions to cross the road in front of approaching FAVs than HDVs. Participants also reported a lower risk perception of crossing in front of FAVs and greater trust in this type of vehicle. Attitude, subjective norm, and perceived behavioral control were significant predictors of intentions to engage in risky road-crossing behavior. Findings of this study provide important implications for the development and implementation of FAVs in the future road transport system.

• Record URL:
  https://doi.org/10.1016/j.trf.2022.05.022
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S1369847822001176
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13698478
• Supplemental Notes:
  • © 2022 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Zhao, Xiaoyuan
  • Li, Xiaomeng
  • Rakotonirainy, Andry
  • Bourgeois- Bougrine, Samira
  • Delhomme, Patricia
• Publication Date: 2022-10

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 524-536
• Serial:
  • Transportation Research Part F: Traffic Psychology and Behaviour
  • Volume: 90
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1369-8478
  • Serial URL: http://www.sciencedirect.com/science/journal/13698478

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Behavior; Pedestrian movement; Pedestrian vehicle interface; Risk taking
• Geographic Terms: Australia
• Subject Areas: Highways; Pedestrians and Bicyclists; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01849910
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 27 2022 5:12PM