Zhang, Chuancheng (Shandong University at Weihai), Wang, Zhenhao (Shandong University), Lv, Chenyang (ShanDong University), Cui, Yanhao (ShanDong University), Jiang, Bin (Shandong University), Guo, Qiang (Shandong University of Finance and Economics)

Integrating Social Value Orientation and Motion Safety Controller in Autonomous Driving: Improving the Safety of Unprotected Left-Turn Behaviour

Scheduled for presentation during the Invited Session "Safety for Intelligent and Connected Vehicles" (ThBT3), Thursday, September 26, 2024, 15:50−16:10, Salon 6

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

With the advent of autonomous driving, the seamless integration of autonomous vehicles (AVs) with human-driven vehicles (HDVs) poses significant challenges. Particularly, at unsignalized intersections lacking explicit coordination, safely predicting and accommodating the unprotected left-turn behaviors of drivers with varying preferences is challenging. This study introduces a novel framework that integrates Social Value Orientation (SVO) with Deep Reinforcement Learning (DRL) and a Motion Safety Controller (MSC), targeting the enhancement of AVs safety and efficiency in these complex scenarios. Integrating the SVO into the DRL reward function encourages socially considerate behaviors among AVs to minimize potential incidents. Equipped with a track supervisor and a motion controller, the MSC assists in foreseeing and mitigating hazards, thus enhancing road safety. Our study trains, evaluates, and validates the efficacy of our proposed method on a gym-like highway simulator. The method surpasses existing state-of-the-art (SOTA) baseline models in reducing collision rates and improving vehicular behavior. This study represents a significant advancement in autonomous driving, addressing complex unprotected left turns at intersections and aligning technological innovations with the societal need for safer roads.