Multilane traffic is hard to model because of its hybrid nature: continuous dynamics on each lane and discrete event for lane-change. We design a hybrid system, where the lane-changing mechanism has three components: safety, incentive and cool-down time. We model traffic flow using two populations: human-driven vehicles and autonomous vehicles. Recently, a lot of attention was given to control of traffic with autonomous vehicles. We consider the mean-field as one population (human-driven) pass to the limit. Gamma-convergence is proven for optimal control problems at the microscopic scale to the mean-field ones, consisting of coupled controlled hybrid ODEs and Vlasov-type PDE with source terms representing lane-change.

Mean-Field of Optimal Control Problems for Hybrid Model of Multilane Traffic / Gong, X.; Piccoli, B.; Visconti, G.. - In: IEEE CONTROL SYSTEMS LETTERS. - ISSN 2475-1456. - 5:6(2021), pp. 1964-1969. [10.1109/LCSYS.2020.3046540]

Mean-Field of Optimal Control Problems for Hybrid Model of Multilane Traffic

Visconti G.
2021

Abstract

Multilane traffic is hard to model because of its hybrid nature: continuous dynamics on each lane and discrete event for lane-change. We design a hybrid system, where the lane-changing mechanism has three components: safety, incentive and cool-down time. We model traffic flow using two populations: human-driven vehicles and autonomous vehicles. Recently, a lot of attention was given to control of traffic with autonomous vehicles. We consider the mean-field as one population (human-driven) pass to the limit. Gamma-convergence is proven for optimal control problems at the microscopic scale to the mean-field ones, consisting of coupled controlled hybrid ODEs and Vlasov-type PDE with source terms representing lane-change.
2021
Hybrid system; mean-field; multilane multi-class traffic; optimal control
01 Pubblicazione su rivista::01a Articolo in rivista
Mean-Field of Optimal Control Problems for Hybrid Model of Multilane Traffic / Gong, X.; Piccoli, B.; Visconti, G.. - In: IEEE CONTROL SYSTEMS LETTERS. - ISSN 2475-1456. - 5:6(2021), pp. 1964-1969. [10.1109/LCSYS.2020.3046540]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1553416
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