Scilight Press

Author Information

Received: 25 Apr 2023 | Accepted: 19 Sep 2023 | Published: 25 Sep 2023

Abstract

Keywords

multi-vehicle cooperative control | cooperative adaptive cruise control | distributed control

References 

• 1.
  Shladover, S.E. PATH at 20—History and major milestones. IEEE Transactions on Intelligent Transportation Systems 2007, 8(4), 584–592.
• 2.
  Chang, K.S.; Li, W.; Devlin, P.; et al. Experimentation with a vehicle platoon control system. In Vehicle Navigation and Information Systems Conference. IEEE: Piscataway, NJ, USA, 1991, Vol. 2, pp. 1117–1124.
• 3.
  Milanés, V.; Shladover, S.E.; Spring, J.; et al. Cooperative adaptive cruise control in real traffic situations. IEEE Transactions on Intelligent Transportation Systems 2013, 15(1), 296–305.
• 4.
  Liu, H.; Kan, X.; Wei, D.; et al. Using cooperative adaptive cruise control (CACC) to formhigh-performance vehicle streams. 2018. Available online: https://path.berkeley.edu/sites/default/files/general/simulation_methodology_reviewdraft.pdf (Accessed on 25 April 2023).
• 5.
  Shladover, S.; Lu, X.Y.; Yang, S.; et al. Cooperative adaptive cruise control (CACC) for partially automated truck platooning. 2018. Available online: https://escholarship.org/content/qt260060w4/qt260060w4.pdf (Accessed on 25 April 2023).
• 6.
  Schulze, M. Chauffeur-the european way towards an automated highway system. In Mobility for Everyone. 4th World Congress on Intelligent Transport Systems, 21–24 October 1997, Berlin, Germany. (Paper No. 2311).
• 7.
  Maiti, S.; Winter, S.; Kulik, L. A conceptualization of vehicle platoons and platoon operations. Transportation Research Part C: Emerging Technologies 2017, 80, 1–19.
• 8.
  Larburu, M.; Urquiza, A.; Sanchez, J. Safe Road Trains for the Environment (SARTRE): Validation of SARTRE Platoon service and the SARTRE HMI. In 19th ITS World CongressERTICO-ITS EuropeEuropean CommissionITS AmericaITS Asia-Pacific. 22–26 October 2012, Vienna, Austria.
• 9.
  Bergenhem, C.; Huang, Q.; Benmimoun, A.; et al. Challenges of platooning on public motorways. In 17th World Congress on Intelligent Transport Systems. 2010, pp. 1–12. Available online: https://trimis.ec.europa.eu/sites/default/files/project/documents/20130204_115543_96121_SARTRE_ConferencePaper1.pdf (Accessed on 25 April 2023).
• 10.
  Adolfson, M. Cooperative dynamic formation of platoons for safe and energy-optimized goods transportation. In 93rd Annual Meeting of the Transportation Research Board, Washington, DC, USA (Oral presentation), 2014, p. 42. Available online: https://unece.org/DAM/trans/doc/2014/wp29grrf/GRRF-76-43e.pdf (Accessed on 25 April 2023).
• 11.
  Pezzano, A.; IDIADA, P.D. ENabling SafE Multi-Brand pLatooning for Europe. 2020. Available online: https://platooningensemble.eu/storage/uploads/documents/2023/03/10/ENSEMBLE-D2.14-Final_version_Hazard_Analysis_and_Risk_Assessment_and_Functional_Safety_Concept_FINAL.pdf (Accessed on 25 April 2023).
• 12.
  Willemsen, D.M.; Schmeitz, A.J.; Mascalchi, E. EU ENSEMBLE Project: Specification of an Interoperable Solution for a Support Function for Platooning. IEEE Transactions on Intelligent Transportation Systems 2023, 24(6), 5705–5718.
• 13.
  Soto, I.; Calderon, M.; Amador, O.; et al. A survey on road safety and traffic efficiency vehicular applications based on C-V2X technologies. Vehicular Communications 2022, 33, 100428.
• 14.
  Lioris, J.; Pedarsani, R.; Tascikaraoglu, F.Y.; et al. Platoons of connected vehicles can double throughput in urban roads. Transportation Research Part C: Emerging Technologies 2017, 77, 292–305.
• 15.
  Lee, J.; Huang, H.; Wang, J.; et al. Road safety under the environment of intelligent connected vehicles. Accident Analysis & Prevention 2022, 170, 106645.
• 16.
  Kopelias, P.; Demiridi, E.; Vogiatzis, K.; et al. Connected & autonomous vehicles–Environmental impacts–A review. Science of the Total Environment 2020, 712, 135237.
• 17.
  Qu, D.Y.; Zhao, Z.X.; Song, H.; et al. (). Design of Vehicle–Road Cooperative Assistant Decision System for Active Safety at Intersections. Journal of transportation engineering, Part A: Systems 2022, 148(5), 04022022.
• 18.
  Wang, J.; Ma, F.; Yu, Y.; et al. Optimization design of the decentralized multi-vehicle cooperative controller for freeway ramp entrance. International Journal of Automotive Technology 2021, 22, 799–810.
• 19.
  Ploeg, J.; Scheepers, B.T.; Van Nunen, E.; et al. (2011, October). Design and experimental evaluation of cooperative adaptive cruise control. In 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC), 05–07 October 2011, Washington, DC, USA, pp. 260–265. IEEE: Piscataway, NJ, USA.
• 20.
  Naus, G.J.; Vugts, R.P.; Ploeg, J.; et al. String-stable CACC design and experimental validation: A frequency-domain approach. IEEE Transactions on Vehicular Technology 2010, 59(9), 4268–4279.
• 21.
  Knorn, S.; Donaire, A.; Agüero, J.C.; et al. Passivity-based control for multi-vehicle systems subject to string constraints. Automatica 2014, 50(12), 3224–3230.
• 22.
  Wang, Z.; Wu, G.; Barth, M.J. (2018, November). A review on cooperative adaptive cruise control (CACC) systems: Architectures, controls, and applications. In 2018 21st International Conference on Intelligent Transportation Systems (ITSC). IEEE: Piscataway, NJ, USA, pp. 2884–2891.
• 23.
  Zheng, Y.; Li, S.E.; Wang, J.; et al. Stability and scalability of homogeneous vehicular platoon: Study on the influence of information flow topologies. IEEE Transactions on Intelligent Transportation Systems 2015, 17(1), 14–26.
• 24.
  Li, S.E.; Zheng, Y.; Li, K.; et al. (, June). An overview of vehicular platoon control under the four-component framework. In 2015 IEEE Intelligent Vehicles Symposium (IV). IEEE: Piscataway, NJ, USA, 2015, pp. 286–291.
• 25.
  He, Y.; Ciuffo, B.; Zhou, Q.; et al. Adaptive cruise control strategies implemented on experimental vehicles: A review. IFAC-PapersOnLine 2019, 52(5), 21–27.
• 26.
  Rajamani, R. Vehicle Dynamics and Control. Springer Science & Business Media: Berlin, Germany, 2011.
• 27.
  Xiao, L.; Gao, F. A comprehensive review of the development of adaptive cruise control systems. Vehicle System Dynamics 2010, 48(10), 1167–1192.
• 28.
  Pananurak, W.; Thanok, S.; Parnichkun, M. Adaptive cruise control for an intelligent vehicle. In 2008 IEEE International Conference on Robotics and Biomimetics. IEEE: Piscataway, NJ, USA, 2009, pp. 1794–1799.
• 29.
  Chen, J.; Zhou, Y.; Liang, H. Effects of ACC and CACC vehicles on traffic flow based on an improved variable time headway spacing strategy. IET Intelligent Transport Systems 2019, 13(9), 1365–1373.
• 30.
  Swaroop, D.; Hedrick, J.K.; Chien, C.C.; et al. A comparision of spacing and headway control laws for automatically controlled vehicles1. Vehicle System Dynamics 1994, 23(1), 597–625.
• 31.
  Zhou, J.; Peng, H. Range policy of adaptive cruise control vehicles for improved flow stability and string stability. IEEE Transactions on Intelligent Transportation Systems 2005, 6(2), 229–237.
• 32.
  Weinberger, M.; Winner, H.; Bubb, H. Adaptive cruise control field operational test—the learning phase. JSAE Review 2001, 22(4), 487–494.
• 33.
  Prestl, W.; Sauer, T.; Steinle, J.; et al. The BMW active cruise control ACC. SAE Technical Paper 2000, No. 2000-01-0344.
• 34.
  Kumar, R.; Pathak, R. Adaptive cruise control-towards a safer driving experience. International Journal of Scientific and Engineering Research 2012, 3(8), 3–7.
• 35.
  Kesting, A.; Treiber, M.; Schönhof, M.; et al. Jam-avoiding adaptive cruise control (ACC) and its impact on traffic dynamics. In Traffic and Granular Flow’05. Springer Berlin Heidelberg, Germany, 2007, pp. 633–643.
• 36.
  Venhovens, P.; Naab, K.; Adiprasito, B. (). Stop and go cruise control. SAE Technical Paper 2000, No. 2000-05-0368.
• 37.
  Zhang, Y.; Lin, Q.; Wang, J.; et al. Lane-change intention estimation for car-following control in autonomous driving. IEEE Transactions on Intelligent Vehicles 2018, 3(3), 276–286.
• 38.
  Miyata, S.; Nakagami, T.; Kobayashi, S.; et al. Improvement of adaptive cruise control performance. EURASIP Journal on Advances in Signal Processing 2010, 2010, 1–8.
• 39.
  Milanés, V.; Shladover, S.E. Modeling cooperative and autonomous adaptive cruise control dynamic responses using experimental data. Transportation Research Part C: Emerging Technologies 2014, 48, 285–300.
• 40.
  Wischhof, L.; Ebner, A.; Rohling, H. Information dissemination in self-organizing intervehicle networks. IEEE Transactions on Intelligent Transportation Systems 2005, 6(1), 90–101.
• 41.
  Uhlemann, E. Connected-vehicles applications are emerging [connected vehicles]. IEEE Vehicular Technology Magazine 2016, 11(1), 25–96.
• 42.
  Xiao, L.; Wang, M.; Schakel, W.; et al. Unravelling effects of cooperative adaptive cruise control deactivation on traffic flow characteristics at merging bottlenecks. Transportation research part C: Emerging Technologies 2018, 96, 380–397.
• 43.
  Porfyri, K.N.; Mintsis, E.; Mitsakis, E. Assessment of ACC and CACC systems using SUMO. EPiC Series in Engineering 2018, 2, 82–93.
• 44.
  Xiao, L.; Wang, M.; Van Arem, B. Realistic car-following models for microscopic simulation of adaptive and cooperative adaptive cruise control vehicles. Transportation Research Record 2017, 2623(1), 1–9.
• 45.
  Stanger, T.; del Re, L. A model predictive cooperative adaptive cruise control approach. In 2013 American control conference. IEEE: Piscataway, NJ, USA, 2013, pp. 1374–1379.
• 46.
  Wang, C.; Gong, S.; Zhou, A.; et al. Cooperative adaptive cruise control for connected autonomous vehicles by factoring communication-related constraints. Transportation Research Part C: Emerging Technologies 2020, 113, 124–145.
• 47.
  Gong, S.; Zhou, A.; Peeta, S. Cooperative adaptive cruise control for a platoon of connected and autonomous vehicles considering dynamic information flow topology. Transportation Research Record 2019, 2673(10), 185–198.
• 48.
  Gong, L.; Luo, L.; Wang, H.; et al. Adaptive cruise control design based on fuzzy-PID. In 2010 International Conference on E-Product E-Service and E-Entertainment. IEEE: Piscataway, NJ, USA, 2010, pp. 1–4.
• 49.
  Yang, J.; Liu, X.; Liu, S.; et al. Longitudinal tracking control of vehicle platooning using DDPG-based PID. In 2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI). IEEE: Piscataway, NJ, USA, 2020, pp. 656–661.
• 50.
  Wang, J.; Hu, X. Distributed consensus in multi-vehicle cooperative control: Theory and Applications (Ren, W. and Beard, RW; 2008)[Book Shelf]. IEEE Control Systems Magazine 2010, 30(3), 85–86.
• 51.
  Wang, L.Y.; Syed, A.; Yin, G.G.; et al. Control of vehicle platoons for highway safety and efficient utility: Consensus with communications and vehicle dynamics. Journal of Systems Science and Complexity 2014, 27, 605–631.
• 52.
  Di Bernardo, M.; Salvi, A.; Santini, S. Distributed consensus strategy for platooning of vehicles in the presence of time-varying heterogeneous communication delays. IEEE Transactions on Intelligent Transportation Systems 2014, 16(1), 102–112.
• 53.
  Li, Y.; Tang, C.; Li, K.; et al. Consensus-based cooperative control for multi-platoon under the connected vehicles environment. IEEE Transactions on Intelligent Transportation Systems 2018, 20(6), 2220–2229.
• 54.
  Hu, J.; Bhowmick, P.; Arvin, F.; et al. Cooperative control of heterogeneous connected vehicle platoons: An adaptive leader-following approach. IEEE Robotics and Automation Letters 2020, 5(2), 977–984.
• 55.
  Li, Y.; Tang, C.; Peeta, S.; et al. Nonlinear consensus-based connected vehicle platoon control incorporating car-following interactions and heterogeneous time delays. IEEE Transactions on Intelligent Transportation Systems 2018, 20(6), 2209–2219.
• 56.
  Wang, W.; Wang, C.; Wang, Z.; et al. (). Nonlinear consensus-based autonomous vehicle platoon control under event-triggered strategy in the presence of time delays. Applied Mathematics and Computation 2021, 404, 126246.
• 57.
  Li, Y.; Wu, Y.; He, S. Distributed consensus control for a group of autonomous marine vehicles with nonlinearity and external disturbances. Neurocomputing 2021, 443, 380–387.
• 58.
  Yang, P.; Tang, Y.; Yan, M.; et al. Consensus based control algorithm for nonlinear vehicle platoons in the presence of time delay. International Journal of Control, Automation and Systems 2019, 17, 752–764.
• 59.
  Wang, Z.; Wu, G.; Hao, P.; et al. Developing a platoon-wide eco-cooperative adaptive cruise control (CACC) system. In 2017 IEEE Intelligent Vehicles Symposium (IV). IEEE: Piscataway, NJ, USA, 2017, pp. 1256–1261.
• 60.
  Li, Y.; Tang, C.; Li, K.; et al. Nonlinear finite-time consensus-based connected vehicle platoon control under fixed and switching communication topologies. Transportation Research Part C: Emerging Technologies 2018, 93, 525–543.
• 61.
  Yu, G.; Wong, P.K.; Huang, W.; et al. Distributed adaptive consensus protocol for connected vehicle platoon with heterogeneous time-varying delays and switching topologies. IEEE Transactions on Intelligent Transportation Systems 2022, 23(10), 17620–17631.
• 62.
  Yang, H.; Rakha, H.; Ala, M.V. Eco-cooperative adaptive cruise control at signalized intersections considering queue effects. IEEE Transactions on Intelligent Transportation Systems 2016, 18(6), 1575–1585.
• 63.
  Turri, V.; Besselink, B.; Johansson, K.H. Cooperative look-ahead control for fuel-efficient and safe heavy-duty vehicle platooning. IEEE Transactions on Control Systems Technology 2016, 25(1), 12–28.
• 64.
  Van De Hoef, S.; Johansson, K.H.; Dimarogonas, D.V. Fuel-efficient en route formation of truck platoons. IEEE Transactions on Intelligent Transportation Systems 2017, 19(1), 102–112.
• 65.
  Zohdy, I.H.; Rakha, H. Game theory algorithm for intersection-based cooperative adaptive cruise control (CACC) systems. In 2012 15th International IEEE Conference on Intelligent Transportation Systems. IEEE: Piscataway, NJ, USA, 2012, pp. 1097–1102.
• 66.
  Kianfar, R.; Falcone, P.; Fredriksson, J. A receding horizon approach to string stable cooperative adaptive cruise control. In 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC). IEEE: Piscataway, NJ, USA, 2011, pp. 734–739.
• 67.
  Bu, F.; Tan, H.S.; Huang, J. Design and field testing of a cooperative adaptive cruise control system. In Proceedings of the 2010 American Control Conference. IEEE: Piscataway, NJ, USA, 2010, pp. 4616–4621.
• 68.
  Tapli, T.; Akar, M. Cooperative adaptive cruise control algorithms for vehicular platoons based on distributed model predictive control. In 2020 IEEE 16th International Workshop on Advanced Motion Control (AMC). IEEE: Piscataway, NJ, USA, 2020, pp. 305–310.
• 69.
  Nie, G.; Xie, B.; Hao, Z.; et al. A distributed model predictive control approach to cooperative adaptive cruise control of the heterogeneous platoon. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 2022, 236(14), 3153–3167.
• 70.
  Farag, A.; AbdelAziz, O.M.; Hussein, A.; et al. Reinforcement Learning Based Approach for Multi-Vehicle Platooning Problem with Nonlinear Dynamic Behavior. 2020. Available online: https://www.researchgate.net/profile/Amr-Ramadan-6/publication/349313418_Reinforcement_Learning_Based_Approach_for_Multi-Vehicle_Platooning_Problem_with_Nonlinear_Dynamic_Behavior/links/602a65ec92851c4ed57317a3/Reinforcement-Learning-Based-Approach-for-Multi-Vehicle-Platooning-Problem-with-Nonlinear-Dynamic-Behavior.pdf (Accessed on 25 April 2023).
• 71.
  Lu, S.; Cai, Y.; Chen, L.; et al. A sharing deep reinforcement learning method for efficient vehicle platooning control. IET Intelligent Transport Systems 2022, 16(12), 1697–1709.
• 72.
  Peake, A.; McCalmon, J.; Raiford, B.; et al. Multi-agent reinforcement learning for cooperative adaptive cruise control. In 2020 IEEE 32nd International Conference on Tools with Artificial Intelligence (ICTAI). IEEE: Piscataway, NJ, USA, 2020, pp. 15–22.
• 73.
  Shi, H.; Zhou, Y.; Wu, K.; et al. Connected automated vehicle cooperative control with a deep reinforcement learning approach in a mixed traffic environment. Transportation Research Part C: Emerging Technologies 2021, 133, 103421.
• 74.
  Feng, S.; Zhang, Y.; Li, S.E.; et al. String stability for vehicular platoon control: Definitions and analysis methods. Annual Reviews in Control 2019, 47, 81–97.
• 75.
  Naus, G.J.; Vugts, R.P.; Ploeg, J.; et al. String-stable CACC design and experimental validation: A frequency-domain approach. IEEE Transactions on Vehicular Technology 2010, 59(9), 4268–4279.
• 76.
  Khatir, M.E.; Davidson, E.J. Bounded stability and eventual string stability of a large platoon of vehicles using non-identical controllers. In 2004 43rd IEEE Conference on Decision and Control (CDC)(IEEE Cat. No. 04CH37601). IEEE: Piscataway, NJ, USA, 2004, Vol. 1, pp. 1111–1116.
• 77.
  Jin, I.G.; Orosz, G. Optimal control of connected vehicle systems with communication delay and driver reaction time. IEEE Transactions on Intelligent Transportation Systems 2016, 18(8), 2056–2070.
• 78.
  Swaroop, D.; Hedrick, J. K. String stability of interconnected systems. IEEE Transactions on Automatic Control 1996, 41(3), 349–357.
• 79.
  Mokogwu, C.N.; Hashtrudi-Zaad, K. Energy-based analysis of string stability in vehicle platoons. IEEE Transactions on Vehicular Technology 2022, 71(6), 5915–5929.
• 80.
  Shladover, S.E.; Nowakowski, C.; Lu, X.Y.; et al. Cooperative adaptive cruise control: Definitions and operating concepts. Transportation Research Record 2015, 2489(1), 145–152.
• 81.
  Xing, H.; Ploeg, J.; Nijmeijer, H. Compensation of communication delays in a cooperative ACC system. IEEE Transactions on Vehicular Technology 2019, 69(2), 1177–1189.
• 82.
  Zhang, Y.; Bai, Y.; Wang, M.; et al. Cooperative adaptive cruise control with robustness against communication delay: An approach in the space domain. IEEE Transactions on Intelligent Transportation Systems 2020, 22(9), 5496–5507.
• 83.
  Maxim, A.; Pauca, O.; Caruntu, C.F.; et al. Distributed model predictive control algorithm with time-varying communication delays for a CACC vehicle platoon. In 2020 24th International Conference on System Theory, Control and Computing (ICSTCC). IEEE: Piscataway, NJ, USA, 2020, pp. 775–780.
• 84.
  Ploeg, J.; van de Wouw, N.; Nijmeijer, H. Fault tolerance of cooperative vehicle platoons subject to communication delay. IFAC-PapersOnLine 2015, 48(12), 352–357.
• 85.
  Tian, B.; Deng, X.; Xu, Z.; et al. Modeling and numerical analysis on communication delay boundary for CACC string stability. IEEE Access 2019, 7, 168870–168884.
• 86.
  Ploeg, J.; Semsar-Kazerooni, E.; Lijster, G.; et al. Graceful degradation of CACC performance subject to unreliable wireless communication. In 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013). IEEE: Piscataway, NJ, USA, 2013, pp. 1210–1216.
• 87.
  Acciani, F.; Frasca, P.; Heijenk, G.; et al. Stochastic string stability of vehicle platoons via cooperative adaptive cruise control with lossy communication. IEEE Transactions on Intelligent Transportation Systems 2021, 23(8), 10912–10922.
• 88.
  Wu, C.; Lin, Y.; Eskandarian, A. Cooperative adaptive cruise control with adaptive Kalman filter subject to temporary communication loss. IEEE Access 2019, 7, 93558–93568.
• 89.
  Tu, Y.; Wang, W.; Li, Y.; et al. Longitudinal safety impacts of cooperative adaptive cruise control vehicle's degradation. Journal of Safety Research 2019, 69, 177–192.
• 90.
  Lei, C.; Van Eenennaam, E.M.; Wolterink, W.K.; et al. Impact of packet loss on CACC string stability performance. In 2011 11th International Conference on ITS Telecommunications. IEEE: Piscataway, NJ, USA, 2011, pp. 381–386.
• 91.
  Razzaghpour, M.; Shahram, S.; Valiente, R.; et al. Impact of communication loss on mpc based cooperative adaptive cruise control and platooning. In 2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall). IEEE: Piscataway, NJ, USA, 2021, pp. 1–7.
• 92.
  Shladover, S.E. Truck automation operational concept alternatives. In 2010 IEEE Intelligent Vehicles Symposium. IEEE: Piscataway, NJ, USA, 2010, pp. 1072–1077.
• 93.
  Xie, S.; Hu, J.; Bhowmick, P.; et al. Distributed motion planning for safe autonomous vehicle overtaking via artificial potential field. IEEE Transactions on Intelligent Transportation Systems 2022, 23(11), 21531–21547.
• 94.
  Wang, D.; Hu, M.; Wang, Y.; et al. Model predictive control–based cooperative lane change strategy for improving traffic flow. Advances in Mechanical Engineering 2016, 8(2), 1687814016632992.
• 95.
  Shi, Y.; Lv, L.; Qi, Y.; et al. A Cooperative Control Algorithm for Real-time On-ramp Merging of Connected and Automated Vehicles. In 2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD). IEEE: Piscataway, NJ, USA, 2022, pp. 659–664.
• 96.
  Xie, S.; Hu, J.; Ding, Z.; et al. Cooperative adaptive cruise control for connected autonomous vehicles using spring damping energy model. IEEE Transactions on Vehicular Technology 2022, 72(3), 2974–2987.
• 97.
  Kneissl, M.; Madhusudhanan, A.K.; Molin, A.; et al. A multi-vehicle control framework with application to automated valet parking. IEEE Transactions on Intelligent Transportation Systems 2020, 22(9), 5697–5707.
• 98.
  Guler, S.I.; Menendez, M.; Meier, L. Using connected vehicle technology to improve the efficiency of intersections. Transportation Research Part C: Emerging Technologies 2014, 46, 121–131.
• 99.
  Kunze, R.; Ramakers, R.; Henning, K.; et al. Organization and operation of electronically coupled truck platoons on German motorways. In Automation, communication and cybernetics in science and engineering 2009/2010. Springer Berlin Heidelberg: Germany, 2011, pp. 427–439.
• 100.
  Tsugawa, S. Results and issues of an automated truck platoon within the energy ITS project. In 2014 IEEE Intelligent Vehicles Symposium Proceedings. IEEE: Piscataway, NJ, USA, 2014, pp. 642–647.
• 101.
  Yoshida, J.; Sugimachi, T.; Fukao, T.; et al. Autonomous driving of a truck based on path following control. In Proc. 10th Int. Symposium on Advanced Vehicle Control (CD-ROM). 2010.
• 102.
  Sugimachi, T.; Fukao, T.; Suzuki, Y.; et al. Development of autonomous platooning system for heavy-duty trucks. IFAC Proceedings Volumes 2013, 46(21), 52–57.
• 103.
  Ellwanger, S.; Wohlfarth, E. Truck platooning application. In 2017 IEEE Intelligent Vehicles Symposium (IV). IEEE: Piscataway, NJ, USA, 2017, pp. 966–971.
• 104.
  Nowakowski, C.; Shladover, S.E.; Lu, X.Y.; et al. Cooperative adaptive cruise control (CACC) for truck platooning: Operational concept alternatives. 2015.
• 105.
  Foreman, C.; Keen, M.; Petrella, M.; et al. FHWA Research and Technology Evaluation TechBrief: Truck Platooning (No. FHWA-HRT-22-007). United States. Federal Highway Administration. Research and Technology Evaluation. 2021.
• 106.
  Shawky, M. Factors affecting lane change crashes. IATSS Research 2020, 44(2), 155–161.
• 107.
  Sun, M.; Chen, Z.; Li, H.; et al. Cooperative Lane-Changing Strategy for Intelligent Vehicles. In 2021 40th Chinese Control Conference (CCC). IEEE: Piscataway, NJ, USA, 2021, pp. 6022–6027.
• 108.
  Ni, J.; Han, J.; Dong, F. Multivehicle cooperative lane change control strategy for intelligent connected vehicle. Journal of Advanced Transportation 2020, 2020, 1–10.
• 109.
  Kim, H.; Borrelli, F. Facilitating Cooperative and Distributed Multi-Vehicle Lane Change Maneuvers. arXiv preprint 2023, arXiv:2301.04316.
• 110.
  Li, T.; Wu, J.; Chan, C.Y.; et al. A cooperative lane change model for connected and automated vehicles. IEEE Access 2020, 8, 54940–54951.
• 111.
  Luo, Y.; Yang, G.; Xu, M.; et al. Cooperative lane-change maneuver for multiple automated vehicles on a highway. Automotive Innovation 2019, 2, 157–168.
• 112.
  Zhang, S.; Deng, G.; Yang, E.; et al. Optimal Vehicle Lane Change Trajectory Planning in Multi-Vehicle Traffic Environments. Applied Sciences 2022, 12(19), 9662.
• 113.
  Hu, Z.; Huang, J.; Yang, Z.; et al. Embedding robust constraint-following control in cooperative on-ramp merging. IEEE Transactions on Vehicular Technology 2021, 70(1), 133–145.
• 114.
  Chen, Y.; Weniuan, E.; Wang, X.; et al. Multi-vehicle Cooperative Confluence Strategy in Freeway Merging Area under New Mixed Traffic Environment. In 2022 5th International Conference on Intelligent Autonomous Systems (ICoIAS). IEEE: Piscataway, NJ, USA, 2022, pp. 358–363.
• 115.
  Goli, M.; Eskandarian, A. MPC-based lateral controller with look-ahead design for autonomous multi-vehicle merging into platoon. In 2019 American Control Conference (ACC). IEEE: Piscataway, NJ, USA, 2019, pp. 5284–5291.
• 116.
  Hang, P.; Lv, C.; Huang, C.; et al. Cooperative decision making of connected automated vehicles at multi-lane merging zone: A coalitional game approach. IEEE Transactions on Intelligent Transportation Systems 2021, 23(4), 38293841.
• 117.
  Zhang, L.; Wang, Y.; Zhu, H. Theory and experiment of cooperative control at multi-intersections in intelligent connected vehicle environment: review and perspectives. Sustainability 2022, 14(3), 1542.
• 118.
  Deng, Z.; Shi, Y.; Han, Q.; et al. A conflict duration graph-based coordination method for connected and automated vehicles at signal-free intersections. Applied Sciences 2020, 10(18), 6223.
• 119.
  Yu, J.; Jiang, F.; Luo, Y.; et al. Networked predictive control method of multi-vehicle cooperative control at communication-constrained unsignalized multi-intersection. IET Intelligent Transport Systems 2023, 17(5), 929–942.
• 120.
  Li, N.; Yao, Y.; Kolmanovsky, I.; et al. Game-theoretic modeling of multi-vehicle interactions at uncontrolled intersections. IEEE Transactions on Intelligent Transportation Systems 2020, 23(2), 1428–1442.
• 121.
  Cai, M.; Xu, Q.; Chen, C.; et al. Multi-lane unsignalized intersection cooperation with flexible lane direction based on multi-vehicle formation control. IEEE Transactions on Vehicular Technology 2022, 71(6), 5787–5798.
• 122.
  Cheng, Y.; Zhao, Y.; Zhang, R.; et al. Conflict resolution model of automated vehicles based on multi-vehicle cooperative optimization at intersections. Sustainability 2022, 14(7), 3838.
• 123.
  Ge, Q.; Sartoretti, G.; Duan, J.; et al. Distributed Model Predictive Control of Connected Multi-Vehicle Systems at Unsignalized Intersections. In 2022 IEEE International Conference on Unmanned Systems (ICUS). IEEE: Piscataway, NJ, USA, 2022, pp. 1466–1472.
• 124.
  Wang, W.; Song, Y.; Zhang, J.; et al. Automatic parking of vehicles: A review of literatures. International Journal of Automotive Technology 2014, 15, 967–978.
• 125.
  Yamazaki, A.; Izumi, Y.; Yamane, K.; et al. Development of control technology for controlling automated valet parking. Denso Ten Technical Review 2019, 3, 18–23.
• 126.
  Kessler, T.; Knoll, A. Multi vehicle trajectory coordination for automated parking. In 2017 IEEE Intelligent Vehicles Symposium (IV). IEEE: Piscataway, NJ, USA, 2017, pp. 661–666.
• 127.
  Wu, B.; Qian, L.; Lu, M.; et al. Optimal control problem of multi-vehicle cooperative autonomous parking trajectory planning in a connected vehicle environment. IET Intelligent Transport Systems 2019, 13(11), 1677–1685.
• 128.
  Li, B.; Zhang, Y.; Shao, Z.; et al. Simultaneous versus joint computing: A case study of multi-vehicle parking motion planning. Journal of Computational Science 2017, 20, 30–40.
• 129.
  Mrazovic, P.; Eser, E.; Ferhatosmanoglu, H.; et al. Multi-vehicle route planning for efficient urban freight transport. In 2018 International Conference on Intelligent Systems (IS). IEEE: Piscataway, NJ, USA, 2018, pp. 744–753.
• 130.
  Kneissl, M.; vom Dorff, S.; Molin, A.; et al. Mixed-reality testing of multi-vehicle coordination in an automated valet parking environment. IFAC-PapersOnLine 2020, 53(2), 17564–17571.
• 131.
  Alipour-Fanid, A.; Dabaghchian, M.; Zeng, K. Impact of jamming attacks on vehicular cooperative adaptive cruise control systems. IEEE Transactions on Vehicular Technology 2020, 69(11), 12679–12693.
• 132.
  Du, L.; Chen, L.; Hou, X.; et al. Cooperative vehicle localization base on extended Kalman filter in intelligent transportation system. In 2019 28th Wireless and Optical Communications Conference (WOCC). IEEE: Piscataway, NJ, USA, 2019, pp. 1–5.
• 133.
  Zhang, S.; Lu, C.; Jiang, S.; et al. An unmanned intelligent transportation scheduling system for open-pit mine vehicles based on 5G and big data. IEEE Access 2020, 8, 135524–135539.
• 134.
  Yang, M.; Wei, S.; Jiang, R.; et al. Single-message-based cooperative authentication scheme for intelligent transportation systems. Computers & Electrical Engineering 2021, 96, 107390.
• 135.
  Wu, S.; Wang, H.; Yu, W.; et al. A new SOTIF scenario hierarchy and its critical test case generation based on potential risk assessment. In 2021 IEEE 1st International Conference on Digital Twins and Parallel Intelligence (DTPI). IEEE: Piscataway, NJ, USA, 2021, pp. 399–409.
• 136.
  Zhou, R.; Liu, Y.; Zhang, K.; et al. Genetic algorithm-based challenging scenarios generation for autonomous vehicle testing. IEEE Journal of Radio Frequency Identification 2022, 6, 928–933.