Institutional Repository [SANDBOX]
Technical University of Crete
EN  |  EL

Search

Browse

My Space

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

Simple record


URIhttp://purl.tuc.gr/dl/dias/8F2AE0AC-A5A2-427A-B4E3-9734A74D2FE1-
Identifierhttps://doi.org/10.1109/TIV.2023.3241200-
Identifierhttps://ieeexplore.ieee.org/document/10032638-
Languageen-
Extent15 pagesen
TitleOptimal trajectory planning for connected and automated vehicles in lane-free traffic with vehicle nudgingen
CreatorYanumula Venkata-Karteeken
CreatorYanumula Karteekel
CreatorTypaldos Panagiotisen
CreatorΤυπαλδος Παναγιωτηςel
CreatorTroullinos Dimitriosen
CreatorΤρουλλινος Δημητριοςel
CreatorMalekzadehkebria Miladen
CreatorMalekzadehkebria Miladel
CreatorPapamichail Ioannisen
CreatorΠαπαμιχαηλ Ιωαννηςel
CreatorPapageorgiou Markosen
CreatorΠαπαγεωργιου Μαρκοςel
PublisherInstitute of Electrical and Electronics Engineersen
DescriptionThe 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
Content SummaryThe 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
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by-nc-nd/4.0/en
Date of Item2024-06-27-
Date of Publication2023-
SubjectLane-free trafficen
SubjectOptimal controlen
SubjectTrajectory planningen
SubjectAutomated vehiclesen
Bibliographic CitationV. 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

Available Files

Services

Statistics