Analysis of Bicyclist Communication in a Simulator Environment

Urban roads are a dynamic environment in which formal and informal communication are crucial. In order for autonomous vehicles to operate effectively in such an environment, they must be able to deal with this complexity. In particular, an understanding of the communication patterns of bicyclists is crucial because of their vulnerability and lack of standardized indicators, which allows greater variability and subtlety in the way they communicate. In this study, participants rode a bicycle simulator through various urban traffic scenarios in which explicit and implicit communication behaviors are expected. Participants were recorded with a depth camera, and a markerless motion capture technique was used to record their movements in three dimensions. From this data, hand signal, head movement, and leaning events were extracted, analyzed, and compared. Analyses showed that even in clearly regulated scenarios, not all participants performed a hand signal, with between 80 and 95 percent of participants signaling before turning at a four-way intersection and approximately 60 percent before changing lanes. Participants were also significantly more likely to glance over their left shoulder preceding a left lane-change or left turn compared to other scenarios. The arm shape while performing a hand signal was found to be almost entirely governed by individual preference, rather than scenario. Based on these results, it is clear that cyclist communication behavior frequently does not adhere strictly to traffic regulations and varies from person to person. However, implicit cues such as head movements can be used to supplement behavior prediction models in certain situations.

• Record URL:
  https://annualmeeting.mytrb.org/OnlineProgram/Details/15711
• Supplemental Notes:
  • This paper was sponsored by TRB committee ACH50 Standing Committee on Road User Measurement and Evaluation.
• Corporate Authors:

  Transportation Research Board

  ,    
• Authors:
  • Malcolm, Patrick
  • Grigoropoulos, Georgios
  • Keler, Andreas
  • Kaths, Heather
  • Bogenberger, Klaus
• Conference:
  • Transportation Research Board 100th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2021-1-5 to 2021-1-29
• Date: 2021

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Photos; References; Tables;
• Pagination: 14p

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Behavior; Bicycles; Hand signaling; Machine learning; Traffic safety; Urban highways
• Subject Areas: Highways; Pedestrians and Bicyclists; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01764187
• Record Type: Publication
• Report/Paper Numbers: TRBAM-21-00050
• Files: TRIS, TRB, ATRI
• Created Date: Feb 4 2021 11:00AM