Human-Aided Trajectory Planning for Automated Vehicles through Teleoperation and Arbitration Graphs
Abstract
Teleoperation enables remote human support of automated vehicles in scenarios where the automation is not able to find an appropriate solution. Remote assistance concepts, where operators provide discrete inputs to aid specific automation modules like planning, is gaining interest due to its reduced workload on the human remote operator and improved safety. However, these concepts are challenging to implement and maintain due to their deep integration and interaction with the automated driving system. In this paper, we propose a solution to facilitate the implementation of remote assistance concepts that intervene on planning level and extend the operational design domain of the vehicle at runtime. Using arbitration graphs, a modular decision-making framework, we integrate remote assistance into an existing automated driving system without modifying the original software components. Our simulative implementation demonstrates this approach in two use cases, allowing operators to adjust planner constraints and enable trajectory generation beyond nominal operational design domains.
Keywords
Cite
@article{arxiv.2502.02207,
title = {Human-Aided Trajectory Planning for Automated Vehicles through Teleoperation and Arbitration Graphs},
author = {Nick Le Large and David Brecht and Willi Poh and Jan-Hendrik Pauls and Martin Lauer and Frank Diermeyer},
journal= {arXiv preprint arXiv:2502.02207},
year = {2026}
}
Comments
7 pages, 8 figures, presented at IEEE Intelligent Vehicles Symposium 2025, video demonstration available at https://www.youtube.com/watch?v=fVSO-YOeGMk