A Design of Cooperative Overtaking Based on Complex Lane Detection and Collision Risk Estimation

TL;DR

This paper presents a cooperative overtaking system that uses complex lane detection and collision risk estimation to improve safety and efficiency through real-time vehicle communication and environment modeling.

Contribution

It introduces a novel lane detection and collision risk estimation framework that enhances cooperative overtaking safety and performance in diverse road conditions.

Findings

The proposed method improves overtaking safety in unpredictable road scenarios.

Lane detection accuracy is enhanced using Bezier curve modeling.

Collision risk estimation effectively prevents potential accidents.

Abstract

Cooperative overtaking is believed to have the capability of improving road safety and traffic efficiency by means of the real-time information exchange between traffic participants, including road infrastructures, nearby vehicles and others. In this paper, we focused on the critical issues of modeling, computation, and analysis of cooperative overtaking and made it playing a key role in the road overtaking area. In detail, for the purpose of extending the awareness of the surrounding environment, the lane markings in front of ego vehicle were detected and modeled with Bezier curve using an onboard camera. While the nearby vehicle positions were obtained through the vehicle-to-vehicle communication scheme making assure of the accuracy of localization. Then, Gaussian-based conflict potential field was proposed to guarantee the overtaking safety, which can quantitatively estimate the oncoming collision danger. To support the proposed method, many experiments were conducted on the human-in-the-loop simulation platform. The results demonstrated that our proposed method achieves better performance, especially in some unpredictable nature road circumstances.