Cloud Control System Architectures, Technologies and Applications on Intelligent and Connected Vehicles: a Review


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Expert Systems with Applications, 2019, 121: 38-48.

  1. C Chatzikomis, A Sorniotti, P Gruber, Comparison of path tracking and torque-vectoring controllers for autonomous electric vehicles. IEEE Transactions on Intelligent Vehicles, 2018, 3(4): 559-571.

  2. Y Li, J Ni, J Hu. The design of driverless vehicle trajectory tracking control strategy. IFAC-PapersOnLine, 2018, 51(31): 738-745.

  3. N R Kapania, J C Gerdes. Design of a feedback-feedforward steering controller for accurate path tracking and stability at the limits of handling, Vehicle System Dynamics, 2015, 53(12): 1687-1704.

  4. Q Tan, P Dai, Z Zhang, et al., MPC and PSO based control methodology for path tracking of 4WS4WD vehicles. Applied Sciences, 2018, 8(6):1000.

  5. J. Ji, A Khajepour. Path planning and tracking for vehicle collision avoidance based on model predictive control with multiconstraints. IEEE Transactions on Vehicular Technology, 2017, 25(24): 86-97.

  6. C Shen, H Guo, F Liu, et al. MPC-based path tracking controller design for autonomous ground vehicles. 36th Chinese Control Conference (CCC), Dalian, China, 26–28 July 2017: 9584–9589.

  7. H Jing, C Hu, F Yan, et al. Robust Hfollowing of autonomous ground vehicles. ∞ output-feedback control for path 54th IEEE Conference on Decision & Control (CDC), 2015: 1515–1520.

  8. S Hong, C Zhang, G An, Fuzzy-model-based H∞ dynamic output feedback control with feedforward for autonomous vehicle path tracking. International Conference on Fuzzy Theory and Its Applications (iFUZZY), 2017: 1–6.

  9. C. Hu, H. Jing, R. Wang. Robust Hfollowing of autonomous ground vehicles. ∞ output-feedback control for path Mechanical Systems and

Signal Processing, 2016, 70: 414-427.

  1. D Ren, J Zhang, J Zhang. Sliding mode control for vehicle following with parametric uncertainty. Electric Machines and Control, 2010, 14(1): 73-78.

  2. R Wang, G Yin, X Jin. Robust adaptive sliding mode control for nonlinear four-wheel steering autonomous vehicles path tracking systems. 8th Power Electronics & Motion Control Conference, Hefei, China, 22-26 May 2016: 2999–3006.

  3. J Guo, Y Luo, K Li. Adaptive fuzzy sliding mode control for coordinated longitudinal and lateral motions of multiple autonomous vehicles in a platoon. Science China(Technological Sciences), 2017, 60(4): 576-586.

  4. T Sun, Y Pan, J Zhang, et al. Robust model predictive control for constrained continuous-time nonlinear systems. International Journal of Control, 2018, 91(2): 359-368.

  5. R Gonzalez, M Fiacchini, T Alamo, et al. Online robust tube-based MPC for time-varying systems: a practical approach. International Journal of Control, 2011, 84(6): 1157–1170.

  6. I Nodozi, M Rahmani. LMI-based robust mixed-integer model predictive control for hybrid systems. International Journal of Control, 2019, 12(20): 12-22.

  7. X Wang, Y Zhang, Z Xue. Fuzzy sliding mode control based on RBF neural network for AUV path tracking. International Conference on Intelligent Robotics and Applications, Switzerland: Springer, Cham, 2019: 637–648.

  8. Y Chen, Z Li, H Kong. Model predictive tracking control of nonholonomic mobile robots with coupled input constraints and unknown dynamics. IEEE Transactions on Industrial Informatics, 2019, 15(6):

3198-3205.

  1. N Wang, Z Sun, J Yin, et al. Fuzzy unknown observer-based robust adaptive path following control of underactuated surface vehicles subject to multiple unknowns. Ocean Engineering, 2019, 176: 57-64.

  2. M Ahmadian, S Southward. No–Jerk skyhook control methods for semiactive suspensions. Journal of Vibration and Acoustics, 2004, 126(4):

580–584

  1. Y Liu, L Zuo. Mixed skyhook and power–driven–damper: a new low-jerk semi-active suspension control based on power flow analysis. Journal of Dynamic Systems, Measurement, and Control, 2016, 138(8): 081009.

  2. Q Xiong, B Qin, X Li, et al. A rule–based damping control of MMR–based energy–harvesting vehicle suspension. 2020 American Control Conference (ACC), Denver, USA, 1–3 July 2020: 2262–2267.

  3. S Guo, Q Xiong, J M Li, et al. Truck suspension control for pavement protection at signalized intersections. 2018 Annual American Control Conference (ACC), Milwaukee, USA, 27–29 June 2018: 3696–3701.

  4. H Fritz. Longitudinal and lateral control of heavy duty trucks for automated vehicle following in mixed traffic: experimental results from the CHAUFFEUR project. Kohala Coast, USA, 22–27 Aug. 1999: 1348–1352.

  5. H Peng, M Tomizuka. Preview control for vehicle lateral guidance in highway automation. American Control Conference, Boston, USA, 26–28 Jun. 1991: 3090–3095.

  6. L Li, D Wen, D Yao. A survey of traffic control with vehicular communications. IEEE Transactions on Intelligent Transportation Systems, 2014, 15(1): 425–432.

  7. Q Guo, L Li, X Ban. Urban traffic signal control with connected and automated vehicles: a survey. Transportation Research Part C: Emerging Technologies, 2019, 101: 313–334.

  8. W Li, X Ban. Traffic signal timing optimization in connected vehicles environment. 2017 IEEE Intelligent Vehicles Symposium (IV), Los Angeles, CA, USA, 11–14 June 2017: 1330–1335.

  9. Y Zheng, J Wang, K Li. Smoothing traffic flow via control of autonomous vehicles. IEEE Internet of Things Journal, 2020, 7(5): 3882–3896.

  10. J Wang, Y Zheng, Q Xu, et al. Controllability analysis and optimal control of mixed traffic flow with human–driven and autonomous vehicles.


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