Autonomous driving in urban environments: Boss and the Urban Challenge
C. Urmson, J. Anhalt, H. Bae, J. Bagnell, C. Baker, R.E. Bittner, T. Brown,
M.N. Clark, M. Darms, D. Demitrish, J. Dolan, D. Duggins, D. Ferguson,
T. Galatali, C.M. Geyer, M. Gittleman, S. Harbaugh, M. Hebert, T. Howard,
S. Kolski, M. Likhachev, B. Litkouhi, A. Kelly, M. McNaughton, N. Miller,
J. Nickolaou, K. Peterson, B. Pilnick, R. Rajkumar, P. Rybski, V. Sadekar,
B. Salesky, Y. Seo, S. Singh, J.M. Snider, J.C. Struble, A. Stentz, M. Taylor,
W.L. Whittaker, Z. Wolkowicki, W. Zhang, and J. Ziglar
Abstract
Boss is an autonomous vehicle that uses on-board sensors (global positioning
system, lasers, radars, and cameras) to track other vehicles, detect static
obstacles, and localize itself relative to a road model. A three-layer planning
system combines mission, behavioral, and motion planning to drive in urban
environments. The mission planning layer considers which street to take to
achieve a mission goal. The behavioral layer determines when to change lanes
and precedence at intersections and performs error recovery maneuvers. The
motion planning layer selects actions to avoid obstacles while making progress
toward local goals. The system was developed from the ground up to address the
requirements of the DARPA Urban Challenge using a spiral system development
process with a heavy emphasis on regular, regressive system testing. During the
National Qualification Event and the 85-km Urban Challenge Final Event, Boss
demonstrated some of its capabilities, qualifying first and winning the
challenge.