Bağlantılı otonom araç takımlarının nöro-kayan kipli denetleyici ile boylamsal kontrolü

Abstract

Bağlantılı otonom araçlar (CAV) trafik kazaları, trafik sıkışıklığı ve trafik güvenliğinin sağlanması gibi karayolu taşımacılığını önemli ölçüde etkileme potansiyelleri nedeniyle son zamanlarda önemli bir araştırma konusu haline gelmiştir. Bu nedenle bu çalışmada, bağlantılı otonom araç takımlarının boylamsal kontrolünü sağlamak için bir nöro-kayan kipli denetleyici (NSMC) tasarlanmıştır. Öncelikle, CAV takımının boylamsal dinamiklerinin formülasyonu elde edilmiştir. Sonrasında, araç takımının dizi kararlılığını sağlamak ve doğruluğu, Lyapunov kararlılık kriterleri ile teorik doğrulamanın ardından simülasyon çalışmalarıyla gösterilmiştir. Sonuç olarak harici bozucu etkiler ve parametre belirsizlikleri dikkate alınarak CAV'ın doğrusal olmayan matematiksel modelinin oluşturulması sağlanmıştır ve zamanla değişen belirsiz dinamikler altında NSMC denetleyici tasarımı gerçekleştirilmiştir. Bu tasarlanan denetleyici yapısındaki sinir ağları yardımıyla bilinmeyen sistem dinamikleri öğrenilerek kayan kipli denetleyici ile de hedeflenen araçlar arası mesafelerin oluşturulması sağlanmıştır ve araç takımındaki boylamsal dizi kararlılığı başarılı bir şekilde gerçekleştirilmiştir.

Keywords

• Araç takımlarının kontrolü
• doğrusal olmayan kontrol
• kayan kipli denetleyici
• sinir ağları

Longitudinal control of connected autonomous vehicles platoons with neuro sliding mode controller

Abstract

Connected autonomous vehicles (CAV) have recently become an important research topic due to their potential to significantly affect road transport such as traffic accidents, traffic congestion and ensuring traffic safety. Therefore in this study, a neuro-sliding mode controller (NSMC) is designed to provide longitudinal control of connected autonomous vehicles platoons. First, the formulation of the longitudinal dynamics of the CAV platoon is obtained. Afterwards, the neuro-sliding mode controller design was carried out under uncertain dynamics that change over time by formulating platoon control targets in order to ensure the string stability of the vehicle platoon and to prevent rear end collisions. The accuracy of the designed controller is demonstrated by simulation studies after theoretical verification with Lyapunov stability criteria. As a result, the nonlinear mathematical model of CAV was created by taking into account external disturbances and parameter uncertainties, and the NSMC controller design was implemented under uncertain dynamics that change over time. With the help of neural networks in the designed controller structure, unknown system dynamics were learned, and the desired inter-vehicle distances were achieved using a sliding mode controller, and longitudinal string stability in the vehicle platoon was successfully achieved.

Keywords

• Vehicle platoons control
• nonlinear control
• sliding mode control
• neural network

References

1. Cheng, F., Zheng, H., Gong, C., & Kaku, C., Longitudinal Cruise Control of Truck Platoon Based on Distributed Sliding Mode Control Strategy. In 2022 6th CAA International Conference on Vehicular Control and Intelligence (CVCI) (pp. 1-5). IEEE, (2022,).
2. Bayuwindra, A., Lefeber, E., Ploeg, J., & Nijmeijer, H., Extended look-ahead tracking controller with orientation-error observer for vehicle platooning. IEEE Transactions on Intelligent Transportation Systems, 21(11), 4808-4821, (2019).
3. Li, Y., Chen, W., Peeta, S., & Wang, Y., Platoon control of connected multi-vehicle systems under V2X communications: Design and experiments. IEEE Transactions on Intelligent Transportation Systems, 21(5), 1891-1902, (2019).
4. Li, S. E., Zheng, Y., Li, K., Wu, Y., Hedrick, J. K., Gao, F., & Zhang, H., Dynamical modeling and distributed control of connected and automated vehicles: Challenges and opportunities. IEEE Intelligent Transportation Systems Magazine, 9(3), 46-58, (2017).
5. Li, Y., Tang, C., Peeta, S., & Wang, Y., Nonlinear consensus-based connected vehicle platoon control incorporating car-following interactions and heterogeneous time delays. IEEE Transactions on Intelligent Transportation Systems, 20(6), 2209-2219, (2018).
6. Zheng, Y., Li, S. E., Li, K., & Wang, L. Y., Stability margin improvement of vehicular platoon considering undirected topology and asymmetric control. IEEE Transactions on Control Systems Technology, 24(4), 1253-1265, (2015).
7. Zhu, Y., Li, Y., Hu, S., & Yu, S., Optimal Control for Vehicle Platoon Considering External Disturbances. In 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) (pp. 453-458). IEEE, (2022).
8. Sheikholeslam, S., & Desoer, C. A., Longitudinal control of a platoon of vehicles. In 1990 American control conference (pp. 291-296). IEEE, (1990).

9. Horowitz, R., & Varaiya, P., Control design of an automated highway system. Proceedings of the IEEE, 88(7), 913-925, (2000).
10. Zakerimanesh, A., Qiu, T., & Tavakoli, M., Heterogeneous vehicular platooning with stable decentralized linear feedback control. In 2021 IEEE International Conference on Autonomous Systems (ICAS) (pp. 1-5). IEEE, (2021).
11. Wang, Y., & Liu, C., Dynamic Integral Sliding Mode for Vehicle Platoon Control with Constant Time Headway Policy. In 2021 IEEE International Conference on Robotics and Biomimetics (ROBIO) (pp. 1479-1484). IEEE, (2021).
12. Li, Y., Lv, Q., Zhu, H., Li, H., Li, H., Hu, S., & Wang, Y., Variable time headway policy based platoon control for heterogeneous connected vehicles with external disturbances. IEEE Transactions on Intelligent Transportation Systems, 23(11), 21190-21200, (2022).
13. Han, J., He, C., Liu, W., Li, C., & Zhang, J., Fast terminal sliding mode control for cooperative braking of the vehicle platoon. In 2021 40th Chinese Control Conference (CCC) (pp. 5992-5997). IEEE, (2021).
14. Wang, P., Deng, H., Zhang, J., Wang, L., Zhang, M., & Li, Y., Model predictive control for connected vehicle platoon under switching communication topology. IEEE Transactions on Intelligent Transportation Systems, 23(7), 7817-7830, (2021).
15. Guo, G., & Li, D., Adaptive sliding mode control of vehicular platoons with prescribed tracking performance. IEEE Transactions on Vehicular Technology, 68(8), 7511-7520, (2019).
16. Zhao, X., Chen, Y. H., & Zhao, H., Robust approximate constraint‐following control for autonomous vehicle platoon systems. Asian Journal of Control, 20(4), 1611-1623, (2018).
17. Wen, S., & Guo, G., Observer-based control of vehicle platoons with random network access. Robotics and Autonomous systems, 115, 28-39, (2019).
18. Liang, K. Y., Mårtensson, J., & Johansson, K. H., Heavy-duty vehicle platoon formation for fuel efficiency. IEEE Transactions on Intelligent Transportation Systems, 17(4), 1051-1061, (2015).
19. Fakhfakh, F., Tounsi, M., & Mosbah, M., Vehicle platooning systems: Review, classification and validation strategies. International Journal of Networked and Distributed Computing, 8(4), 203-213, (2020).
20. Boubakri, A., & Gammar, S. M., Intra-platoon communication in autonomous vehicle: A survey. In 2020 9th IFIP International Conference on Performance Evaluation and Modeling in Wireless Networks (PEMWN) (pp. 1-6). IEEE, (2020).
21. Prayitno, A., & Nilkhamhang, I., V2V network topologies for vehicle platoons with cooperative state variable feedback control. In 2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP) (pp. 1-4). IEEE, (2021).
22. Ge, X., Han, Q. L., Wang, J., & Zhang, X. M., Scalable and resilient platooning control of cooperative automated vehicles. IEEE Transactions on Vehicular Technology, 71(4), 3595-3608, (2022).
23. Utkin, V., Variable structure systems with sliding modes. IEEE Transactions on Automatic control, 22(2), 212-222, (1977).
24. Nobe, S. A., & Wang, F. Y., An overview of recent developments in automated lateral and longitudinal vehicle controls. In 2001 IEEE International Conference on Systems, Man and Cybernetics. E-Systems and E-Man for Cybernetics in Cyberspace (Cat. No. 01CH37236) (Vol. 5, pp. 3447-3452). IEEE, (2001).
25. Gunagwera, A., & Zengin, A. T., A longitudinal inter-vehicle distance controller application for autonomous vehicle platoons. PeerJ Computer Science, 8, e990, (2022).
26. Li, S. E., Gao, F., Li, K., Wang, L. Y., You, K., & Cao, D., Robust longitudinal control of multi-vehicle systems—A distributed H-infinity method. IEEE Transactions on Intelligent Transportation Systems, 19(9), 2779-2788, (2017).
27. Zhao, F., Liu, Y., Wang, J., & Wang, L., Distributed model predictive longitudinal control for a connected autonomous vehicle platoon with dynamic information flow topology. In Actuators (Vol. 10, No. 9, p. 204). MDPI, (2021).
28. Xu, H., & Lu, C., Design of switched fuzzy adaptive double coupled sliding mode control for vehicles platoon. In 2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE) (pp. 422-426). IEEE, (2020).
29. Shalaby, M. K., Farag, A., AbdelAziz, O. M., Mahfouz, D. M., Shehata, O. M., & Morgan, E. I., Design of various dynamical-based trajectory tracking control strategies for multi-vehicle platooning problem. In 2019 IEEE Intelligent Transportation Systems Conference (ITSC) (pp. 1631-1637). IEEE, (2019).
30. Song, L., Li, J., Wei, Z., Yang, K., Hashemi, E., & Wang, H., Longitudinal and lateral control methods from single vehicle to autonomous platoon. Green Energy and Intelligent Transportation, 2(2), 100066, (2023).
31. Olwan, M. A., Mostafa, A. A., AbdELAty, Y. M., Mahfouz, D. M., Shehata, O. M., & Morgan, E. I., Behavior Evaluation of Vehicle Platoon via Different Fuzzy-X Tuned Controllers. In 2020 8th International Conference on Control, Mechatronics and Automation (ICCMA) (pp. 149-155). IEEE, (2020).
32. Peng, B., Yu, D., Zhou, H., Xiao, X., & Fang, Y., A platoon control strategy for autonomous vehicles based on sliding-mode control theory. IEEE Access, 8, 81776-81788, (2020).
33. Chen, H., Li, Y., Yu, S., & Shi, S., Integral Sliding-Mode Platoon Control for Connected Vehicles with Disturbance Observer. In 2022 6th CAA International Conference on Vehicular Control and Intelligence (CVCI) (pp. 1-6). IEEE, (2022).
34. Aghababa, M. P., & Saif, M., Finite time sliding mode control of connected vehicle platoons guaranteeing string stability. In 2020 IEEE International Conference on Human-Machine Systems (ICHMS) (pp. 1-6). IEEE, (2020).
35. Guo, G., & Li, D., PMP-based set-point optimization and sliding-mode control of vehicular platoons. IEEE Transactions on Computational Social Systems, 5(2), 553-562, (2018).
36. Chen, J., Bai, D., Liang, H., & Zhou, Y., A Third‐Order Consensus Approach for Vehicle Platoon with Intervehicle Communication. Journal of Advanced Transportation, 2018(1), 8963289, (2018).
37. Guo, X., Wang, J., Liao, F., & Teo, R. S. H., Distributed adaptive integrated-sliding-mode controller synthesis for string stability of vehicle platoons. IEEE Transactions on Intelligent Transportation Systems, 17(9), 2419-2429, (2016).
38. Rajamani, R., Vehicle dynamics and control. Springer Science & Business Media, (2011).
39. Kiencke, U., & Nielsen, L., Automotive control systems: for engine, driveline, and vehicle, (2000).
40. Guzzella, L., & Sciarretta, A., Vehicle propulsion systems (Vol. 1). Springer-Verlag Berlin Heidelberg, (2007).
41. Farag, A., Hussein, A., Shehata, O. M., Garcia, F., Tadjine, H. H., & Matthes, E., Dynamics platooning model and protocols for self-driving vehicles. In 2019 IEEE Intelligent Vehicles Symposium (IV) (pp. 1974-1980). IEEE, (2019).
42. Farag, A., Hussein, A., Shehata, O. M., & Morgan, E. I., Design and Validation of A Novel Adaptive Cruise Control Law for a Platoon Of Vehicles. In 2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) (pp. 81-86). IEEE, (2020).
43. Genta, G., Motor vehicle dynamics: modeling and simulation (Vol. 43). World scientific, (1997).
44. Guo, J., Hu, P., & Wang, R., Nonlinear coordinated steering and braking control of vision-based autonomous vehicles in emergency obstacle avoidance. IEEE Transactions on Intelligent Transportation Systems, 17(11), 3230-3240, (2016).
45. Lewis, F. W., Jagannathan, S., & Yesildirak, A., Neural network control of robot manipulators and non-linear systems. CRC press, (2020).
46. Sastry, S., Nonlinear systems: analysis, stability, and control (Vol. 10). Springer Science & Business Media, (2013).
47. Hardy, G. H., Inequalities. Cambridge University Press, (1952).