Work

Multi-Vehicle Collision Avoidance by Vehicle Longitudinal Control Based on Optimal Collision Distance Estimation

Year: 2025

Type: article

Abstract: This paper proposes a collision avoidance method for vehicle longitudinal velocity control based on multi-vehicle collision distance estimation. The method begins by estimating the position and shape of object vehicles with collision risk using environmental sensors. The collision point is identified from the object vehicle’s surface, and a Kalman filter is applied for accurate estimation. The optimal collision distance is then determined by evaluating the collision risk at the identified point. A longitudinal control technique, incorporating the optimal collision distance and time gap, is employed to implement the collision avoidance system. The proposed method was validated through scenario-based simulations involving multi-vehicle collision avoidance, which were implemented in an environment combining ROS and the MORAI simulator, along with comparative experiments. Comparative studies with conventional vehicle center-based approaches demonstrated that the proposed surface-based collision point method significantly enhances collision avoidance performance. While the conventional method led to a collision between the ego and object vehicles, the proposed method successfully avoided the collision by maintaining a separation of about 3.6 m, demonstrating its feasibility and reliability.

Source: Mathematics

DOI: 10.3390/math13081283

Authors: Joon Ho Lee, Youngok Lee, Young Seop Son, Woo Young Choi

Institutions: Pukyong National University, Daelim University College, Kyungpook National University

Language: English

Topic: Autonomous Vehicle Technology and Safety

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $3,137

Funders: National Research Foundation of Korea, Ministry of SMEs and Startups