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2017, Volume 18, Issue 9

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Frontiers of Information Technology & Electronic Engineering >> 2017, Volume 18, Issue 9 doi: 10.1631/FITEE.1601427

Using improved particle swarm optimization totune PID controllers in cooperative collision avoidance systems

. College of Computer Science and Technology,Jilin University, Changchun 130012, China.. MOE Key Laboratory of Symbol Computationand Knowledge Engineering, Changchun 130012, China.. Department of Measurement and ControllingEngineering, Changchun University, Changchun 130012, China

Available online: 2018-01-18
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Abstract

The introduction of proportional-integral-derivative (PID) controllersinto cooperative collision avoidance systems (CCASs) has been hinderedby difficulties in their optimization and by a lack of study of theireffects on vehicle driving stability, comfort, and fuel economy. Inthis paper, we propose a method to optimize PID controllers usingan improved particle swarm optimization (PSO) algorithm, and to bettermanipulate cooperative collision avoidance with other vehicles. First,we use PRESCAN and MATLAB/Simulink to conduct a united simulation,which constructs a CCAS composed of a PID controller, maneuver strategyjudging modules, and a path planning module. Then we apply the improvedPSO algorithm to optimize the PID controller based on the dynamicvehicle data obtained. Finally, we perform a simulation test of performancebefore and after the optimization of the PID controller, in whichvehicles equipped with a CCAS undertake deceleration driving and steeringunder the two states of low speed (≤50 km/h) and high speed (≥100km/h) cruising. The results show that the PID controller optimizedusing the proposed method can achieve not only the basic functionsof a CCAS, but also improvements in vehicle dynamic stability, ridingcomfort, and fuel economy.

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