Safety is an important topic in autonomous driving since any collision may cause serious damage to people and the environment . Hamilton-Jacobi (HJ) Reachability is a formal method that verifies safety in multi-agent interaction and provides a safety controller for collision avoidance. However, due to the worst-case assumption on the car's future actions , reachability might result in too much conservatism such that the normal operation of the vehicle is largely hindered. In this paper, we leverage the power of trajectory prediction , and propose a prediction-based reachability framework for the safety controller . Instead of always assuming for the worst-case, we first cluster the car's behaviors into multiple driving modes, e.g. left turn or right turn. Under each mode, a reachability-based safety controller is designed based on a less conservative action set. For online purpose , we first utilize the trajectory prediction and our proposed mode classifier to predict the possible modes, and then deploy the corresponding safety controller. Through simulations in a T-intersection and an 8-way roundabout, we demonstrate that our prediction-based reachability method largely avoids collision between two interacting cars and reduces the conservatism that the safety controller brings to the car's original operations .
Safety is an important topic in autonomous driving since any collision may cause serious injury to people and damage to property . Hamilton-Jacobi (HJ) Reachability is a formal method that verifies safety in multi-agent interaction and provides a safety controller for collision avoidance. However, due to the worst-case assumption on the cars future behaviours , reachability might result in too much conservatism such that the normal operation of the vehicle is badly hindered. In this paper, we leverage the power of trajectory prediction and propose a prediction-based reachability framework to compute safety controllers . Instead of always assuming the worst case, we cluster the car's behaviors into multiple driving modes, e.g. left turn or right turn. Under each mode, a reachability-based safety controller is designed based on a less conservative action set. For online implementation , we first utilize the trajectory prediction and our proposed mode classifier to predict the possible modes, and then deploy the corresponding safety controller. Through simulations in a T-intersection and an 8-way roundabout, we demonstrate that our prediction-based reachability method largely avoids collision between two interacting cars and reduces the conservatism that the safety controller brings to the car's original operation .
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damage
injury
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the environment
damage to property
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car's future actions
cars future behaviours
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largely
badly
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,
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for the safety controller
to compute safety controllers
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for the worst-case, we first
the worst case, we
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purpose
implementation
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operations
operation