Fuzzy-GSA Based Control Approach for Developing Adaptive Cruise Control
محورهای موضوعی : Mechanical Engineering
1 - Sama technical and vocational training college, Islamic Azad University, Kazerun Branch, Kazerun, Iran
کلید واژه: Adaptive cruise control, Distance control, fuzzy logic control, Velocity control,
چکیده مقاله :
Adaptive Cruise Control (ACC) controls vehicle speed and its distance to the proceeding vehicle in the same lane. In this paper a two-level control architecture is proposed to control both velocity and distance to the leading vehicle by taking advantage of fuzzy logic control (FLC) approach. Then the control parameters were tuned by Gravitational Search Algorithm (GSA) to ensure achieving the fastest and most accurate control response. To evaluate performance of the proposed scheme, a speed profile was developed in simulation based test platform to measure performance of the proposed ACC in different maneuvers including some velocity tests and a distance control maneuver. The results revealed that the proposed approach had a stable and fast response which satisfied the requirements of an ACC.
[1] Weisswange, T. H., Bolder, B., Fritsch, J., Hasler, S., and Goerick, C., “An Integrated ADAS for Assessing Risky Situations in Urban Driving”, IEEE Intelligent Vehicles Symposium IV, 2013, pp. 292- 297.
[2] Luo, X., Du, W., and Zhang, J., “Safety Benefits of Motorized Seat Belt as a Component in ADAS in Front-End Collisions”, IEEE 17th International Conference on Intelligent Transportation Systems (ITSC), 2014, pp. 661-666.
[3] Gruyer, D., Pechberti, S., and Glaser, S., “Development of Full Speed Range ACC with SiVIC, a Virtual Platformfor ADAS Prototyping, Test and Evaluation”, IEEE Intelligent Vehicles Symposium Workshops IV, 2013, pp. 93-98.
[4] García, F., Escalera, A., and Armingol, J. M., “Enhanced Obstacle Detection Based on Data Fusion for ADAS Applications”, 16th International IEEE Annual Conference on Intelligent Transportation Systems, 2013, pp. 1370-1375
[5] Liu, S., Huang, Y., and Zhang, R., “Obstacle Recognition for ADAS Using Stereovision and Snake Models”, IEEE 17th International Conference on Intelligent Transportation Systems (ITSC), 2014, pp. 99-104.
[6] Dixit, R. S., Gandhe, S. T., “Pedestrian Detection System for ADAS Using Friendly ARM”, International Conference on Energy Systems and Applications (ICESA), 2015, pp. 557-560.
[7] Devapriya, W., Kennedy, C. N., and Srihari T., “Advance Driver Assistance System (ADAS) Speed Bump Detection”, IEEE International Conference on Computational Intelligence and Computing Research, 2015, pp. 1-6.
[8] Guo, C., Meguro J., Kojima, Y., and Naito T., “A Multimodal ADAS System for Unmarked Urban Scenarios Based on Road Context Understanding”, IEEE Transactions on Intelligent Transportation Systems, 2014, pp. 1-15.
[9] Crow, J., Parker, R., “Automatic Headway Control - an Automatic Vehicle Spacing System”, International Society of Automotive Engineering (SAE), 1970, pp. 1-12.
[10] Geamanu, M. S., Cela, A., LeSolliec, G., Mounier, H., and Niculescu, S., “Maximum Friction Estimation and Longitudinal Control for a Full In-Wheel Electric Motor Vehicle”, IEEE 12th Control, Automation and Systems, International Conference (ICCAS), 2012.
[11] Mammar, S., Oufroukh, N. A., Nouveli`ere, L., and Gruyer, D., “Integrated Automated Vehicle String Longitudinal Control”, IEEE Intelligent Vehicles Symposium IV, 2013, pp. 803-808.
[12] Takasaki, G. M., and Fenton R. E., “On Vehicle Longitudinal Dynamics Identification and Control”, IEEE 26th Vehicular Technology Conference, 1976, pp. 16-20.
[13] Lian, Y., Zhao, Y., Hu, L., and Tian, Y., “Longitudinal Collision Avoidance Control of Electric Vehicles Based on a New Safety Distance Model and Constrained Regenerative Braking Strength Continuity Braking Force Distribution Strategy”, IEEE Transactions on Vehicular Technology, 2015, pp. 1-17.
[14] Corno, M., Lucchetti, A., Boniolo, I., and Savaresi, S. M., “Coordinated Lateral and Longitudinal Vehicle Dynamics Control of a Scale RC Vehicle”, American Control Conference, 2015, pp. 1433-1438.
[15] Tai, M., Tomizuka, M., “Robust Longitudinal Velocity Tracking of Vehicles Using Traction and Brake Control”, IEEE Advanced Motion Control Workshop, 2000, pp. 305-310.
[16] Muller, R., Nocker, G., “Intelligent Cruise Control with Fuzzy Logic”, Symposium Proceedings of the Intelligent Vehicles, 1992, pp. 173-178.
[17] Zlocki, A., Themann, P., “Methodology for Quantification of Fuel Reduction Potential for Adaptive Cruise Control Relevant Driving Strategies”, Intelligent Transport Systems (IET), Vol. 7, Issue 1, 2014, pp. 68-75.
[18] Zhang, J., Ioannou, P. A., “Longitudinal Control of Heavy Trucks in Mixed Traffic: Environmental and Fuel Economy Considerations”, IEEE Transactions on Intelligent Transportation Systems, Vol. 7, No. 1. 2006, pp. 92-104.
[19] Flehmig, F., Sardari, A., Fischer, U., and Wagner, A., “Energy Optimal Adaptive Cruise Control During Following of Other Vehicles”, IEEE Intelligent Vehicles Symposium IV, 2015, pp. 724-729.
[20] Naranjo, J. E., González, C., Reviejo, J., García, R., and Pedro, “Adaptive Fuzzy Control for Inter-Vehicle Gap”, IEEE transactions on Intelligent Transportation System, Vol. 4, No. 3, 2003, pp. 132-142.
[21] Cai, L., Rad, A. B., Chan, W. L., and Ho, M. L., “A Neural-Fuzzy Controller for Intelligent Cruise Control of Vehicle in Highways”, IEEE Intelligent Transportation Systems Proceedings, 2003, pp. 1389-1393.
[22] Liang, B., Lin, W. S., “Vehicular Adaptive Optimal Cruise Control with Multiple Objectives”, IEEE International Conference on Systems, Man and Cybernetics, 2012, pp. 2539-2544.
[23] Su´arez, J. I., Vinagre, B. M., and Chen, Y. Q., “Spatial Path Tracking of an Autonomous Industrial Vehicle Using Fractional Order Controllers”, ICAR 11th Int. Conf. on Advanced Robotics, 2003, pp. 405–410.
[24] Rossetter, E. J., Gerdes, J. C., “Performance Guarantees for Hazard Based Lateral Vehicle Control”, Proc. ASME. Dynamic Systems and Control, 2002, pp. 1-11.
[25] Luo, L., Liu, H., Li, P., and Wang, H., “Model Predictive Control for Adaptive Cruise Control with Multi-Objectives: Comfort, Fuel-Economy, Safety and Car-Following”, Journal of Zhejiang University, Vol. 11, Issue 1, 2010, pp. 191-201.
[26] Ioannou, P., Xu, Z., Eckert, S., Clemons, D., and Sieja, T., “Intelligent Cruise Control: Theory and Experiment”, IEEE 32nd Decision and Control Conference, 1993, pp. 1885-1890.
[27] Higashimata, A., Adachi, K., Hashizume, T., and Tange, S., “Design of a Headway Distance Control System for ACC”, JSAE, Vol. 22, Issue 1, 2001, pp. 15-22.
[28] Zheng, P., McDonald, M., “Manual vs. Adaptive Cruise Control, Can Driver’s Expectation Be Matched”, Transportation Research Part C: Emerging Technologies, Vol. 13, Issues 5–6, 2005, pp. 421–431.
[29] Sathiyan, P., Kumar, S., and Selvakumar, A., “Optimized Fuzzy Controller for Improved Comfort Level During Transition in Cruise and Adaptive Cruise Control Vehicles”, IEEE Transactions on Evolutionary Computation, 2015, pp. 86-91.
[30] Takahashi, H., “Automatic Speed Control Device Using Self-Tuning Fuzzy Logic”, IEEE Workshop on Automotive Applications of Electronics, 1988, pp. 65-71.
[31] Idriz, A. F., “Safe Interaction Between Lateral and Longitudinal Adaptive Cruise Control in Autonomous Vehicles”, Ph.D. Dissertation, Mechanical Engineering Dept., Delft University of Technology, 2015.
[32] Pérez, J., Milanés, V., Godoy, J., Villagrá, J., and Onieva, E., “Cooperative Controllers for Highways Based on Human Experience”, Expert Systems with Applications, Vol. 40, Issue 4, 2013, pp 1024–1033.
[33] Maeda, M., “Fuzzy Drive Expert System for an Automobile”, Information Sciences Applications, Vol. 4, No. 1, 1995, pp. 29-48.
[34] Khayyam, H., Nahavandi, S., and Davis, S., “Adaptive Cruise Control Cook-Ahead System for Energy Management of Vehiclesˮ, Expert Systems with Applications, Vol. 39, No. 3, 2012, pp. 3874-3885.
[35] Higashimata, A., Adachi, K., Hashizume, T., and Tange, S., “Design of a Headway Distance Control System for ACC”, JSAE, Vol. 22, No. 1, 2001, pp. 15-22.
[36] Zadeh, L. A., “Fuzzy Sets”, Journal of information and control, Vol. 8, No. 3, 1965, pp. 338-353.
[37] Mamdani, E. H., “Application of Fuzzy Algorithms for Control of Simple Dynamic Plant”, Proceedings of The Institution of Electrical Engineers, Vol. 121, No. 12, 1974, pp. 1585-1588.
[38] Juang, J., Chio, J., “Aircraft Landing Control Lased on Fuzzy Modeling Networks”, IEEE International Conference on Control Applications, 2002, pp. 144-149.
[39] Zaheer, S., Kim, J., “Type-2 Fuzzy Airplane Altitude Control, a Comparative Study”, IEEE International Conference on Fuzzy Systems, 2011, pp. 2370-2376.
[40] Juang, J., Lin, B., and Chin, K., “Automatic Landing Control Using Particle Swarm Optimization”, IEEE International Conference on Mechatronics, 2005, pp. 721-726.
[41] Cheok, D., Shiomi, S., “Combined Heuristic Knowledge and Limited Measurement Based Fuzzy Logic Antiskid Control for Railway Applications”, IEEE Transactions on Man and Cybernetics Vol. 30, No. 4, 2000, pp. 554-568.
[42] Chernov, V., Bogachev, V. A., and Karpenko, E. V., “Rough and Fuzzy Sets Approach for Incident Identification in Railway Infrastructure Management System”, IEEE International Conference on Soft Computing and Measurements (SCM), 2016, pp. 228-230.
[43] Poursamad, A., Montazeri, M., “Design of Genetic-Fuzzy Control Strategy for Parallel Hybrid Electric Vehicles”, Control engineering practice, Vol. 16, No. 7, 2008, pp. 861-873.
[44] Bostanian, M., Barakati, S. M., Najjari B., and Kalhori D. M., “A Genetic-Fuzzy Control Strategy for Parallel Hybrid Electric Vehicle”, International Journal of Automotive Engineering (IJAE) Vol. 3, No. 3, 2013, pp. 482-495.
