Are Automonous Vehicles Safer Drivers than Humans? Comparing performance in San Francisco
This research project seeks to determine if automated vehicles (AVs) are safer drivers than humans by comparing their pedestrian interaction behaviors and yielding performance in real-world conditions in San Francisco. The study will be framed by the city's "Focus on Five" strategy, which targets the five moving violations most commonly associated with traffic fatalities. Researchers will conduct evaluations of two focus violations, with the first being a comparison of the compliance of AVs and human drivers in yielding to pedestrians in a crosswalk. To gather data, the team will install high-resolution video cameras at two or more crosswalks with no traffic control for a period of one to three weeks to passively record vehicle-pedestrian interactions. Machine learning-based computer vision methods will then be used to automatically classify vehicles as either automated or human-driven. Following this classification, researchers will review the footage to code each interaction, noting if the vehicle yielded to the pedestrian. Finally, the performance of the two groups will be compared using two-sample t-tests to determine if any observed differences are statistically significant. A parallel analysis will be conducted for a second violation, to be determined.
- Record URL:
Language
- English
Project
- Status: Active
- Funding: $107643.00
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Contract Numbers:
69A3552348336
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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:
Office of the Assistant Secretary for Research and Technology
Department of Transportation
1200 New Jersey Avenue, SE
Washington, DC United States 20590 -
Project Managers:
Stearns, Amy
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Performing Organizations:
University of California, Berkeley
Safe Transportation Research and Education Center
Berkeley, CA United States 94720 -
Principal Investigators:
Griswold, Julia
- Start Date: 20251201
- Expected Completion Date: 20261130
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers
Subject/Index Terms
- TRT Terms: Automatic vehicle classification; Autonomous vehicles; Computer vision; Crosswalks; Driving behavior; Pedestrian safety; Pedestrian vehicle interface
- Geographic Terms: San Francisco (California)
- Subject Areas: Operations and Traffic Management; Pedestrians and Bicyclists; Safety and Human Factors; Vehicles and Equipment;
Filing Info
- Accession Number: 01971696
- Record Type: Research project
- Source Agency: Center for Pedestrian and Bicyclist Safety
- Contract Numbers: 69A3552348336
- Files: UTC, RIP
- Created Date: Nov 18 2025 3:14PM