Automatically synthesizing a planning and control subsystem for the DARPA urban challenge

Thumbnail Image
Penn collection
Departmental Papers (ESE)
General Robotics, Automation, Sensing and Perception Laboratory
Degree type
mobile robots
path planning
road traffic
road vehicles
DARPA Urban Challenge
control subsystem
dynamic obstacle
mobile robot
path planning
road vehicle
static obstacle
traffic law
Grant number
Copyright date
Related resources

To incorporate robots into society, they must be able to perform complex tasks while interacting with the world around them in a safe and dependable manner. The recent DARPA 2007 Urban Challenge made a step towards that goal by testing how well robotic vehicles can interact in an urban environment while dealing with static and dynamic obstacles and other cars. This paper uses the Urban challenge to demonstrates a general approach for automatically synthesizing correct hybrid controllers from high level descriptions. Here we create a planning and control subsystem for the vehicle that, if the information gathered by the sensor is correct, satisfies the requirements of the challenge for different dynamic environments. This approach automatically produces a system that is guaranteed to behave according to the traffic laws while interacting with other vehicles. Furthermore, it allows systems to be changed rapidly and easily thus reducing design time and eliminating human error.

Date of presentation
Conference name
Departmental Papers (ESE)
Conference dates
Conference location
Date Range for Data Collection (Start Date)
Date Range for Data Collection (End Date)
Digital Object Identifier
Series name and number
Volume number
Issue number
Publisher DOI
Journal Issue
Copyright 2008 IEEE. Reprinted from: Kress-Gazit, H.; Pappas, G.J., "Automatically synthesizing a planning and control subsystem for the DARPA urban challenge," Automation Science and Engineering, 2008. CASE 2008. IEEE International Conference on , vol., no., pp.766-771, 23-26 Aug. 2008 URL: This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
Recommended citation