Will automated vehicles encourage more jaywalking? Results from a stated preference survey

When interacting with driverless cars, pedestrians might be emboldened to jaywalk knowing the vehicles will slow down for them automatically. Increased jaywalking might disrupt traffic flow and pose challenges for traffic law enforcement. Few studies examined pedestrians’ attitudes toward driverless cars’ safety implication, management strategies for the interactions between pedestrians and driverless cars, and how pedestrians would expect their street crossing behavior to change in the presence of driverless cars. The authors conducted an online stated preference survey of 1,000 residents in the Philadelphia and the Seattle metropolitan areas to investigate respondents’ attitudes toward driverless cars and their preferences of jaywalking under different driverless car saturation levels. Through descriptive data analysis and multilevel binomial logit analysis, the authors found that overall pedestrians felt less safe with driverless cars on the road. Pedestrians preferred limiting the speeds of driverless cars or disabling driverless functions in areas with heavy pedestrian traffic to increasing enforcement for jaywalking laws. Multilevel binomial logit analysis showed pedestrians were more likely to jaywalk in the presence of driverless cars in high visibility and low traffic volume, and were deterred by bigger, faster streets. Respondents’ current crossing behavior might serve as an indicator of their crossing behavior in the presence of driverless cars. The findings remind cities that sound street design strategies could help to ensure safer interactions between pedestrians and driverless cars and greater acceptance of driverless cars on urban streets.

• Record URL:
  https://doi.org/10.1016/j.trf.2024.04.011
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S1369847824000858
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13698478
• Supplemental Notes:
  • © 2024 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Dong, Xiaoxia
  • 0000-0002-3907-3237
  • Guerra, Erick
  • Daziano, Ricardo A
• Publication Date: 2024-5

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 217-229
• Serial:
  • Transportation Research Part F: Traffic Psychology and Behaviour
  • Volume: 103
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1369-8478
  • Serial URL: http://www.sciencedirect.com/science/journal/13698478

Subject/Index Terms

• TRT Terms: Attitudes; Autonomous vehicles; Midblock crossings; Pedestrian movement; Traffic safety
• Geographic Terms: Philadelphia (Pennsylvania); Seattle (Washington)
• Subject Areas: Highways; Pedestrians and Bicyclists; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01917827
• Record Type: Publication
• Files: TRIS
• Created Date: May 9 2024 9:24AM