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Optimal trajectory planning for connected and automated vehicles in lane-free traffic with vehicle nudging

Yanumula Venkata-Karteek, Typaldos Panagiotis, Troullinos Dimitrios, Malekzadehkebria Milad, Papamichail Ioannis, Papageorgiou Markos

Απλή Εγγραφή


URIhttp://purl.tuc.gr/dl/dias/8F2AE0AC-A5A2-427A-B4E3-9734A74D2FE1-
Αναγνωριστικόhttps://doi.org/10.1109/TIV.2023.3241200-
Αναγνωριστικόhttps://ieeexplore.ieee.org/document/10032638-
Γλώσσαen-
Μέγεθος15 pagesen
ΤίτλοςOptimal trajectory planning for connected and automated vehicles in lane-free traffic with vehicle nudgingen
ΔημιουργόςYanumula Venkata-Karteeken
ΔημιουργόςYanumula Karteekel
ΔημιουργόςTypaldos Panagiotisen
ΔημιουργόςΤυπαλδος Παναγιωτηςel
ΔημιουργόςTroullinos Dimitriosen
ΔημιουργόςΤρουλλινος Δημητριοςel
ΔημιουργόςMalekzadehkebria Miladen
ΔημιουργόςMalekzadehkebria Miladel
ΔημιουργόςPapamichail Ioannisen
ΔημιουργόςΠαπαμιχαηλ Ιωαννηςel
ΔημιουργόςPapageorgiou Markosen
ΔημιουργόςΠαπαγεωργιου Μαρκοςel
ΕκδότηςInstitute of Electrical and Electronics Engineersen
ΠεριγραφήThe research leading to these results has received funding from the European Research Council under the European Union’s Horizon 2020 Research and Innovation programme/ ERC Grant Agreement n. [833915], project TrafficFluid.en
ΠερίληψηThe paper presents a movement strategy for Connected and Automated Vehicles (CAVs) in a lane-free traffic environment with vehicle nudging by use of an optimal control approach. State-dependent constraints on control inputs are considered to ensure that the vehicle moves within the road boundaries and to prevent collisions. An objective function, comprising various weighted sub-objectives, is designed, whose minimization leads to vehicle advancement at the desired speed, when possible, while avoiding obstacles. A nonlinear optimal control problem (OCP) is formulated for the minimization of the objective function subject to constraints for each vehicle. A computationally efficient Feasible Direction Algorithm (FDA) is called, on event-triggered basis, to compute in real-time the numerical solution for finite time-horizons within a Model Predictive Control (MPC) framework. The approach is applied to each vehicle on the road, while running simulations on a lane-free ring-road, for a wide range of vehicle densities and different types of vehicles. From the simulations, which create myriads of driving episodes for each involved vehicle, it is observed that the proposed approach is highly efficient in delivering safe, comfortable and efficient vehicle trajectories, as well as high traffic flow outcomes. The approach is under investigation for further use in various lane-free road infrastructures for CAV traffic.en
ΤύποςPeer-Reviewed Journal Publicationen
ΤύποςΔημοσίευση σε Περιοδικό με Κριτέςel
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by-nc-nd/4.0/en
Ημερομηνία2024-06-27-
Ημερομηνία Δημοσίευσης2023-
Θεματική ΚατηγορίαLane-free trafficen
Θεματική ΚατηγορίαOptimal controlen
Θεματική ΚατηγορίαTrajectory planningen
Θεματική ΚατηγορίαAutomated vehiclesen
Βιβλιογραφική ΑναφοράV. K. Yanumula, P. Typaldos, D. Troullinos, M. Malekzadeh, I. Papamichail and M. Papageorgiou, "Optimal trajectory planning for connected and automated vehicles in lane-free traffic with vehicle nudging," IEEE Trans. Intell. Veh., 2022, doi: 10.1109/TIV.2023.3241200.en

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