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  • Adams, M. (2001). On-line gradient based surface discontinuity detection for outdoor scanning range sensors. Proceedings. 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2001, Maui, HI (Volume 3, pp. 1726–1731).
  • Barton, M. (2001). Controller development and implementation for path planning and following in an autonomous urban vehicle. Undergraduate thesis, University of Sydney, Sydney, Australia.
  • Boer, E., & Hoedemaeker, M. (1998). Modeling driver behavior with different degrees of automation: A hierarchical decision framework for interactive mental models. In Proceedings of the 17th European Annual Conference on Human Decision Making and Manual Control, Valenciennes, France.
  • Coulter, R. C. (1992). Implementation of the pure pursuit path tracking algorithm (Tech. Rep. CMU-RI-TR-92-01). Pittsburgh, PA: Robotics Institute, Carnegie Mellon University.
  • Cremer, J., Kearney, J., & Papelis, Y. (1995). HCSM: A framework for behavior and scenario control in virtual environments. ACM Transactions on Modeling and Computer Simulation, 5(3), 242267.
  • Harper, D., Hua, D. K., Foroosh, D. H., Leonessa, D. A., Qu, D. Z., Pillat, R., Norvell, D., Santiago, S., Collins, T., Stein, G., Stickler, S., Decker, G., Andres, R., Shen, Y., Chen, H., & Xie, F. (2005). DARPA Grand Challenge 2005 (Tech. Rep.). Orlando: University of Central Florida.
  • Michon, J. (1985). A critical view of driver behaviour models: What do we know, what should we do? In L.Evans & R.Schwing (Eds.), Human behaviour and traffic safety. New York: Plenum.
  • Moravec, H. (1988). Sensor fusion in certainty grids for mobile robots. AI Magazine, 9(2), 6174.
  • Papelis, Y., & Ahmad, O. (2001). A comprehensive microscopic autonomous driver model for use in high-fidelity driving simulation environments. In Proceedings of 81st Annual Meeting of the Transportation Research Board, Washington, DC.
  • Qu, Z., Wang, J., & Plaisted, C. E. (2004). A new analytical solution to mobile robot trajectory generation in the presence of moving obstacles. IEEE Transactions on Robotics, 20, 978993.
  • Surmann, H., Nuechter, A., & Hertzberg, J. (2003). An autonomous mobile robot with a 3D laser range finder for 3D exploration and digitalization of indoor environments. Robotics and Autonomous Systems, 45, 181198.
  • Thrun, S., Burgard, W., & Fox, D. (2005). Probabilistic robotics. Intelligent robotics and autonomous agents. Cambridge, MA: MIT Press.
  • 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., Stand, 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. (2006). Stanley: The robot that won the DARPA Grand Challenge. Journal of Field Robotics: Special Issue on the DARPA Grand Challenge, Part 2, 23(9), 661692.
  • Wulf, O., & Wagner, B. (2003). Fast 3D-scanning methods for laser measurement systems. International Conference on Control Systems and Computer Science (CSCS14), July 2–5, 2003, Bucharest, Romania.
  • Yang, J., Daoui, A., Qu, Z., Wang, J., & Hull, R. (2005). An optimal and real-time solution to parameterized mobile robot trajectories in the presence of moving obstacles. In 2005 IEEE International Conference on Robotics and Automation, Barcelona, Spain (pp. 4423–4428).