Finding Multiple Lanes in Urban Road Networks with Vision and Lidar
Name
Huang_Finding multiple lanes.pdf
Size
18.09 MB
Format
Adobe PDF
Checksum (MD5)
a17ad4de3d4dc3315fe57bcd94242bb5
Author(s)
Huang, Albert S.
Moore, David C.
Antone, Matthew
Olson, Edwin B.
Teller, Seth
Date Issued
March 2009
Journal
Autonomous Robots
Publisher
Springer Netherlands
Citation
A. Huang, D. Moore, M. Antone, E. Olson, and S. Teller, “Finding multiple lanes in urban road networks with vision and lidar,” Autonomous Robots, vol. 26, Apr. 2009, pp. 103-122.
Version
Author's final manuscript
Abstract
This paper describes a system for detecting and estimating the properties of multiple travel lanes in an urban road network from calibrated video imagery and laser range data acquired by a moving vehicle. The system operates in real-time in several stages on multiple processors, fusing detected road markings, obstacles, and curbs into a stable non-parametric estimate of nearby travel lanes. The system incorporates elements of a provided piecewise-linear road network as a weak prior.
Our method is notable in several respects: it detects and estimates multiple travel lanes; it fuses asynchronous, heterogeneous sensor streams; it handles high-curvature roads; and it makes no assumption about the position or orientation of the vehicle with respect to the road.
We analyze the system’s performance in the context of the 2007 DARPA Urban Challenge. With five cameras and thirteen lidars, our method was incorporated into a closed-loop controller to successfully guide an autonomous vehicle through a 90 km urban course at speeds up to 40 km/h amidst moving traffic.
Subjects
lane-finding
lane estimation
lidar
vision
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1007/s10514-009-9113-3
