Model-Based Probabilistic Collision Detection in Autonomous Driving

By Matthias Althoff, Olaf Stursberg, Martin Buss. IEEE transactions on intelligent transportation systems (Print), 2009

313 citations recorded by the source corpus.

How researchers see this paper

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Online Verification of Automated Road Vehicles Using Reachability Analysis (2014, methodology): “This is avoided by approaches that compute the stochastic prediction deterministically [34].”
A survey on motion prediction and risk assessment for intelligent vehicles (2014, unknown): “(a) RRT (adapted from [[42]]) (b) GP (adapted from [[49]]) (c) Stochastic reachable sets (adapted from [[50]]).”
Real-time motion planning methods for autonomous on-road driving: State-of-the-art and future research directions (2015, background): “Additionally, testing with only two vehicles cannot resemble a real world traffic environment (Althoff et al., 2009).”
Reachability Analysis and its Application to the Safety Assessment of Autonomous Cars (2010, methodology): “This computation has been used in [188] and generates overestimated crash probabilities.”
CommonRoad: Composable benchmarks for motion planning on roads (2017, unknown): “Gaussian [52], piecewise constant [53], etc.”
Probabilistic Analysis of Dynamic Scenes and Collision Risks Assessment to Improve Driving Safety (2011, unknown): “In addition to the knowledge about an object detected at a certain location at a specific time in the traffic scene, the prediction of its likely future behavior leads to more adequate interpretation of its possible impact on the ego-vehicle [12], [39], [40], [41].”