Intelligent decision making for overtaking maneuver using mixed observable Markov decision process

References

• Balas, M. M., Balas, V. E., & Duplaix, J. (2007, June). Optimizing the distance-gap between cars by constant time to collision planning. IEEE International Symposium on Industrial Electronics (ISIE'07) (pp. 304–309). IEEE.
   Google Scholar
• Bandyopadhyay, T., Jie, C. Z., Hsu, D., Ang, M. H. Jr, Rus, D., & Frazzoli, E. (2013). Intention-aware pedestrian avoidance. In Experimental robotics: The 13th international symposium on experimental robotics (pp. 963–977). Springer International Publishing.
   Google Scholar
• Bandyopadhyay, T., Won, K. S., Frazzoli, E., Hsu, D., Lee, W. S., & Rus, D. (2013). Intention-aware motion planning. Algorithmic foundations of robotics X (pp. 475–491). Berlin/Heidelberg: Springer.
   Google Scholar
• Bellis, E., & Page, J. (2008). National motor vehicle crash causation survey (NMVCCS) SAS analytical users manual ( No. HS-811 053).
   Google Scholar
• Bie, J., Roelofsen, M., Jin, L., & van Arem, B. (2013). Lane change and overtaking collisions: Causes and avoidance techniques. Wireless vehicular networks for car collision avoidance (pp. 143–187). New York: Springer.
   Google Scholar
• Brechtel, S., Gindele, T., & Dillmann, R. (2014, October). Probabilistic decision-making under uncertainty for autonomous driving using continuous POMDPs. IEEE 17th International Conference on Intelligent Transportation Systems (ITSC) (pp. 392–399). IEEE.
   Google Scholar
• Chen, Y. L., Shen, K. Y., & Wang, S. C. (2013). Forward collision warning system considering both time-to-collision and safety braking distance. International Journal of Vehicle Safety 8, 6(4), 347–360.
   Google Scholar
• Clarke, D. D., Ward, P. J., & Jones, J. (1998). Overtaking road-accidents: Differences in manoeuvre as a function of driver age. Accident Analysis & Prevention, 30(4), 455–467.
   PubMed Web of Science ®Google Scholar
• Hans, A., & Udluft, S. (2009). Efficient uncertainty propagation for reinforcement learning with limited data. In: Alippi C., Polycarpou M., Panayiotou C., Ellinas G. (eds), Artificial Neural Networks – ICANN 2009. ICANN 2009. Lecture Notes in Computer Science, vol 5768. Berlin, Heidelberg: Springer.
   Google Scholar
• Hegeman, G., Brookhuis, K., & Hoogendoorn, S. (2005). Opportunities of advanced driver assistance systems towards overtaking. EJTIR, 5(4), 281–296.
   Google Scholar
• Kretschmer, M., Neubeck, J., & Wiedemann, J. (2005). Combining vehicle dynamics control and decision making procedures towards safe overtaking maneuvers (No. 2005-01-0412). SAE Technical Paper.
   Google Scholar
• Kuhlman, M. J., Švec, P., Kaipa, K. N., Sofge, D., & Gupta, S. K. (2014, May). Physics-aware informative coverage planning for autonomous vehicles. In 2014 IEEE International Conference on Robotics and Automation (ICRA) (pp. 4741–4746). IEEE.
   Google Scholar
• Kurniawati, H., Hsu, D., & Lee, W. S. (2008, June). SARSOP: Efficient point-based POMDP planning by approximating optimally reachable belief spaces. In Robotics: Science and systems (Vol. 2008). Retrieved from: http://www.comp.nus.edu.sg/∼leews/publications/rss08.pdf
   Google Scholar
• Kusano, K. D., & Gabler, H. (2011). Method for estimating time to collision at braking in real-world, lead vehicle stopped rear-end crashes for use in pre-crash system design. SAE International Journal of Passenger Cars-Mechanical Systems, 4(2011-01-0576), 435–443.
   Google Scholar
• Kusano, K. D., & Gabler, H. C. (2012). Safety benefits of forward collision warning, brake assist, and autonomous braking systems in rear-end collisions. IEEE Transactions on Intelligent Transportation Systems, 13(4), 1546–1555.
   Web of Science ®Google Scholar
• Loewenau, J., Gresser, K., Wisselmann, D., Richter, W., Rabel, D., & Durekovic, S. (2006). Dynamic pass prediction—A new driver assistance system for superior and safe overtaking. Advanced microsystems for automotive applications 2006 (pp. 67–77). Berlin/Heidelberg: Springer.
   Google Scholar
• Naranjo, J. E., Gonzalez, C., Garcia, R., & De Pedro, T. (2008). Lane-change fuzzy control in autonomous vehicles for the overtaking maneuver. IEEE Transactions on Intelligent Transportation Systems, 9(3), 438–450.
   Web of Science ®Google Scholar
• Ng, M., & Sathasivan, K. (2014). Probabilistic modeling of erroneous human response to In-Vehicle route guidance systems: A first look. Journal of Intelligent Transportation Systems, 18(2), 131–137.
   Web of Science ®Google Scholar
• Ong, S. C., Png, S. W., Hsu, D., & Lee, W. S. (2010). Planning under uncertainty for robotic tasks with mixed observability. The International Journal of Robotics Research, 29(8), 1053–1068.
   Web of Science ®Google Scholar
• Ortiz-García, J. J., Costello, S. B., & Snaith, M. S. (2006). Derivation of transition probability matrices for pavement deterioration modeling. Journal of Transportation Engineering, 132(2), 141–161.
   Web of Science ®Google Scholar
• Paielli, R. A., & Erzberger, H. (1997). Conflict probability estimation for free flight. Journal of Guidance, Control, and Dynamics, 20(3), 588–596.
   Web of Science ®Google Scholar
• Petrov, P., & Nashashibi, F. (2014). Modeling and nonlinear adaptive control for autonomous vehicle overtaking. IEEE Transactions on Intelligent Transportation Systems, 15(4), 1643–1656.
   Web of Science ®Google Scholar
• Pineau, J., Gordon, G., & Thrun, S. (2003, August). Point-based value iteration: An anytime algorithm for POMDPs. In IJCAI International Joint Conference on Artificial Intelligence (pp. 1025–1032).
   Google Scholar
• Puterman, M. L. (2014). Markov decision processes: discrete stochastic dynamic programming. Hoboken, NJ: John Wiley & Sons.
   Google Scholar
• Russell, S. J., & Norvig, P. (1995). A modern approach: Artificial Intelligence. Englewood Cliffs, NJ: Prentice-Hall.
   Google Scholar
• Sabbadin, R. (2001). Possibilistic markov decision processes. Engineering Applications of Artificial Intelligence, 14(3), 287–300.
   Web of Science ®Google Scholar
• Salmon, P. M., Regan, M. A., & Johnston, I. (2005). Human error and road transport: Phase one—Literature review ( No. 256).
   Google Scholar
• Sezer, V., Bandyopadhyay, T., Rus, D., Frazzoli, E., & Hsu, D. (2015, September). Towards autonomous navigation of unsignalized intersections under uncertainty of human driver intent. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 3578–3585). IEEE.
   Google Scholar
• Shamir, T. (2004). How should an autonomous vehicle overtake a slower moving vehicle: Design and analysis of an optimal trajectory. IEEE Transactions on Automatic Control, 49(4), 607–610.
   Web of Science ®Google Scholar
• Shani, G., Brafman, R. I., & Shimony, S. E. (2007, January). Forward Search Value Iteration for POMDPs. In IJCAI International Joint Conference on Artificial Intelligence, (pp. 2619–2624).
   Google Scholar
• Smallwood, R. D., & Sondik, E. J. (1973). The optimal control of partially observable Markov processes over a finite horizon. Operations Research, 21(5), 1071–1088.
   Web of Science ®Google Scholar
• Smith, T., & Simmons, R. (2004, July). Heuristic search value iteration for POMDPs. Proceedings of the 20th Conference on Uncertainty in Artificial Intelligence (pp. 520–527). AUAI Press.
   Google Scholar
• Smith, T., & Simmons, R. (2012). Point-based POMDP algorithms: Improved analysis and implementation. arXiv preprint arXiv:1207.1412.
   Google Scholar
• Tapani, A. (2012). Vehicle trajectory effects of adaptive cruise control. Journal of Intelligent Transportation Systems, 16(1), 36–44.
   Web of Science ®Google Scholar
• Thrun, S., Burgard, W., & Fox, D. (2005). Probabilistic robotics. Cambridge, MA: MIT Press.
   Google Scholar
• Toledo-Moreo, R., Santa, J., & Zamora-Izquierdo, M. (2009). A cooperative overtaking assistance system. Planning, Perception and Navigation for Intelligent Vehicles (PPNIV), 50.
   Google Scholar
• Treat, J. R., Tumbas, N. S., McDonald, S. T., Shinar, D., & Hume, R. D. (1979). Tri-level study of the causes of traffic accidents. executive summary ( No. DOTHS034353579TAC (5) Final Rpt).
   Google Scholar
• Vahidi, A., & Eskandarian, A. (2003). Research advances in intelligent collision avoidance and adaptive cruise control. IEEE Transactions on Intelligent Transportation Systems, 4(3), 143–153.
   Web of Science ®Google Scholar
• Vinel, A., Belyaev, E., Egiazarian, K., & Koucheryavy, Y. (2012). An overtaking assistance system based on joint beaconing and real-time video transmission. IEEE Transactions on Vehicular Technology, 61(5), 2319–2329.
   Web of Science ®Google Scholar
• Wang, F., Yang, M., & Yang, R. (2009). Conflict-probability-estimation-based overtaking for intelligent vehicles. IEEE Transactions on Intelligent Transportation Systems, 10(2), 366–370.
   Web of Science ®Google Scholar
• Wei, J., Dolan, J. M., Snider, J. M., & Litkouhi, B. (2011, May). A point-based mdp for robust single-lane autonomous driving behavior under uncertainties. IEEE International Conference on Robotics and Automation (ICRA) (pp. 2586–2592). IEEE.
   Google Scholar