日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

週刊ニュースレター購読
arXiv:2502.02207

Human-Aided Trajectory Planning for Automated Vehicles through Teleoperation and Arbitration Graphs

Human-Aided Trajectory Planning for Automated Vehicles through Teleoperation and Arbitration Graphs

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著者: Nick Le Large, David Brecht, Willi Poh, Jan-Hendrik Pauls, Martin Lauer, Frank Diermeyer

分類: cs.RO, cs.HC

原文アブストラクト

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.