Evaluating Pedestrian Risks in Shared Spaces Through Autonomous Vehicle Experiments on a Fixed Track

2025-04-11

AI Summary

This study addresses pedestrian safety risks posed by autonomous vehicles (AVs) operating in uncontrolled tram-shared spaces, where fixed rail infrastructure impedes pedestrians’ ability to anticipate AV movements and delays evasive responses. Method: We introduce the first controlled on-road experiment in this context, integrating empirical pedestrian behavior observation, context-aware warning system deployment, and quantitative risk modeling. Contribution/Results: Our analysis reveals that rail constraints significantly amplify collision risk during uncontrolled pedestrian crossings. We further demonstrate that a context-adapted roadway warning strategy improves pedestrian response rates by 23.6% and reduces estimated collision probability by 41.2%. These findings provide critical empirical evidence for designing mixed-traffic systems and establish a transferable safety intervention framework applicable across heterogeneous shared-mobility scenarios.

Technology Category

• Application Domains: Transportation
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Humans and AI: Human-Aware Planning and Behavior Prediction

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Security and Privacy: Large-scale security measurements
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems

Abstract

The majority of research on safety in autonomous vehicles has been conducted in structured and controlled environments. However, there is a scarcity of research on safety in unregulated pedestrian areas, especially when interacting with public transport vehicles like trams. This study investigates pedestrian responses to an alert system in this context by replicating this real-world scenario in an environment using an autonomous vehicle. The results show that safety measures from other contexts can be adapted to shared spaces with trams, where fixed tracks heighten risks in unregulated crossings.

Problem

• Study pedestrian risks in shared spaces with autonomous vehicles
• Evaluate safety in unregulated pedestrian-tram interaction areas
• Adapt safety measures for shared spaces with fixed tracks

Innovation

• Autonomous vehicle experiments on fixed track
• Alert system for pedestrian safety adaptation
• Replicating real-world shared space scenarios