The MIT–Cornell collision and why it happened

  • Authors:
  • Luke Fletcher;Seth Teller;Edwin Olson;David Moore;Yoshiaki Kuwata;Jonathan How;John Leonard;Isaac Miller;Mark Campbell;Dan Huttenlocher;Aaron Nathan;Frank-Robert Kline

  • Affiliations:
  • Massachusetts Institute of Technology Cambridge, Massachusetts 02139;Massachusetts Institute of Technology Cambridge, Massachusetts 02139;Massachusetts Institute of Technology Cambridge, Massachusetts 02139;Massachusetts Institute of Technology Cambridge, Massachusetts 02139;Massachusetts Institute of Technology Cambridge, Massachusetts 02139;Massachusetts Institute of Technology Cambridge, Massachusetts 02139;Massachusetts Institute of Technology Cambridge, Massachusetts 02139;Cornell University Ithaca, New York 14853;Cornell University Ithaca, New York 14853;Cornell University Ithaca, New York 14853;Cornell University Ithaca, New York 14853;Cornell University Ithaca, New York 14853

  • Venue:
  • Journal of Field Robotics - Special Issue on the 2007 DARPA Urban Challenge, Part III
  • Year:
  • 2008

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Abstract

Midway through the 2007 DARPA Urban Challenge, MIT's robot “Talos” and Team Cornell's robot “Skynet” collided in a low-speed accident. This accident was one of the first collisions between full-sized autonomous road vehicles. Fortunately, both vehicles went on to finish the race and the collision was thoroughly documented in the vehicle logs. This collaborative study between MIT and Cornell traces the confluence of events that preceded the collision and examines its root causes. A summary of robot–robot interactions during the race is presented. The logs from both vehicles are used to show the gulf between robot and human-driver behavior at close vehicle proximities. Contributing factors are shown to be (1) difficulties in sensor data association leading to an inability to detect slow-moving vehicles and phantom obstacles, (2) failure to anticipate vehicle intent, and (3) an overemphasis on lane constraints versus vehicle proximity in motion planning. Finally, we discuss approaches that could address these issues in future systems, such as intervehicle communication, vehicle detection, and prioritized motion planning. © 2008 Wiley Periodicals, Inc.