Examining the Relationships between Multimodal Environments and Multitasking Driving Behaviors

Tianqi Zou, Huizhong Guo, Moein Khaloei, Don Mackenzie, Linda Ng Boyle

Research output: Chapter in Book/Report/Conference proceedingChapter


This study examined multitasking behaviors of drivers in environments that include large numbers of pedestrians and cyclists, using video and vehicle data from the second Strategic Highway Research Program (SHRP2). The study includes 15 sites in both Seattle, WA, and Tampa, FL, U.S., (nine pedestrian and six cyclist locations), including three marking and signal types for crosswalks and two types for bike treatments. A total of 1,458 SHRP2 traversals with time-series data and forward videos were extracted with face/dash videos for about 50% of these traversals. Forward video coding was conducted for all daytime traversals starting from one block before to one block after the selected site. Face/dash video was coded for all traversals with pedestrians or cyclists. A matched set of traversals without pedestrians or cyclists were also coded. The final data set included 458 traversals with coded data on multitasking behavior and the multimodal environment. Mixed-effect binary logistic regression models were used to examine the associations of pedestrian/cyclist presence and the facility type with drivers’ multitasking behavior. The findings show that the presence of pedestrians/cyclists and facility types could be related to driv-ers’ multitasking behavior. The findings can provide the foundation for future studies that examine safety for non-motorists with respect to infrastructure design, signage, and policies. There is also the potential to provide insights into assistive driving systems within automated vehicles, which are discussed in this paper.

Original languageEnglish (US)
Title of host publicationTransportation Research Record
PublisherSAGE Publications Ltd
Number of pages14
StatePublished - Feb 2023


  • bicycles
  • distraction
  • driver behavior
  • human factors
  • naturalistic data studies
  • pedestrians

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Mechanical Engineering


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