Augmenting Cartographic Resources for Autonomous Driving

In this paper we present algorithms for automatically generating a road network description from aerial imagery. The road network inforamtion (RNI) produced by our algorithm includes a composite topoloigical and spatial representation of the roads visible in an aerial image. We generate this data for use by autonomous vehicles operating on-road in urban environments. This information is used by the vehicles to both route plan and determine appropriate tactical behaviors. RNI can provide important contextual cues that influence driving behaviors, such as the curvature of the road ahead, the location of traffic signals, or pedestrian dense areas. The value of RNI was demonstrated compellingly in the DARPA Urban Challenge 1 , where the vehicles relied on this information to drive quickly, safely and efficiently. The current best methods for generating RNI are manual, labor intensive and error prone. Automation of this process could thus provide an important capability. As a step toward t...

• Type: Conference
• Year: 2009
• Where: GIS
• Authors: Young-Woo Seo, Chris Urmson, David Wettergreen Jin-Woo Lee
• Keywords: Appropriate Tactical Behaviors, DARPA Urban Challenge, Database, GIS 2009, Important Contextual Cues