Optimized Active Collision Avoidance Algorithm of Intelligent Vehicles

Abstract

This research introduces an innovative strategy to impede and lessen lateral and rear-end vehicular collisions by consolidating braking systems with active emergency steering controls. This study puts forward a T-type active emergency steering method, designed to circumvent both lateral and rear-end collisions at vehicular intersections. To secure vehicular stability and condense the time required for steering during the T-type active emergency process, this research formulates a nonlinear dynamic model for the vehicle, in addition to a nonlinear tire model. This study also engages in a thorough analysis of the constraints linked to the initial and terminal states of the steering process. The issue at hand is articulated as an optimization control problem with boundary value restrictions, which is subsequently resolved using the Radau pseudospectral method. Simulation results corroborate that the prompt commencement of the anti-collision strategy can effectively deter potential collisions. This pioneering approach shows considerable promise in augmenting the active safety of intelligent vehicles and bears meaningful implications for high-precision automotive collision evasion systems.

Control Architecture for Connected Vehicle Platoons: From Sensor Data to Controller Design Using Vehicle-to-Everything Communication

“…In the last two cases, the use of vehicle communication can improve performances due to the fact that the follower is not using only measurements from its own sensors, but also information received from its neighbour vehicles. The most used approaches for lateral control are based on the MPC strategy [69][70][71], LQR algorithm [72,73], adaptive control [74], and optimal control [75]. The lateral control of the leader involves steering the vehicle according to the trajectory from the planning subsystem.…”