Stochastic motion planning and applications to traffic
This paper presents a stochastic motion planning algorithm and its application to traffic navigation. The algorithm copes with the uncertainty of road traffic conditions by stochastic modeling of travel delay on road networks. The algorithm determines paths between two points that optimize a cost fu...
| Main Authors: | , , , , |
|---|---|
| Other Authors: | |
| Format: | Book chapter |
| Language: | en_US |
| Published: |
Springer Berlin/Heidelberg
2012
|
| Online Access: | http://hdl.handle.net/1721.1/72494 https://orcid.org/0000-0002-7470-3265 https://orcid.org/0000-0001-5473-3566 https://orcid.org/0000-0003-1709-4034 https://orcid.org/0000-0002-1455-9652 |
| Summary: | This paper presents a stochastic motion planning algorithm and its application to traffic navigation. The algorithm copes with the uncertainty of road traffic conditions by stochastic modeling of travel delay on road networks. The algorithm determines paths between two points that optimize a cost function of the delay probability distribution. It can be used to find paths that maximize the probability of reaching a destination within a particular travel deadline. For such problems, standard shortest-path algorithms don’t work because the optimal substructure property doesn’t hold. We evaluate our algorithm using both simulations and real-world drives, using delay data gathered from a set of taxis equipped with GPS sensors and a wireless network. Our algorithm can be integrated into on-board navigation systems as well as route-finding Web sites, providing drivers with good paths that meet their desired goals. |
|---|