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Platoon-actuated variable area mainstream traffic control for bottleneck decongestion. (English) Zbl 1501.93010

Summary: In this paper a platoon-actuated mainstream traffic control is proposed to decongest bottlenecks due to recurrent and nonrecurrent events. Indeed, differently from traditional mainstream control strategies, i.e., control strategies applied with fixed actuators, platoon-actuated control can be applied at any location on the freeway. In this work, the control actions to be communicated to the platoons, i.e., speed and configuration, are defined by means of a predictive control law based on traffic and platoon state detected in an area identified immediately upstream of the bottleneck. The main peculiarity of this scheme is that the size of the controlled area is dynamically adjusted based on the predicted congestion at the bottleneck. This approach keeps the control law computation burden low, while not sacrificing much control performance. Specifically, the number of platoons to be controlled and the time at which the platoons begin to be controlled depend on the size of the controlled area. Simulation results reported in the paper show the effectiveness of the proposed scheme, eliminating from 60% to 80% of the delay incurred from congestion compared with the uncontrolled case, depending on the level of traffic.

MSC:

93A16 Multi-agent systems
90B20 Traffic problems in operations research

References:

[1] Alam, A.; Besselink, B.; Turri, V.; Mårtensson, J.; Johansson, K. H., Heavy-duty vehicle platooning for sustainable freight transportation: a cooperative method to enhance safety and efficiency, IEEE Control Systems, volume 35, 34-56 (2015)
[2] Bhoopalam, A. K.; Agatz, N.; Zuidwijk, R., Planning of truck platoons: A literature review and directions for future research, Transportation Research B, volume 107, 212-228 (2018)
[3] Carlson, R. C.; Papamichail, I.; Papageorgiou, M., Local feedback-based mainstream traffic flow control on motorways using variable speed limits, IEEE Transactions on intelligent transportation systems, volume 12, 1261-1276 (2011)
[4] Čičić, M.; Johansson, K. H., Stop-and-go wave dissipation using accumulated controlled moving bottlenecks in multi-class CTM framework, IEEE 58th Conference on Decision and Control, 3146-3151 (2019)
[5] M. Čičić, X. Xiong, L. Jin, K.H. Johansson, Coordinating vehicle platoons for highway bottleneck decongestion and throughput improvement, 2021, IEEE Transactions on Intelligent Transportation Systems
[6] Liang, K.-Y.; Mårtensson, J.; Johansson, K. H., When is it fuel efficient for a heavy duty vehicle to catch up with a platoon, IFAC Proceedings Volumes, volume 46, 738-743 (2013)
[7] Lu, X. Y.; Shladover, S. E., Review of variable speed limits and advisories: theory, algorithms, and practice, Transportation research record, volume 1, 2423 (2014)
[8] Pasquale, C.; Sacone, S.; Siri, S.; Ferrara, A., A new micro-macro METANET model for platoon control in freeway traffic networks, Proc. of the 21th IEEE Intelligent Transportation Systems Conference, 1481-1486 (2018)
[9] Piacentini, G.; Pasquale, C.; Sacone, S.; Siri, S.; Ferrara, A., Multiple moving bottlenecks for traffic control in freeway systems, In Proc. of European Control Conference, 3662-3667 (2019)
[10] Raposo, M. A., The future of road transport - implications of automated, connected, low-carbon and shared mobility, EUR 29748 EN (2019), Publications Office of the European Union: Publications Office of the European Union Luxembourg
[11] S. Sacone, C. Pasquale, S. Siri, A. Ferrara, Centralized and decentralized schemes for platoon control in freeway traffic systems, 60th IEEE Conference on Decision and Control, 2021, Austin, USA, December 13-15. pp. 2665-2670.
[12] Simoni, M. D.; Claudel, C. G., A fast simulation algorithm for multiple moving bottlenecks and applications in urban freight traffic management, Transportation Research Part B, volume 104, 238-255 (2017)
[13] Siri, S.; Pasquale, C.; Sacone, S.; Ferrara, A., Freeway traffic control: a survey, Automatica, volume 130, 109655 (2021)
[14] van de Hoef, S.; Johansson, K. H., Fuel-efficient en route formation of truck platoons, EEE Transactions on Intelligent Transportation Systems, volume 19, 102-112 (2018)
[15] Vinitsky, E.; Parvate, K.; Kreidieh, A.; Wu, C.; Bayen, A., Lagrangian control through deep-rl: applications to bottleneck decongestion, Proc. of the 21st IEEE International Conference on Intelligent Transportation Systems, 759-765 (2018)
[16] Wang, M.; Daamen, W.; Hoogendoorn, S. P.; van Arem, B., Connected variable speed limits control and car-following control with vehicle-infrastructure communication to resolve stop-and-go waves, Journal of Intelligent Transportation Systems, volume 20, 559-572 (2016)
[17] Yu, H.; Amin, S.; Krstic, M., Stability analysis of mixed-autonomy traffic with CAV platoons using two-class aw-rascle model, Proc. 59th IEEE Conference on Decision and Control, 5659-5664 (2020)
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