Abstract
In the longitudinal driving of a heterogeneous platoon, external disturbances of local vehicles can cause safety problems of the intended functionality. Therefore, a cooperative control method based on situation assessment is proposed. First, the minimum safe distance is determined according to the state of adjacent vehicles. A novel situation assessment model is established to characterize the stability of the platoon. Vehicle spacing, speed, and acceleration are selected as evaluation indicators. Then, an improved active disturbance rejection controller (IADRC) is designed to improve platoon stability through feedback compensation control. In addition, considering the unnecessary continuous involvement of the IADRC, its intervention time is determined by the situation assessment results. Finally, simulation and hardware-in-the-loop (HIL) experiments are carried out under two communication topologies. The results show that the proposed method can effectively improve the stability and safety of the platoon.
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Abbreviations
- p :
-
: Vehicle position
- v :
-
: Vehicle velocity
- a :
-
: Vehicle acceleration
- τ :
-
: Time constant
- ω :
-
: External disturbances
- p̃ i :
-
: Distance tracking error between vehicle i and leader
- ṽ i :
-
: Velocity tracking error between vehicle i and leader
- ã i :
-
: Acceleration tracking error between vehicle i and leader
- D min :
-
: Minimum safety distance
- TTC:
-
: Collision time
- μ :
-
: Road adhesion coefficient
- g :
-
: Acceleration due to gravity
- L :
-
: Length of the vehicle
- p m :
-
: Desired distance between two adjacent vehicles
- v m :
-
: Desired velocity
- a m :
-
: Desired acceleration
- ∂:
-
: Comprehensive situation value
- δ:
-
: Length of the linear interval
References
Benedetto, F., Calvi, A., D’Amico, F., & Giunta, G. (2015). Applying telecommunications methodology to road safety for rear-end collision avoidance. Transportation Research Part c: Emerging Technologies, 50, 150–159.
Bengler, K., Dietmayer, K., Farber, B., Maurer, M., Stiller, C., & Winner, H. (2014). Three decades of driver assistance systems: Review and future perspectives. IEEE Intelligent Transportation Systems Magazine, 6(4), 16–22.
Chehardoli, H., & Homaeinezhad, M. R. (2017). Stable control of a heterogeneous platoon of vehicles with switched interaction topology, time-varying communication delay and lag of actuator. Proceedings of the Institution of Mechanical Engineers, Part c: Journal of Mechanical Engineering Science, 231(22), 4197–4208.
Chen, Z. W., Zhang, Z. Z., & Cao, Y. J. (2018). Fal function improvement of ADRC and its application in quadrotor aircraft attitude control. Control and Decision, 33(10), 1901–1907.
Deng, Y., Liang, H., Wang, Z. L., & Huang, J. J. (2014). An integrated forward collision warning system based on monocular vision. In Proc. IEEE Int. Conf. Robotics and Biomimetics (ROBIO), Bali, Indonesia.
Feng, J. B., He, L. Y., Wang, Y. X., Yang, J. W., & Ren, H. B. (2023). Backstepping method based controller design for third-order truck platoon robust to dynamic uncertainty and external disturbance. Journal of Mechanical Science and Technology, 37(3), 1433–1442.
Feng, S., Sun, H. W., Zhang, Y., Zheng, J. F., Liu, H. X., & Li, L. (2020). Tube-based discrete controller design for vehicle platoons subject to disturbances and saturation constraints. IEEE Transactions on Control Systems Technology, 28(3), 1066–1073.
Guevara, L., Jorquera, F., Walas, K., & Auat-Cheein, F. (2023). Robust control strategy for generalized N-trailer vehicles based on a dual-stage disturbance observer. Control Engineering Practice, 131, 105382.
Guo, G., & Yue, W. (2014). Sampled-data cooperative adaptive cruise control of vehicles with sensor failures. IEEE Transactions on Intelligent Transportation Systems, 15(6), 2404–2418.
Guo, H. Y., Liu, J., Dai, Q. K., Chen, H., Wang, Y. L., & Zhao, W. Z. (2020). A distributed adaptive triple-step nonlinear control for a connected automated vehicle platoon with dynamic uncertainty. IEEE Internet of Things Jounal, 7(5), 3861–3871.
Jiao, S. Y., Zhang, S. R., Li, Z. Z., Zhou, B., & Zhao, D. (2020). An improved car-following speed model considering speed of the lead vehicle, vehicle spacing, and driver’s sensitivity to them. Journal of Advanced Transportation, 2020, 1–13.
Li, S. B., Zheng, Y., Li, K. Q., Wu, Y. J., Hedrick, J. K., Gao, F., & Zhang, H. W. (2017). Dynamical modeling and distributed control of connected and automated vehicles: Challenges and opportunities. IEEE Intelligent Transportation Systems Magazine, 9(3), 46–58.
Li, Y. F., Chen, W. B., Peeta, S., & Wang, Y. B. (2020). Platoon control of connected multi-vehicle systems under v2x communications: Design and experiments. IEEE Transactions on Intelligent Transportation Systems, 21(5), 1891–1902.
Li, Y. F., Lv, Q. X., Zhu, H., Li, H. Q., Li, H. Q., Hu, S., Yu, S. Y., & Wang, Y. B. (2022). Variable time headway policy based platoon control for heterogeneous connected vehicles with external disturbances. IEEE Transactions on Intelligent Transportation Systems, 23(11), 21190–21200.
Li, Y. F., Tang, C. C., Li, K. Z., Peeta, S., He, X. Z., & Wang, Y. B. (2018). Nonlinear finite-time consensus- based connected vehicle platoon control under fixed and switching communication topologies. Transportation Research Part c: Emerging Technologies, 93, 525–543.
Ligthart, J. A. J., Ploeg, J., Semsar-kazerooni, E., Fusco, M., & Nijmeijer, H. (2018). Safety analysis of a vehicle equipped with cooperative adaptive cruise control. In 15th IFAC Symp. Control in Transportation Systems (CTS), Savona, Italy.
Luo, Q. Y., Nguyen, A. T., Fleming, J., & Zhang, H. (2021). Unknown input observer based approach for distributed tube-based model predictive control of heterogeneous vehicle platoons. IEEE Trans. Vehicular Technology, 70(4), 2930–2944.
Mao, X., Li, P., Weng, Z., & Zhao, J. (2023). Distributed tube model predictive control for string stability of heterogeneous vehicle platoons. Proceedings of the Institution of Mechanical Engineers, Part i: Journal of Systems and Control Engineering, 0959651823, 1173763.
Minderhoud, M. M., & Bovy, P. H. L. (2001). Extended time- to-collision measures for road traffic safety assessment. Accident Analysis and Prevention, 33(1), 89–97.
Mirabilio, M., Iovine, A., De Santis, E., Di Benedetto, M. D., & Pola, G. (2022). Mesoscopic controller for string stability of platoons with disturbances. IEEE Transactions on Control of Network Systems, 9(4), 1754–1766.
Mu, J. B., Feng, Y. H., & He, D. F. (2023). Distributed robust economic predictive control of heterogeneous vehicle platoons under bounded disturbances. Control and Decision, 38(5), 1386–1394.
Swaroop, D., & Hedrick, J. K. (1996). String stability of interconnected systems. IEEE Trans. Automatic Control, 41(3), 349–357.
Tu, Y., Wang, W., Li, Y., Xu, C. C., Xu, T., & Li, X. Q. (2019). Longitudinal safety impacts of cooperative adaptive cruise control vehicle’s degradation. Journal of Safety Research, 69, 177–192.
Vegamoor, V. K., Kalathil, D., Rathinam, S., & Darbha, S. (2019). Reducing time headway in homogeneous CACC vehicle platoons in the presence of packet drops. In Proc. 18th European Control Conf. (ECC), Naples, Italy.
Wang, B., Luo, Y. G., Zhong, Z. H., & Li, K. Q. (2022a). Risk reduction for safety of the intended functionality of CACC with complex uncertainties: A cooperative robust non-fragile fault tolerant strategy. Transportation Research Part c: Emerging Technologies, 144, 103885.
Wang, C. S., Wang, D., & Peng, Z. H. (2022b). Distributed output-feedback control of unmanned container transporter platooning with uncertainties and disturbances using event-triggered mechanism. IEEE Trans. Vehicular Technology, 71(1), 162–170.
Wang, J. G., Wong, W. C., Luo, X. Y., Li, X. L., & Guan, X. P. (2021a). Connectivity-maintained and specified-time vehicle platoon control systems with disturbance observer. International Journal of Robust and Nonlinear Control, 31(16), 7844–7861.
Wang, J. M., Luo, X. Y., Wang, L., Zuo, Z. Q., & Guan, X. P. (2020). Integral sliding mode control using a disturbance observer for vehicle platoons. IEEE Transactions on Industrial Electronics, 67(8), 6639–6648.
Wang, J. M., Luo, X. Y., Yan, J., & Guan, X. P. (2022c). Distributed integrated sliding mode control for vehicle platoons based on disturbance observer and multi power reaching law. IEEE Transactions on Intelligent Transportation Systems, 23(4), 3366–3376.
Wang, J. W., Ma, F. W., Yu, Y., Zhu, S., Gelbal, S. Y., Aksun-Guvenc, B., & Guvenc, L. (2021b). Optimization design of the decentralized multi-vehicle cooperative controller for freeway ramp entrance. International Journal of Automotive Technology, 22(3), 799–810.
Xie, G. Q., Li, Y. W., Han, Y. B., Xie, Y., Zeng, G., & Li, R. F. (2020). Recent advances and future trends for automotive functional safety design methodologies. IEEE Transactions on Industrial Informatics, 16(9), 5629–5642.
Yan, M. D., Ma, W. R., Zuo, L., & Yang, P. P. (2020). Distributed model predictive control for platooning of heterogeneous vehicles with multiple constraints and communication delays. Journal of Advanced Transportation, 2020, 1–16.
Yang, Z. F., Wang, Z. C., & Yan, M. (2021). An optimization design of adaptive cruise control system based on MPC and ADRC. Actuators, 10(6), 110.
Yue, W., & Wang, L. Y. (2017). Event-triggered autonomous platoon control against probabilistic sensor and actuator failures. Automatika, 58(1), 35–47.
Zhao, L. F., Cao, Q. X., Hu, Y. P., Xia, G., Hu, J. F., Wang, H. R., & Tian, B. (2022). Stability control of steer by wire system based on improved ADRC. Proceedings of the Institution of Mechanical Engineers, Part d: Journal of Automobile Engineering, 236(0–11), 2283–2293.
Zhao, L. F., Zhang, D. Z., Wang, H. R., Chen, W. W., Wang, Q. D., & Zhu, M. F. (2021). Study on longitudinal collision avoidance with human–machine cooperation based on improved safety distance model. Automotive Engineering, 43(4), 588–600.
Zheng, Y., Li, S. E., Li, K. Q., Borrelli, F., & Hedrick, J. K. (2017). Distributed model predictive control for heterogeneous vehicle platoons under unidirectional topologies. IEEE Transactions on Control Systems Technology, 25(3), 899–910.
Zheng, Y., Li, S. E., Wang, J. Q., Cao, D. P., & Li, K. Q. (2016). Stability and scalability of homogeneous vehicular platoon: Study on the influence of information flow topologies. IEEE Transactions on Intelligent Transportation Systems, 17(1), 14–26.
Zhou, A., Liu, Y. Y., Tenenboim, E., Agrawal, S., & Peeta, S. (2023). Car-Following behavior of human-driven vehicles in mixed-flow traffic: A driving simulator study. IEEE Transactions on Intelligent Vehicles, 8(4), 2661–2673.
Zhou, J., & Peng, H. (2005). Range policy of adaptive cruise control vehicles for improved flow stability and string stability. IEEE Transactions on Intelligent Transportation Systems, 6(2), 229–237.
Zhou, J. S., Tian, D. X., Sheng, Z. G., Duan, X. T., Qu, G. X., Zhao, D. Z., Cao, D. P., & Shen, X. M. (2022). Robust min–max model predictive vehicle platooning with causal disturbance feedback. IEEE Transactions on Intelligent Transportation Systems, 23(9), 15878–15897.
Zou, S. C., Zhao, W. Z., Wang, C. Y., Liang, W. H., & Chen, F. (2022). Tracking and synchronization control strategy of vehicle dual-motor steer-by-wire system via active disturbance rejection control. IEEE-ASME Transactions on Mechatronics, 28(1), 92–103.
Acknowledgements
The authors are grateful for the support provided by the National Natural Science Foundation of China (Grant No. U22A2046, 52275100). The National Key Research and Development Plan Project (Grant No. 2021YFE0116600). Hefei Natural Science Foundation (Grant No. 202325). Anhui Province Key Research and Development Program (Grant No. 202304a05020018).
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Appendix
Appendix
1.1 A Proof of Theorem 1
Define the spacing error as:
Then we obtain \({\ddot{e}}_{i}\left(t\right)={a}_{i-1}\left(t\right)-{a}_{i}(t)\), given that the accelerations of \({a}_{i}\left(t\right)\) and \({a}_{i-1}(t)\) are bounded, it indicates that \({\ddot{e}}_{i}\left(t\right)\in {\mathcal{L}}_{\infty }\), so \({\dot{e}}_{i}(t)\) is uniformly continuous. Besides,
Therefore, \({\dot{e}}_{i}(t)\in {\mathcal{L}}_{2}\). We have \(\underset{t\to \infty }{{\text{lim}}}{\dot{e}}_{i}(t)=0\) according to Lemma 1. Consequently, we have \({\dot{e}}_{i}(t)\in {\mathcal{L}}_{\infty }\). Similarly, we have \({e}_{i}(t)\in {\mathcal{L}}_{2}\). And we further have.
\(\underset{t\to \infty }{{\text{lim}}}{e}_{i}(t)=0\) based on Lemma 1.
If \(\widetilde{\xi }>0\), then \({\Vert {e}_{i}(0)\Vert }_{\infty }={{\text{sup}}}_{i}\left|{e}_{i}(0)\right|=0<\widetilde{\xi }\). In.
addition, consider that \(\underset{t\to \infty }{{\text{lim}}}{e}_{i}\left(t\right)=0\), \({e}_{i}\left(0\right)=0\), \({e}_{i}(t)\in {\mathcal{L}}_{2}\). Hence, \(\exists \zeta\),\(\varrho >0\),\(s.t.\) \({{\text{sup}}}_{i,t\in [0,\infty )}\left|{e}_{i}(t)\right|=\zeta <\varrho\).Therefore, the string stability is proved according to Definition 1.
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Fang, T., Wang, Q., Zhao, L. et al. Local Disturbance Cooperative Control of Heterogeneous Vehicle Platoon Based on Situation Assessment. Int.J Automot. Technol. 25, 183–200 (2024). https://doi.org/10.1007/s12239-024-00008-8
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DOI: https://doi.org/10.1007/s12239-024-00008-8