This paper considers a coordination problem for Connected and Automated Vehicles (CAVs) in mixed traffic at unsignalized intersections. In such a setting, the behavior of the Human-Driven Vehicles (HDVs) is difficult to predict, thus challenging the formulation and the solution of the coordination problem. To solve this problem, we propose a coordination strategy, where CAVs are used as both sensors and actuators in mixed platoons. A timeslot-based approach is used to coordinate the occupancy of the intersection and to compensate for the HDVs behavior. The proposed approach has a bi-level optimization structure built upon the Model Predictive Control (MPC) framework that decides the crossing order and computes the vehicles' commands. In simulations, we show that the choice of the HDV prediction model heavily affects the coordination by evaluating the performance of two different HDV models: car-following and constant velocity, where the latter demonstrates more consistent results in the presence of deviation of the HDVs' behavior from a nominal model.

Optimization-Based Coordination of Mixed Traffic at Unsignalized Intersections Based on Platooning Strategy / Faris, M.; Falcone, P.; Sjoberg, J.. - 2022-:(2022), pp. 977-983. ((Intervento presentato al convegno 2022 IEEE Intelligent Vehicles Symposium, IV 2022 tenutosi a deu nel 2022 [10.1109/IV51971.2022.9827149].

Optimization-Based Coordination of Mixed Traffic at Unsignalized Intersections Based on Platooning Strategy

Falcone P.;
2022-01-01

Abstract

This paper considers a coordination problem for Connected and Automated Vehicles (CAVs) in mixed traffic at unsignalized intersections. In such a setting, the behavior of the Human-Driven Vehicles (HDVs) is difficult to predict, thus challenging the formulation and the solution of the coordination problem. To solve this problem, we propose a coordination strategy, where CAVs are used as both sensors and actuators in mixed platoons. A timeslot-based approach is used to coordinate the occupancy of the intersection and to compensate for the HDVs behavior. The proposed approach has a bi-level optimization structure built upon the Model Predictive Control (MPC) framework that decides the crossing order and computes the vehicles' commands. In simulations, we show that the choice of the HDV prediction model heavily affects the coordination by evaluating the performance of two different HDV models: car-following and constant velocity, where the latter demonstrates more consistent results in the presence of deviation of the HDVs' behavior from a nominal model.
2022 IEEE Intelligent Vehicles Symposium, IV 2022
deu
2022
2022-
977
983
Faris, M.; Falcone, P.; Sjoberg, J.
Optimization-Based Coordination of Mixed Traffic at Unsignalized Intersections Based on Platooning Strategy / Faris, M.; Falcone, P.; Sjoberg, J.. - 2022-:(2022), pp. 977-983. ((Intervento presentato al convegno 2022 IEEE Intelligent Vehicles Symposium, IV 2022 tenutosi a deu nel 2022 [10.1109/IV51971.2022.9827149].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1286799
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