Traffic Light Mapping and Detection
Venue
Proceedings of ICRA 2011
Publication Year
2011
Authors
Nathaniel Fairfield, Chris Urmson
BibTeX
Abstract
The outdoor perception problem is a major challenge for driver-assistance and
autonomous vehicle systems. While these systems can often employ active sensors
such as sonar, radar, and lidar to perceive their surroundings, the state of
standard traffic lights can only be perceived visually. By using a prior map, a
perception system can anticipate and predict the locations of traffic lights and
improve detection of the light state. The prior map also encodes the control
semantics of the individual lights. This paper presents methods for automatically
mapping the three dimensional positions of traffic lights and robustly detecting
traffic light state onboard cars with cameras. We have used these methods to map
more than four thousand traffic lights, and to perform onboard traffic light
detection for thousands of drives through intersections.
