Research On Dedicated Short Range Communication And Auxiliary Control Under Automobile Cooperative Driving

In addition to convenient transportation,the automobile also brings such problems as road congestion,traffic accident and energy waste.The automobile cooperative driving system can achieve real-time dynamic information interaction between adjacent vehicles so as to provide real-time and accurate control over the vehicle driving status,improve the stability and safety of vehicle driving and transportation efficiency and effectively solve above problems.The keys for effectively operating the vehicle cooperative driving system are to satisfy demands for accuracy and low delay of information interaction in the vehicles and surrounding traffic environment and to provide accurate,real-time and stable control over the vehicle driving status by the vehicle control layer.This paper,focusing on filtering delay compensation of dedicated short range communication(DSRC)system,error rate optimization of wireless access vehicular environment(WAVE)system and control performance optimization of cooperative adaptive cruise control(CACC)system and cooperative collision avoidance(CCA)system,researches the demands for communication quality of the dedicated short range communication system and performance of the auxiliary control system through theoretical analysis,modeling and system simulation.The main contributions of this paper include:(1)With regard to communication signal distortion of the DSRC system under electromagnetic interference,this paper proposes a modified normalized least mean square(NLMS)based adaptive filtering method.With regard to the delay in signal filtering and transmission of the DSRC system,this paper proposes a delay compensation method where the transmission delay of the DSRC system and unit delay operator of the self-adaptive FIR filter are introduced so as to reduce the error caused by system delay.This paper tests the above method under simulated CACC typical working conditions.The test results show that the above method can be applied to effectively reduce data errors caused by system delay,in addition to effective filtering of signal noise of the DSRC system.(2)With regard to high error rate in radio frequency signal of the WAVE system caused by directional equivalence and multipath transmission factor,this paper proposes a method based on space diversity gain characteristics of multi-user multiple-input multiple-output(MU-MIMO)beamforming technology to reduce the system error rate.This paper builds a beamforming matrix of the WAVE system based on the block diagonalization(BD)precoding algorithm,and applies the singular value decomposition(SVD)algorithm and minimum mean square error(MMSE)testing technology into the solution matrix of the beamforming matrix.Simulation results show that the above method can be used to effectively reduce the system error rate.(3)With regard to poor system control performance caused by unsatisfactory parameter setting of the PID controller of the currently introduced CACC system control layer,this paper proposes a modified chaotic ant swarm(CAS)algorism based PID controller parameter setting method.The pheromone concentration factor is utilized so as to improve the convergence speed of the CAS algorism.The modified algorism is applied to set PID controller parameters and improve control performance of the CACC system.This paper tests the above method under simulated CACC typical working conditions.The test results show that the CACC system control layer optimized by the above method can shorten the minimum safety distance,improve the driving stability,comfort and fuel efficiency of the vehicle under the premise of guaranteeing safe driving of multiple fleets.(4)With regard to poor collision avoidance stability and comfort caused by unsatisfactory PID controller parameter setting of the currently introduced CCA system control layer,this paper proposes a particle swarm optimization(PSO)algorism based PID controller parameter setting method.Starting from enriching the diversity of particle swarm and avoiding local algorism optimization,this paper aims to improve the comprehensive performance the PSO algorism.The test results show that the collision avoidance stability and comfort of the CCA system can be improved by the above method.