Joint trajectory optimization for multiple automated vehicles in lane-free traffic with vehicle nudgingJoint trajectory optimization for multiple automated vehicles in lane-free traffic with vehicle nudging Πλήρης Δημοσίευση σε Συνέδριο Conference Full Paper 2024-06-262023enThis paper presents a joint trajectory optimization algorithm for a number of connected and automated vehicles in a lane-free traffic environment with vehicle nudging. A double integrator model is assumed for the longitudinal and lateral movement of each one of the vehicles, considering constant and state-dependent bounds on control inputs, including road boundary constraints. A multi-objective function is designed for all vehicles and is minimized using an efficient feasible direction algorithm. This leads to minimization of fuel consumption, collision avoidance, achievement of desired speeds and prevention of infeasible maneuvers. Challenging scenarios are examined on a lane-free straight motorway stretch, producing promising results for further exploration in situations where simultaneous trajectory optimization for groups of vehicles (e.g., vehicle flocks or two-dimensional platoons) is considered.The 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.http://creativecommons.org/licenses/by-nc-nd/4.0/26th IEEE International Conference on Intelligent Transportation SystemsProc. 26th IEEE International Conference on Intelligent Transportation SystemsDabestani_et_al_ITSC 2023_manuscript.pdfChania [Greece]Library of TUC2024-06-24application/pdf777.1 kBfree Dabestani Niloufar Dabestani Niloufar Typaldos Panagiotis Τυπαλδος Παναγιωτης Yanumula Venkata-Karteek Yanumula Karteek Papamichail Ioannis Παπαμιχαηλ Ιωαννης Papageorgiou Markos Παπαγεωργιου Μαρκος Institute of Electrical and Electronics Engineers Lane-free traffic Automated vehicles Joint path planning Optimal coordination Trajectory planning