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As autonomous vehicles operating on the urban roads, being conscious of the road context is a crucial prerequisite to safely negotiate with the other vehicles. This paper proposes a probabilistic approach to infer the road context from the vehicle behaviors. Specifically, the consistencies of the randomly-observed vehicle states are extracted first, thereafter the road context is inferred in a probabilistic...
This paper considers the problem of motion planning for linear systems subject to Gaussian motion noise and proposes a risk-aware planning algorithm: CC-RRT∗-D. The proposed CC-RRT∗-D employs the chance-constraint approximation and leverages the asymptotically optimal property of RRT∗ framework to compute risk-aware and asymptotically optimal trajectories. By explicitly considering the state dependence...
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