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https://www.nationalacademies.org/trb/events

Evaluating Autonomous Vehicles’ Pedestrian Safety Benefits in Road Networks

Pennsylvania experienced more than 3000 pedestrian-related injuries in 2022, according to PennDOT, and the Governor’s Highway Safety Association estimates that Pennsylvania ranked 10th among all 50 states in 2022 for the most pedestrian fatalities. This project will explore and evaluate the potential for connected autonomous vehicles (CAVs) to reduce these pedestrian-involved incidents. While many past works have explored using CAV capabilities to detect and avoid pedestrians, the research team will specifically focus on ensuring that these benefits are felt where and when they are most needed. Recent studies show that pedestrian fatalities in the United States are especially common at night and on roads that do not have infrastructure designed to support pedestrians. By increasing the concentration of CAVs, which may be safer for pedestrians, on such dangerous roadways, the team may be able to increase overall pedestrian safety. Many pedestrian-related incidents, for example, involve human driver distraction, and CAVs can make use of non-visual (e.g., radar) environmental data to detect pedestrians, especially at night. However, CAVs may also be more dangerous for pedestrians if their detection systems fail. Moreover, intentionally diverting CAVs to areas that are dangerous for pedestrians may have implications for safety and traffic flow through the road network as a whole. For example, proactively routing CAVs to these areas may create more traffic congestion and potentially increase accidents involving vehicles, leading human-driven vehicles to avoid this area. Indeed, CAVs will likely be deployed initially in mixed-autonomy settings with human-driven vehicles, which adds an additional layer of complexity in analyzing how pedestrians will affect safety or traffic flow. The team plans to build on their 2023-4 Safety21 project investigating CAVs’ safety effects in road networks. In particular, the team will make use of their mixed autonomy simulator from the previous project, which includes models of vehicle-involved accidents but does not explicitly seek to improve pedestrian safety. The work will comprise four parts: (i) integrating pedestrian fatality and injury statistics into the mixed autonomy simulator, (ii) developing analytical models for traffic flow and pedestrian injuries/fatalities given CAV routing, (iii) designing algorithms for CAVs to minimize pedestrian fatalities and injuries, and (iv) using the simulator and the analytical models to evaluate whether CAVs can effectively reduce pedestrian injuries and fatalities, as well as any tradeoffs with increasing traffic congestion.

Language

  • English

Project

  • Status: Completed
  • Funding: $180,000.00
  • Contract Numbers:

    69A3552344811

    69A3552348316

  • 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:

    Safety21 University Transportation Center

    Carnegie Mellon University
    Pittsburgh, PA  United States  15213

    Carnegie Mellon University

    Pittsburgh, PA  United States 
  • Performing Organizations:

    Carnegie Mellon University

    Pittsburgh, PA  United States 
  • Principal Investigators:

    Joe-Wong, Carlee

    Yagan, Osman

  • Start Date: 20250701
  • Expected Completion Date: 20260831
  • Actual Completion Date: 20260831
  • USDOT Program: University Transportation Centers

Subject/Index Terms

Filing Info

  • Accession Number: 02002860
  • Record Type: Research project
  • Source Agency: Safety21 University Transportation Center
  • Contract Numbers: 69A3552344811, 69A3552348316
  • Files: UTC, RIP
  • Created Date: Sep 17 2026 5:12PM