Abstract
Boss is an autonomous vehicle that uses on-board sensors (GPS, 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, precedence at intersections and performs error recovery maneuvers. The motion planning layer selects actions to avoid obstacles while making progress towards 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 85km Urban Challenge Final Event Boss demonstrated some of its capabilities, qualifying first and winning the challenge.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Brooks, R.: A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation 2(1), 14–23 (1986)
Committee on Army Unmanned Ground Vehicle Technology and the National Research Council. Technology Development for Army Unmanned Ground Vehicles. Washington, D.C (2002)
Darms, M., Winner, H.: A modular system architecture for sensor data processing of ADAS applications. In: Proceedings of IEEE Intelligent Vehicles Symposium, Las Vegas, USA, pp. 729–734 (2005)
Darms, M.: Eine Basis-Systemarchitektur zur Sensordatenfusion von Umfeldsensoren Fahrerassistenzsysteme, Fortschrittb. VDI: R12, Nr. 653 (2007)
Darms, M., Rybski, P., Urmson, C.: An Adaptive Model Switching Approach for a Multisensor Tracking System used for Autonomous Driving in an Urban Environment. Steuerung und Regelung von Fahrzeugen und Motoren – AUTOREG 2008, Baden Baden (February 2008)
Darms, M., Baker, C., Rybksi, P., Urmson, C.: Vehicle Detection and Tracking for the Urban Challenge- The Approach taken by Tartan Racing. In: Maurer, M., Stiller, C. (eds.) 5. Workshop Fahrerassistenzsysteme FAS 2008, April 2008, FMRT, Karlsruhe (2008)
Darms, M., Rybski, P., Urmson, C.: Classification and Tracking of Dynamic Objects with Multiple Sensors for Autonomous Driving in Urban Environments. In: Proceedings of the IEEE Intelligent Vehicles Symposium. Eindhoven, NL (June 2008)
DARPA Urban Challenge (2007), http://www.darpa.mil/grandchallenge/index.asp
Daubechies, I.: Ten lectures on wavelets. Society for Industrial and Applied. Mathematics (1992)
Duda, R.O., Hart, P.E.: Use of the Hough Transformation to Detect Lines and Curves in Pictures. Comm. ACM 15, 11–15 (1972)
Ferguson, D., Howard, T., Likhachev, M.: Motion Planning in Urban Environments (2008) (in preparation)
Howard, T.M., Kelly, A.: Optimal Rough Terrain Trajectory Generation for Wheeled Mobile Robots. International Journal of Robotics Research 26(2), 141–166 (2007)
Huttenlocker, D., Felzenswalb, P.: Distance Transforms of Sampled Functions, Cornell Computing and Information Science Technical Report TR2004-1963 (2004)
Kaempchen, N., Weiss, K., Schaefer, M., Dietmayer, K.C.J., et al.: IMM object tracking for high dynamic driving maneuvers. In: IEEE Intelligent Vehicles Symposium 2004, Parma, Italy, pp. 825–830 (June 2004)
Likhachev, M., Ferguson, D., Gordon, G., Stentz, A., Thrun, S.: Anytime Dynamic A*: An Anytime, Replanning Algorithm. In: International Conference on Automated Planning and Scheduling, ICAPS (2005)
MacLachlan, R.: Tracking Moving Objects From a Moving Vehicle Using a Laser Scanner. tech. report CMU-RI-TR-05-07, Carnegie Mellon University (June 2005)
Shih, M.-Y., Tseng, D.-C.: A wavelet-based multi-resolution edge detection and tracking. Image and Vision Computing 23(4), 441–451 (2005)
Thrun, S., Montemerlo, M., Dahlkamp, H., Stavens, D., Aron, A., Diebel, J., Fong, P., Gale, J., Halpenny, M., Hoffmann, G., Lau, K., Oakley, C., Palatucci, M., Pratt, V., Stang, P., Strohband, S., Dupont, C., Jendrossek, L.-E., Koelen, C., Markey, C., Rummel, C., van Niekerk, J., Jensen, E., Alessandrini, P., Bradski, G., Davies, B., Ettinger, S., Kaehler, A., Nefian, A., Mahoney, P.: Stanley, the robot that won the DARPA Grand Challenge. Journal of Field Robotics 23(9), 661–692 (2006)
Urmson, C., Anhalt, J., Clark, M., Galatali, T., Gonzalez, J.P., Gowdy, J., Gutierrez, A., Harbaugh, S., Johnson-Roberson, M., Kato, H., Koon, P.L., Peterson, K., Smith, B.K., Spiker, S., Tryzelaar, E., Whittaker, W.L.: High Speed Navigation of Unrehearsed Terrain: Red Team Technology for Grand Challenge, Tech. report CMU-RI-TR-04-37, Robotics Institute, Carnegie Mellon University (2004)
Urmson, C., Anhalt, J., Bartz, D., Clark, M., Galatali, T., Gutierrez, A., Harbaugh, S., Johnston, J., Kato, H., Koon, P.L., Messner, W., Miller, N., Mosher, A., Peterson, K., Ragusa, C., Ray, D., Smith, B.K., Snider, J.M., Spiker, S., Struble, J.C., Ziglar, J., Whittaker, W.L.: A Robust Approach to High-Speed Navi-gation for Unrehearsed Desert Terrain. Journal of Field Robotics 23(8), 467–508 (2006)
Viola, P., Jones, M.: Robust real-time object detection. In: The 2nd International Workshop on Statistical and Computational Theories of Vision-Modeling, Learning, Computing, and Sampling (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Urmson, C. et al. (2009). Autonomous Driving in Urban Environments: Boss and the Urban Challenge. In: Buehler, M., Iagnemma, K., Singh, S. (eds) The DARPA Urban Challenge. Springer Tracts in Advanced Robotics, vol 56. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03991-1_1
Download citation
DOI: https://doi.org/10.1007/978-3-642-03991-1_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03990-4
Online ISBN: 978-3-642-03991-1
eBook Packages: EngineeringEngineering (R0)