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Technical University of Crete
Technical University of Crete
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| URI | http://purl.tuc.gr/dl/dias/8F2AE0AC-A5A2-427A-B4E3-9734A74D2FE1 | - |
| Identifier | https://doi.org/10.1109/TIV.2023.3241200 | - |
| Identifier | https://ieeexplore.ieee.org/document/10032638 | - |
| Language | en | - |
| Extent | 15 pages | en |
| Title | Optimal trajectory planning for connected and automated vehicles in lane-free traffic with vehicle nudging | en |
| Creator | Yanumula Venkata-Karteek | en |
| Creator | Yanumula Karteek | el |
| Creator | Typaldos Panagiotis | en |
| Creator | Τυπαλδος Παναγιωτης | el |
| Creator | Troullinos Dimitrios | en |
| Creator | Τρουλλινος Δημητριος | el |
| Creator | Malekzadehkebria Milad | en |
| Creator | Malekzadehkebria Milad | el |
| Creator | Papamichail Ioannis | en |
| Creator | Παπαμιχαηλ Ιωαννης | el |
| Creator | Papageorgiou Markos | en |
| Creator | Παπαγεωργιου Μαρκος | el |
| Publisher | Institute of Electrical and Electronics Engineers | en |
| Description | 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. | en |
| Content Summary | The 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 Item | Peer-Reviewed Journal Publication | en |
| Type of Item | Δημοσίευση σε Περιοδικό με Κριτές | el |
| License | http://creativecommons.org/licenses/by-nc-nd/4.0/ | en |
| Date of Item | 2024-06-27 | - |
| Date of Publication | 2023 | - |
| Subject | Lane-free traffic | en |
| Subject | Optimal control | en |
| Subject | Trajectory planning | en |
| Subject | Automated vehicles | en |
| Bibliographic Citation | V. 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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