Not-At-Fault Driving In Traffic: A Reachability-Based Approach

2019 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE (ITSC)(2019)

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摘要
To operate in traffic, autonomous vehicles must plan long trajectories (e.g., unprotected left turns across traffic) and validate that they are not-at-fault in a collision. Reachability-based Trajectory Design for Dynamic environments (RTD-D) is a method that plans validated trajectories, which are then tracked a feedback controller-in this work linear MPC. RTD-D computes a Forward Reachable Set (FRS) of the ego vehicle's motion offline, then uses the FRS online to plan by discretizing time and buffering obstacles (i.e., artificially increasing their size) to compensate for the discretization; this requires choosing a conservative buffer so that the discretization is coarse enough for real-time planning. This paper eliminates the discretization-dependent buffer with a new method of computing the FRS over a prespecified choice of time intervals, allowing for a much coarser time discretization that reduces both computational cost and conservatism at runtime. The new method, RTD-Interval (RTD-I), is shown in simulation on a vehicle described by a nonlinear bicycle model in comparison to RTD-D and a State Lattice planner in unstructured dynamic environments. RTD-I is also compared to RTD-D in unprotected left turns across busy intersections, and we demonstrate that the MPC controller tracking the road centerline is unsafe on its own. RTD-I plans faster and less conservatively than RTD-D, and causes no at-fault collisions.
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关键词
RTD-D,feedback controller,forward reachable set,ego vehicle,FRS online,conservative buffer,real-time planning,discretization-dependent buffer,coarser time discretization,computational cost,conservatism,unstructured dynamic environments,unprotected left turns,MPC controller,RTD-I plans,at-fault collisions,at-fault driving,reachability-based approach,autonomous vehicles,long trajectories,reachability-based trajectory design,linear MPC
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