Del Re, Enrico (Johannes Kepler Universität Linz), Aghanouri, Amirhesam (Johannes Kepler Universität Linz), Olaverri-Monreal, Cristina (Johannes Kepler University Linz, Austria)

Integrating Naturalistic Insights in Objective Multi-Vehicle Safety Framework

Scheduled for presentation during the Regular Session "Advanced Vehicle Safety Systems I" (WeBT8), Wednesday, September 25, 2024, 16:10−16:30, Salon 16

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on December 26, 2024

Abstract

As autonomous vehicle technology advances, the precise assessment of safety in complex traffic scenarios becomes crucial, especially in mixed-vehicle environments where human perception of safety must be taken into account. This paper presents a framework designed for assessing traffic safety in multi-vehicle situations, facilitating the simultaneous utilization of diverse objective safety metrics. Additionally, it allows the integration of subjective perception of safety by adjusting model parameters. The framework was applied to evaluate various model configurations in car-following scenarios on a highway, utilizing naturalistic driving datasets. The evaluation of the model showed an outstanding performance, particularly when integrating multiple objective safety measures. Furthermore, the performance was significantly enhanced when considering all surrounding vehicles.