Translation of driver-pedestrian behavioral models at semi-controlled crosswalks into a quantitative framework for practical self-driving vehicle applications

A large number of crosswalks are indicated by pavement markings and signs but are not signal-controlled. Such a location is called “semi-controlled”. However, there is a sufficient amount of interaction between pedestrians and vehicles at “semi-controlled” crosswalks to be concerned about the time when “negotiations” between pedestrians and human drivers are replaced by interactions between pedestrians and self-driving vehicles. Although the behavior between pedestrians and drivers at a semi-controlled crosswalk is becoming better understood, but much efforts are still needed to translate behavioral models into a quantitative framework for practical self-driving vehicles applications. Moreover, if the appropriate sensor and control technology can lead to an optimal traffic control strategy from the perspectives of safety and efficiency, we will have achieved a form of “smart interaction” at crosswalks, which can be a useful element of smart mobility.

• Record URL:
  ccat.umtri.umich.edu

Language

• English

Project

• Status: Completed
• Funding: $150,000 ($75,000 CCAT, $75,000 InDOT)
• Contract Numbers:

  69A3551747105

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590

  Center for Connected and Automated Transportation

  University of Michigan Transportation Research Institute
  Ann Arbor, MI  United States  48109
• Managing Organizations:

  Center for Connected and Automated Transportation

  University of Michigan Transportation Research Institute
  Ann Arbor, MI  United States  48109

  University of Michigan Transportation Research Institute

  2901 Baxter Road
  Ann Arbor, Michigan  United States  48109
• Project Managers:

  Tucker-Thomas, Dawn

  Bezzina, Debra

• Performing Organizations:

  Purdue University, Lyles School of Civil Engineering

  550 Stadium Mall Drive
  West Lafayette, IN  United States  47907
• Principal Investigators:

  Fricker, Jon

• Start Date: 20210101
• Expected Completion Date: 20220930
• Actual Completion Date: 20231222
• USDOT Program: University Transportation Centers Program
• Subprogram: Research

Subject/Index Terms

• TRT Terms: Autonomous vehicle guidance; Congestion management systems; Connected vehicles; Human factors engineering; Policy; Traffic control; Vulnerable road users
• Subject Areas: Pedestrians and Bicyclists; Policy; Safety and Human Factors; Transportation (General); Vehicles and Equipment;

Filing Info

• Accession Number: 01768637
• Record Type: Research project
• Source Agency: Center for Connected and Automated Transportation
• Contract Numbers: 69A3551747105
• Files: UTC, RIP
• Created Date: Mar 26 2021 9:13PM