Ghraizi, Dany (Sorbonne universite, Universite de technologie de Compiegne, CNR), TALJ, Reine (Université de Technologie de Compiègne, Heudiasyc), Francis, Clovis (Arts et Métiers ParisTech)

Decision Making for Autonomous Vehicles Based on Risk Assessment in a Dynamic Environment

Scheduled for presentation during the Invited Session "Enhancing Trustworthiness and Resilience of Connected and Autonomous Vehicles in Adversarial Environments" (FrAT7), Friday, September 27, 2024, 12:10−12:30, Salon 15

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 October 8, 2024

Abstract

Recent advancements in autonomous driving technologies have significantly enhanced road safety and collision avoidance. However, ensuring this in dynamic driving environments remains a challenging endeavor. This paper addresses this challenge by proposing a high-level risk-aware decision-making module integrated into the trajectory planner of autonomous vehicles. The module establishes a function for dynamic risk assessment, considering both longitudinal and lateral aspects of the environment. By incorporating various factors such as velocity and relative position, the proposed function enables the vehicle to anticipate and respond to potential hazards proactively. Additionally, the paper incorporates and builds upon previous work of a modular and distinctive AI-based Adaptive Cruise Control (ACC) system with robust generalization capabilities. Results demonstrate the effectiveness of the proposed approach in improving safety, collision avoidance, and adaptability in highly interactive driving environments allowing the vehicle to dynamically re-plan trajectories and speed profiles during lane change maneuvers.