Driving directionFig. 1: A teleoperated autoTAXI vehicle maneuvering around an improvised construction site C on a test track in Aldenhoven, Germany. The vehicle tracks the trajectory defined by the remote operator (path visualized in blue) from the start position A to the goal position B , effectively solving the AV disengagement scenario. Yellow circles ( ) depict approximate path waypoints specified by a remote operator using the presented teleoperation system.
Teleoperation allows a human operator to remotely interact with and control a mobile robot in a dangerous or inaccessible area. Besides well-known applications such as space exploration or search and rescue operations, the application of teleoperation in the area of automated driving, i.e., teleoperated driving (ToD), is becoming more popular. Instead of an in-vehicle human fallback driver, a remote operator can connect to the vehicle using cellular networks and resolve situations that are beyond the automated vehicle (AV)'s operational design domain. Teleoperation of AVs, and unmanned ground vehicles in general, introduces different problems, which are the focus of ongoing research. This paper presents an open source ToD software stack, which was developed for the purpose of carrying out this research. As shown in three demonstrations, the software stack can be deployed with minor overheads to control various vehicle systems remotely.
In this paper, a steering action-aware Adaptive Cruise Control (ACC) approach for teleoperated road vehicles is proposed. In order to keep the vehicle in a safe state, the ACC approach can override the human operator's velocity control commands. The safe state is defined as a state from which the vehicle can be stopped safely, no matter which steering actions are applied by the operator. This is achieved by first sampling various potential future trajectories. In a second stage, assuming the trajectory with the highest risk, a safe and comfortable velocity profile is optimized. This yields a safe velocity control command for the vehicle. In simulations, the characteristics of the approach are compared to a Model Predictive Control-based approach that is capable of overriding both, the commanded steering angle as well as the velocity. Furthermore, in teleoperation experiments with a 1:10-scale vehicle testbed, it is demonstrated that the proposed ACC approach keeps the vehicle safe, even if the control commands from the operator would have resulted in a collision.
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