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

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.

Keywords

Cooperative collision avoidance system (CCAS) / Improved particle swarm optimization (PSO) / PID controller / Vehicle comfort / Fuel economy

References

[1] CAN NewsletterOnline, 2014. Emergency SteeringAssist.http://can-newsletter.org/engineering/engineering-miscellaneous/140813_emergency-steering-assist

[2] Chen , L.W., Chou , P.C., 2013. A lane-level cooperative collision avoidance system basedon vehicular sensor networks. 19th AnnualInt. Conf. on Mobile Computing & Networking,p.131-134. https://doi.org/10.1145/2500423.2505293

[3] Cho , H., Kim , B., 2014. Cooperative intersection collisionwarning system basedon vehicle-to-vehicle communication. Contemp. Eng. Sci., 7(22):1147-1154. https://doi.org/10.12988/ces.2014.49143

[4] Feng , Y.Q., Ji , H.Q., Liu , Z.S., 2012. Parametersetting and simulation of the PID controller for vehicle spacing controlsystem. China Sci.Technol. Inform., 2012(8):141-143 (in Chinese).

[5] Huang , C.M., Lin , S.Y., 2014. Cooperative vehicle collision warning system using thevector-based approach with dedicated short range communication datatransmission. IETIntell. Transp. Syst., 8(2):124-134. https://doi.org/10.1049/iet-its.2012.0101

[6] Jin , C., Wang , J., Ma , J., , 2010. Applicationof improved PSO for parameter tuning of PID controller. J. Electron. Meas. Instrum., 24(2):141-146. https://doi.org/10.3724/SP.J.1187.2010.00141

[7] Khan , H., Iqbal , J., Baizid , K., , 2015. Longitudinaland lateral slip control of autonomous wheeled mobile robot for trajectorytracking. Front.Inform. Technol. Electron. Eng., 16(2):166-172. https://doi.org/10.1631/FITEE.1400183

[8] Kim , K.I., Guan , H., Wang , B., , 2016. Active steeringcontrol strategy for articulated vehicles. Front. Inform. Technol. Electron. Eng., 17(6):576-586. https://doi.org/10.1631/FITEE.1500211

[9] Konstantinidis , E.I., Patoulidis , G.I., Vandikas , I.N., , 2010. Development of a collaborative vehicle collision avoidance system. IEEE Intelligent Vehicles Symp., p.1066–1071. https://doi.org/10.1109/IVS.2010.5548022

[10] Kreuzen , C., 2012. Cooperative Adaptive cruise controlusing information from multiple predecessors in combination with MPC. MS Thesis, Delft University of Technology, Delft,the Netherlands.

[11] Lee , D.H., Bai , S.N., Kim , T.W., , 2010. Enhanced selective forwarding scheme for alert message propagationin VANETs. Int. Conf. on Information Scienceand Applications, p.1-9. https://doi.org/10.1109/ICISA.2010.5480516

[12] Mirfakhraie , T., He , Y., Liscano , R., 2014. Wirelessnetworked control for active trailer steering systems of articulatedvehicles. ASME Int. Mechanical EngineeringCongress and Exposition, Volume 12: Transportation Systems, p.V012T15A003. https://doi.org/10.1115/IMECE2014-36440

[13] Ong , H.Y., Gerdes , J.C., 2015. Cooperative collision avoidance via proximal messagepassing. American Control Conf., p.4124-4130. https://doi.org/10.1109/ACC.2015.7171976

[14] Seo , H.S., Jung , J.S., Lee , S.S., 2014. Networkperformance analysis and manuever model for overtaking assistant serviceusing wave. Int.J. Autom. Technol., 15(1):57-64. https://doi.org/10.1007/s12239-014-0006-x

[15] Shi , Y., Eberhart , R., 1998. A modified particle swarm optimizer. IEEE Int. Conf. on Evolutionary Computation, p.69-73. https://doi.org/10.1109/ICEC.1998.699146

[16] Shi , Y., Eberhart , R.C., 2001. Fuzzy adaptive particle swarm optimization. Congress on Evolutionary Computation, p.101-106. https://doi.org/10.1109/CEC.2001.934377

[17] Solyom , S., Bengtsson , M., 2012. Collision Avoidance System in a Vehicle.US Patent 8 200 420.

[18] Tan , H.S., Huang , J., 2006. DGPS-based vehicle-to-vehicle cooperative collision warning:engineering feasibility viewpoints. IEEE Trans. Intell. Transp. Syst., 7(4):415-428. https://doi.org/10.1109/TITS.2006.883938

[19] Wang , Q., Phillips , C., 2013. Cooperative collision avoidance for multi-vehicle systemsusing reinforcement learning. 18th Int.Conf. on Methods & Models in Automation & Robotics, p.98-102. https://doi.org/10.1109/MMAR.2013.6669888

[20] Wang , Q., Zhu , S., He , Y., 2015. Model reference adaptivecontrol for active trailer steering of articulated heavy vehicles. SAE Technical Papers, 2015-01-1495. https://doi.org/10.4271/2015-01-1495

[21] Wang , Q.G., Zou , B., Lee , T.H., , 1997. Auto-tuningof multivariable PID controllers from decentralized relay feedback. Automatica, 33(3):319-330. https://doi.org/10.1016/S0005-1098(96)00177-X

[22] Wu , Y.H., Lu , Y.P., 2009. Main factors and evaluation methods of driving comfort. Heilongjiang Jiaotong Keji, 2009(8): 197-198 (in Chinese). https://doi.org/10.16402/j.cnki.issn1008-3383.2009.08.107

[23] Yan , G., Yang , W., Weigle , M.C., , 2010. Cooperative collision warning through mobility and probability prediction. IEEE Intelligent Vehicles Symp., p.1172-1177. https://doi.org/10.1109/IVS.2010.5547990

[24] Yu , C.B., Wang , Y.Q., Shao , J.L., 2016. Optimizationof formation for multi-agent systems based on LQR. Front. Inform. Technol. Electron. Eng., 17(2):96-109. https://doi.org/10.1631/FITEE.1500490

[25] Zardosht , B., Beauchemin , S., Bauer , M.A., 2013. A decisionmaking module for cooperative collision warning systems using vehicularad-hoc networks. 16th Int. IEEE Conf. onIntelligent Transportation Systems, p.1743-1749. https://doi.org/10.1109/ITSC.2013.6728481

[26] Zhang , H.T., Hu , H.L., Wang , B., 2008. A modifiedPSO algorithm and its application in tuning of PID. Techn. Autom. Appl., 27(12):14-16. https://doi.org/10.3969/j.issn.1003-7241.2008.12.004

[27] Zhang , J.M., Li , Q., Cheng N., , 2013. Nonlinearpath-following method for fixed-wing unmanned aerial vehicles. J. Zhejiang Univ.-Sci. C(Comput. & Electron.), 14(2):125-132. https://doi.org/10.1631/jzus.C1200195

[28] Zhang , M.H., Duan , D.P., Chen , L., 2012. Turningmechanism and composite control of stratospheric airships. J. Zhejiang Univ.-Sci. C(Comput. & Electron.), 13(11): 859-865. https://doi.org/10.1631/jzus.C1200084

[29] Zhu , X., Liu , Z., Li , L., 2015. Evasive manoeuvrefor emergency steering based on typical vehicle-pedestrian use case. J. Autom. Safety Energy, 6(3):217-223 (in Chinese). https://doi.org/10.3969/j.issn.1674-8484.2015.03.003

RIGHTS & PERMISSIONS

2017 Zhejiang University and Springer-Verlag GmbHGermany