Multi-Sensor Lane Finding in Urban Road Networks

Proceedings of Robotics: Science and Systems (RSS), 2008

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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 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 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´┐Żs performance in the context of the 2007 DARPA Urban Challenge. With five cameras and thirteen lidars, it 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.


Lane Detection
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    AUTHOR     = {Albert Huang and David Moore and Matthew Antone and Edwin Olson and
                 Seth Teller},
    TITLE      = {Multi-Sensor Lane Finding in Urban Road Networks},
    BOOKTITLE  = {Proceedings of Robotics: Science and Systems ({RSS})},
    YEAR       = {2008},
    MONTH      = {June},
    ADDRESS    = {Zurich, Switzerland},