Emergency Collision Avoidance and Mitigation Using Model Predictive Control and Artificial Potential Function

TL;DR

This paper introduces a novel safe control method combining model predictive control and an innovative artificial potential function to improve collision avoidance and mitigation across diverse road environments, validated through extensive simulations.

Contribution

A new artificial potential function inspired by line charge is proposed, enabling flexible shape fitting and collision mitigation, integrated into a model predictive control framework for all-road scenarios.

Findings

20% higher success rate compared to HJ-reachability methods

Decreased collision occurrence by 43% at targeted vehicle parts

Effective in simulation across 8 diverse scenarios with different vehicle models

Abstract

Although extensive research in emergency collision avoidance has been carried out for straight or curved roads in a highway scenario, a general method that could be implemented for all road environments has not been thoroughly explored. Moreover, most current algorithms don't consider collision mitigation in an emergency. This functionality is essential since the problem may have no feasible solution. We propose a safe controller using model predictive control and artificial potential function to address these problems. A new artificial potential function inspired by line charge is proposed as the cost function for our model predictive controller. The vehicle dynamics and actuator limitations are set as constraints. The new artificial potential function considers the shape of all objects. In particular, the artificial potential function we proposed has the flexibility to fit the shape of the road structures, such as the intersection. We could also realize collision mitigation for a specific part of the vehicle by increasing the charge quantity at the corresponding place. We have tested our methods in 192 cases from 8 different scenarios in simulation with two different models. The simulation results show that the success rate of the proposed safe controller is 20% higher than using HJ-reachability with system decomposition by using a unicycle model. It could also decrease 43% of collision that happens at the pre-assigned part. The method is further validated in a dynamic bicycle model.