CommonRoad: Composable benchmarks for motion planning on roads

M Althoff, M Koschi, S Manzinger - 2017 IEEE Intelligent …, 2017 - ieeexplore.ieee.org
M Althoff, M Koschi, S Manzinger
2017 IEEE Intelligent Vehicles Symposium (IV), 2017ieeexplore.ieee.org
Numerical experiments for motion planning of road vehicles require numerous components:
vehicle dynamics, a road network, static obstacles, dynamic obstacles and their movement
over time, goal regions, a cost function, etc. Providing a description of the numerical
experiment precise enough to reproduce it might require several pages of information. Thus,
only key aspects are typically described in scientific publications, making it impossible to
reproduce results-yet, re-producibility is an important asset of good science. Composable …
Numerical experiments for motion planning of road vehicles require numerous components: vehicle dynamics, a road network, static obstacles, dynamic obstacles and their movement over time, goal regions, a cost function, etc. Providing a description of the numerical experiment precise enough to reproduce it might require several pages of information. Thus, only key aspects are typically described in scientific publications, making it impossible to reproduce results - yet, re-producibility is an important asset of good science. Composable benchmarks for motion planning on roads (CommonRoad) are proposed so that numerical experiments are fully defined by a unique ID; all information required to reconstruct the experiment can be found on the CommonRoad website. Each benchmark is composed by a vehicle model, a cost function, and a scenario (including goals and constraints). The scenarios are partly recorded from real traffic and partly hand-crafted to create dangerous situations. We hope that CommonRoad saves researchers time since one does not have to search for realistic parameters of vehicle dynamics or realistic traffic situations, yet provides the freedom to compose a benchmark that fits one's needs.
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