Title :
Multiple-vehicle longitudinal collision avoidance and impact mitigation by active brake control
Author :
Lu, Xiao-Yun ; Wang, Jianqiang
Author_Institution :
PATH, U.C. Berkeley, Richmond, CA, USA
Abstract :
This paper proposes a control strategy for multiple-vehicle longitudinal collision avoidance or impact minimization if it is unavoidable. The system is defined as a coupled group of vehicles with vehicle-to-vehicle communication (V2V) in short enough distance following. The relationships with the further front and/or rear vehicle without V2V has been taken into account, which are modeled as lower bound limit on deceleration of the first vehicle and upper bound on maximum deceleration of the last vehicle in the system. The objective is to determine the desired deceleration for each vehicle such that the total impact of the system is minimized at each time step. The impact is defined as the relative kinetic energy between a pair of vehicles. The optimal control problem is further simplified as a finite time horizon predictive control (MPC), which is a quadratic programming problem. Simulation in Matlab shows some interesting results. The algorithm can be applied to vehicles with automated brake control capabilities with progressive market penetration of V2V.
Keywords :
brakes; collision avoidance; impact testing; predictive control; quadratic programming; road safety; road traffic control; vehicle dynamics; MPC; Matlab simulation; V2V; active brake control; automated brake control; finite time horizon predictive control; impact minimization; impact mitigation; multiple-vehicle longitudinal collision avoidance; quadratic programming problem; relative kinetic energy; vehicle deceleration; vehicle-to-vehicle communication; Collision avoidance; Kinetic energy; Mathematical model; Predictive models; Trajectory; Vehicle crash testing; Vehicles;
Conference_Titel :
Intelligent Vehicles Symposium (IV), 2012 IEEE
Conference_Location :
Alcala de Henares
Print_ISBN :
978-1-4673-2119-8
DOI :
10.1109/IVS.2012.6232246