Examining Drivers’ Behaviors to Connected and Automated Vehicles

It is envisioned that Connected and Autonomous Vehicles (CAVs) are the future of transportation as they will assist in minimizing some inefficiencies of current transport systems. Autonomous vehicles (AVs) and CAVs are currently being developed in both commercial and research projects across the world and are expected to be publicly available soon. CAVs are expected to provide more accessible mobility options for all road users, especially older adults’, and people with disabilities. It might be also a safe mobility option during the period of pandemic (e.g., COVID 19). However, it is not clear how drivers of conventional vehicles would interact with other CAVS in such a mix traffic environment especially at complex traffic areas (e.g., merging, and diverging areas). Indeed, it is expected that a mixed traffic network (including both CAVs and human-driven vehicles) would impose additional challenges to drivers (especially to older road users), which are necessary to be studied and remedied. Not only does studying the actual drivers’ behaviors to other CAVs affect the safety of all road users, but also plays a significant role in acceptance and propagation of CAVs. In this regard, little is known about the acceptance of CAVs among different socio-demographic groups of drivers. Therefore, it is imperative to study the aforesaid issues before CAVs being publically available to facilitate paving the success road for the CAVs. This study strives to address the aforesaid issues by addressing the following three objectives: (1) Examine how drivers will interact with other CAVs under different traffic and environmental conditions. To achieve this goal, different driving simulator scenarios will be designed and developed using LSU driving simulator. These scenarios will include examining the most challenging driving maneuvers and conditions (e.g., on-ramp and off-ramp merging/diverging in the presence of CAVs). (2) Investigate drivers’ behaviors to different levels of vehicular automation (semi and fully levels of vehicular automation). For example, using several cameras inside the driving simulator, drivers’ behaviors to possible cases of vehicular automation failure will be examined. (3) Explore the changes in the willingness and preferences of road users toward CAVs before and after participating in the driving simulator experiments. A before and after questionnaire study will be designed to identify the extent to which familiarizing the population with CAVs would affect their acceptance and willingness toward using CAVs. It is expected that this study will provide valuable insights about the actual driving behaviors and challenges of drivers in the most critical driving conditions in a mixed traffic environment containing both CAVs and other human driven vehicles. The identification of these challenges will allow also to identify effective countermeasures to improve the safety of all road users and the most vulnerable ones (i.e., older adults). The results of this study would also shed light on whether public acceptance of CAVs, especially in older population, would be affected by training, publicizing, and educational programs. Finally, this research will result in improving the knowledge of young researchers in this important area of research as a graduate student at Louisiana state University will perform his/her master or Ph.D. thesis in the same topic of this research proposal.

• Supplemental Notes:
  • 21ITSLSU16

Language

• English

Project

• Status: Active
• Funding: $75279
• Contract Numbers:

  69A3551747106

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Transportation Consortium of South-Central States (Tran-SET)

  Louisiana State University
  Baton Rouge, LA  United States  70803
• Project Managers:

  Mousa, Momen

• Performing Organizations:

  Louisiana State University, Baton Rouge

  P.O. Box 94245, Capitol Station
  Baton Rouge, LA  United States  70803
• Principal Investigators:

  Hassan, Hany

• Start Date: 20210801
• Expected Completion Date: 20230201
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Before and after studies; Behavior; Connected vehicles; Drivers; Driving simulators; Traffic safety
• Subject Areas: Highways; Planning and Forecasting; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01832348
• Record Type: Research project
• Source Agency: Transportation Consortium of South-Central States (Tran-SET)
• Contract Numbers: 69A3551747106
• Files: UTC, RIP
• Created Date: Jan 10 2022 2:40PM