Stochastic motion planning and applications to traffic
Name
9321822.pdf
Description
Accepted version
Size
871.7 KB
Format
Adobe PDF
Checksum (MD5)
c3072b2ee2b3e702b58842b5f03641bf
Author(s)
Lim, Sejoon
Balakrishnan, Hari
Gifford, David
Madden, Samuel
Rus, Daniela
Date Issued
2011
Journal
International Journal of Robotics Research
Publisher
SAGE Publications
Version
Author's final manuscript
Abstract
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 data 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 do not work because the optimal substructure property does not hold. We evaluate our algorithm using both simulations and real-world drives, using delay data gathered from a set of taxis equipped with global positioning system sensors and a wireless network. Our algorithm can be integrated into onboard navigation systems as well as route-finding websites, providing drivers with good paths that meet their desired goals. © 2011 The Author(s).
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1177/0278364910386259
