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Română · beta. Traducerea a fost făcută automat și este încă în curs de revizuire. Citește pagina în engleză

În afara temei aiqbench

În afara temei aiqbench

Această știre a fost preluată de la o sursă pe care o urmărim, dar nu ține de domeniul AI sau cuantic, așa că nu există o perspectivă aiqbench pentru ea.

Unifying Decision-Making and Trajectory-Planning in Unsignalized Intersections Using Time-Varying Potential Fields

arXiv1 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2607.13626v2 Announce Type: replace-cross Abstract: This paper presents a novel framework for integrated Decision-Making (DM) and Trajectory Planning (TP) for automated vehicles at unsignalized intersections. The approach leverages a Finite Horizon Optimal Control Problem (FHOCP) that employs Time-Varying Artificial Potential Fields (TV-APF). By utilizing short-horizon motion prediction and a dedicated conflict-zone occupancy coefficient, the framework suitably accounts for potential collisions within the FHOCP. The proposed method effectively unifies DM and TP, ensuring the generation of a feasible and safe reference trajectory. Simulation results in multi-vehicle traffic scenarios demonstrate the effectiveness of the approach.

Abstract:This paper presents a novel framework for integrated Decision-Making (DM) and Trajectory Planning (TP) for automated vehicles at unsignalized intersections. The approach leverages a Finite Horizon Optimal Control Problem (FHOCP) that employs Time-Varying Artificial Potential Fields (TV-APF). By utilizing short-horizon motion prediction and a dedicated conflict-zone occupancy coefficient, the framework suitably accounts for potential collisions within the FHOCP. The proposed method effectively unifies DM and TP, ensuring the generation of a feasible and safe reference trajectory. Simulation results in multi-vehicle traffic scenarios demonstrate the effectiveness of the approach.

Published in the "2026 34th Mediterranean Conference on Control and Automation (MED)". v2 adds the final IEEE citation and DOI; technical content unchanged

Systems and Control (eess.SY); Robotics (cs.RO)

arXiv:2607.13626 [eess.SY]

(or arXiv:2607.13626v2 [eess.SY] for this version)

2026 34th Mediterranean Conference on Control and Automation (MED), Ancona, Italy, 2026, pp. 251-256

https://doi.org/10.1109/MED70602.2026.11598041 DOI(s) linking to related resources

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