Research on Collision Avoidance Systems for Intelligent Vehicles Considering Driver Collision Avoidance Behaviour

Abstract

In this paper, a new collision avoidance switching system is proposed to address the lack of adaptability of intelligent vehicles under different collision avoidance operating conditions. To ensure the rationality of the collision avoidance switching strategy for intelligent vehicles, the NGSIM road dataset is introduced to analyse the driver’s collision avoidance behaviour, and a two-layer fuzzy controller considering the overlap rate is established to design the collision avoidance switching strategy. In order to achieve real-time collision avoidance system activation, a lane change collision avoidance model based on MPC control is also developed. Finally, a simulation environment was created using Matlab/CarSim for simulation verification. The simulation results show that the collision avoidance switching system is more responsive and has a shorter start-up distance and is more adaptable to different driving conditions.

Personalized Collision Avoidance Control for Intelligent Vehicles Based on Driving Characteristics

“…Meanwhile, driver and IV will exist simultaneously in the long future. The driving characteristics (DC) of different individuals are an essential factor that affects the performance of collision avoidance controllers (CAC) [5]. For this reason, the DC is becoming a mainly considered aspect of CAC design.…”