Shared Autonomy for Teleoperated Driving: A Real-Time Interactive Path Planning Approach

Teleoperation deals with extraordinary situations where an external operator takes over the control of an autonomous vehicle. Especially in complex urban scenarios, this may cause a too high workload for the human operator, resulting in suboptimal solutions. This contribution presents a teleoperation paradigm to raise the autonomy level of teleoperated driving, while the operator still remains the main decision-maker in all driving tasks. The introduced approach generates collision-free paths using LiDAR sensor information and suggests them to the operator. Therefore, a new hybrid path planning method has been developed, which searches and clusters in the first phase all feasible paths in the environment using a modified Rapidly-Exploring-Random Tree (RRT). In the second phase, the path selected by the operator is optimized online by a modified CHOMP algorithm. Real driving experiments confirm the effectiveness of the approach and highlight both the achieved driving safety and real time capability.