Abstract
This chapter presents an overview of the most advanced intelligent vehicle projects which once attended either the Grand Challenge or the Urban Challenge supported by the DARPA in the USA. Sections 2.2 to 2.8 introduce in detail the following projects: Boss (Carnegie Mellon University), Junior (Stanford University), Odin (Virginia Polytechnic Institute and State University), Talos (Massachusetts Institute of Technology), Skynet (Cornell University), Little Ben (University of Pennsylvania and Lehigh University), TerraMax (Oshkosh Truck Corporation).
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References
Aoude, G.S., How, J.P.: Using support vector machines and Bayesian filtering for classifying agent intentions at road intersections. The Association for Computational Linguistics (2009)
Bacha, A., Bauman, C., Faruque, R., Fleming, M., Terwelp, C., Reinholtz, C., Hong, D., Wicks, A., Alberi, T., Anderson, D., et al.: Odin: team victortango’s entry in the DARPA urban challenge. J. Field Robot. 25(8), 467–492 (2008)
Bishop, R.: A survey of intelligent vehicle applications worldwide. In: Proceedings of the IEEE on Intelligent Vehicles Symposium, 2000. IV 2000, pp. 25–30. IEEE, New York (2000)
Bohren, J., Foote, T., Keller, J., Kushleyev, A., Lee, D., Stewart, A., Vernaza, P., Derenick, J., Spletzer, J., Satterfield, B.: Little Ben: The Ben Franklin racing teams entry in the 2007 DARPA Urban Challenge. DARPA Urban Challenge 25(9), 231–255 (2009)
Braid, D., Broggi, A., Schmiedel, G.: The TerraMax autonomous vehicle. J. Field Robot. 23(9), 693–708 (2006)
Crisman, J.D., Thorpe, C.E.: UNSCARF—a color vision system for the detection of unstructured roads. In: Proc. of the IEEE International Conference on Robotics and Automation (1991)
Crisman, J.D., Thorpe, C.E.: SCARF: a color vision system that tracks roads and intersections. IEEE Trans. Robot. Autom. 9(1), 49–58 (1993)
Herbert, M.H., Thorpe, C., Stentz, A.: Intelligent Unmanned Ground Vehicles: Autonomous Navigation Research at Carnegie Mellon. Kluwer Academic, Norwell (1997)
Huang, A.S., Antone, M., Olson, E., Fletcher, L., Moore, D., Teller, S., Leonard, J.: A high-rate, heterogeneous data set from the DARPA Urban Challenge. Int. J. Robot. Res. 29(13), 1595 (2010)
Iagnemma, K., Buehler, M.: Editorial for journal of field robotics special issue on the DARPA grand challenge. J. Field Robot. 23(9), 655–656 (2006)
Jochem, T.M., Pomerleau, D.A., Thorpe, C.E.: MANIAC: a next generation neurally based autonomous road follower. In: Proceedings of the International Conference on Intelligent Autonomous Systems: IAS-3, Pittsburgh, Pennsylvania, USA (1993)
Kluge, K., Thorpe, C.: Intersection detection in the YARF road following system. In: Intelligent Autonomous Systems, IAS–3: An International Conference, Pittsburgh, Pennsylvania. IOS Press, Amsterdam (1993)
Leonard, J., How, J., Teller, S., Berger, M., Campbell, S., Fiore, G., Fletcher, L., Frazzoli, E., Huang, A., Karaman, S., et al.: A perception-driven autonomous urban vehicle. DARPA Urban Challenge 25(10), 163–230 (2009)
Montemerlo, M., Becker, J., Bhat, S., Dahlkamp, H., Dolgov, D., Ettinger, S., Haehnel, D., Hilden, T., Hoffmann, G., Huhnke, B., et al.: Junior: the Stanford entry in the urban challenge. J. Field Robot. 25(9), 569–597 (2008)
Pisoni, A.: Skynet. Manual version 0.9, http://skynet.rubyforge.org/, 3 (2007)
Pomerleau, D.A.: Neural network based autonomous navigation. In: Vision and Navigation. The Carnegie Mellon Navlab, pp. 83–93 (1990)
Thorpe, C., Hebert, M.H., Kanade, T., Shafer, S.A.: Vision and navigation for the Carnegie–Mellon Navlab. IEEE Trans. Pattern Anal. Mach. Intell. 10(3), 362–373 (1988)
Urmson, C., Anhalt, J., Bagnell, D., Baker, C., Bittner, R., Clark, M., Dolan, J., Duggins, D., Galatali, T., Geyer, C., et al.: Autonomous driving in urban environments: boss and the urban challenge. J. Field Robot. 25(8), 425–466 (2008)
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Cheng, H. (2011). The State-of-the-Art in the USA. In: Autonomous Intelligent Vehicles. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-4471-2280-7_2
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DOI: https://doi.org/10.1007/978-1-4471-2280-7_2
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