CommonRoad is a collection of composable benchmarks for motion planning on roads. This website presents our benchmark collection and provides researchers with a means of evaluating and comparing their motion planners. For further information, read up on the introduction below. Also, have a look at our scenarios.
Numerical experiments for motion planning of road vehicles require numerous ingredients: 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, reproducibility 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 required information 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 having the freedom to compose a benchmark that fits one's needs.
CommonRoad is introduced in our paper M. Althoff, M. Koschi, and S. Manzinger, ''CommonRoad: Composable Benchmarks for Motion Planning on Roads,'' in Proc. of the IEEE Intelligent Vehicles Symposium, 2017, pp. 719-726.
We offer you the possibility to suggest new benchmarks. If you want to contribute a new component, e.g. a scenario, please contact us per email.
It is our pleasure to release the 2018a version of CommonRoad with exciting new features:
We hope that you are enjoying the new features.
Your CommonRoad Team