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Optimal path planning for connected and automated vehicles in lane-free traffic

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

Πλήρης Εγγραφή


URI: http://purl.tuc.gr/dl/dias/C5AF11CF-FDEB-4190-A032-BA6A45CB614B
Έτος 2021
Τύπος Πλήρης Δημοσίευση σε Συνέδριο
Άδεια Χρήσης
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Βιβλιογραφική Αναφορά V. K. Yanumula, P. Typaldos, D. Troullinos, M. Malekzadeh, I. Papamichail and M. Papageorgiou, "Optimal path planning for connected and automated vehicles in lane-free traffic," in 24th IEEE International Intelligent Transportation Systems Conference (ITSC 2021), 2021, pp. 3545-3552, doi: 10.1109/ITSC48978.2021.9564698. https://doi.org/10.1109/ITSC48978.2021.9564698
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This paper develops a path planning algorithm for Connected and Automated Vehicles (CAVs) driving on a lane-free highway, according to a recently proposed novel paradigm for vehicular traffic in the era of CAVs. The approach considers a simple model of vehicle kinematics, along with appropriate constraints for control variables and road boundaries. Appropriate, partly competitive sub-objectives are designed to enable efficient vehicle advancement, while avoiding collisions with other vehicles and infeasible vehicle maneuvers. Based on these elements, a nonlinear Optimal Control Problem (OCP) is formulated for each ego vehicle, and a Feasible Direction Algorithm (FDA) is employed for its computationally efficient numerical solution. The OCP is solved repeatedly for short time horizons within a Model Predictive Control (MPC) framework, while the vehicle advances. It is demonstrated via traffic simulation, involving many such vehicles, on a lane-free ring-road that the proposed approach delivers promising results and can be considered as a candidate for use in further developments related to lane-free CAV traffic.

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