Are Automated Vehicles Safer Drivers than Humans? Comparing performance in San Francisco

Project Description

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.