Elayan, Mohammad (University of Nebraska - Lincoln), Kontar, Wissam (University of Nebraska-Lincoln)

Consensus-Aware AV Behavior: Trade-Offs between Safety, Interaction, and Performance in Mixed Urban Traffic

Scheduled for presentation during the Regular Session "S12b-Safety and Risk Assessment for Autonomous Driving Systems" (WE-EA-T12), Wednesday, November 19, 2025, 14:50−15:30, Broadbeach 3

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 19, 2025

Abstract

Transportation systems have long been shaped by complexity and heterogeneity, driven by the interdependency of agent actions and traffic outcomes. The deployment of automated vehicles (AVs) in such systems introduces a new challenge: achieving consensus across safety, interaction quality, and traffic performance. In this work, we position consensus as a fundamental property of the traffic system and aim to quantify it. We use high-resolution trajectory data from the Third Generation Simulation (TGSIM) dataset to empirically analyze AV and human-driven vehicle (HDV) behavior at a signalized urban intersection and around vulnerable road users (VRUs). Key metrics, including Time-to-Collision (TTC), Post-Encroachment Time (PET), deceleration patterns, headways, and string stability, are evaluated across the three performance dimensions. Results show that full consensus across safety, interaction, and performance is rare, with only 1.66% of AV-VRU interaction frames meeting all three conditions. These findings highlight the need for AV models that explicitly balance multi-dimensional performance in mixed-traffic environments.

Full reproducibility is supported via our open-source codebase on Github page: https://github.com/wissamkontar/Consensus-AV-Analysis