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The Robustly-Safe Automated Driving System for Enhanced Active Safety
ISSN: 0148-7191, e-ISSN: 2688-3627
Published March 28, 2017 by SAE International in United States
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Road safety is one of the major concerns for automated vehicles. In order for these vehicles to interact safely and efficiently with the other road participants, the behavior of the automated vehicles should be carefully designed. Liu and Tomizuka proposed the Robustly-safe Automated Driving system (ROAD) which prevents or minimizes occurrences of collisions of the automated vehicle with other road participants while maintaining efficiency. In this paper, a set of design principles are elaborated as an extension of the previous work, including robust perception and cognition algorithms for environment monitoring and high level decision making and low level control algorithms for safe maneuvering of the automated vehicle. The autonomous driving problem in mixed traffic is posed as a stochastic optimization problem, which is solved by 1) behavior classification and trajectory prediction of other road participants, and 2) a unique parallel planner architecture which addresses the efficiency goal in the long term and the safety goal in the short term separately. Moreover, a python-based high fidelity simulation system is developed and extensive simulations are performed to evaluate the effectiveness of the proposed algorithm, where both high level decision making and low level vehicle regulation are considered. Two typical scenarios are studied, driving on freeway and driving in unstructured environments such as parking lots. In the simulation, multiple moving agents representing surrounding vehicles and pedestrians are added to the environment, some of which are controlled by human subjects in order to test the real time response of the automated vehicle.
CitationLiu, C., Chen, J., Nguyen, T., and Tomizuka, M., "The Robustly-Safe Automated Driving System for Enhanced Active Safety," SAE Technical Paper 2017-01-1406, 2017, https://doi.org/10.4271/2017-01-1406.
- Burns L. D., "Sustainable mobility: a vision of our transport future," Nature, vol. 497, pp. 181 – 182, 2013.
- Urmson C., Anhalt J., Bagnell D., Baker C., Bittner R., Clark M., Dolan J., Duggins D., Galatali T., Geyer C. and , "Autonomous driving in urban environments: Boss and the urban challenge," Jounal of Field Robotics, vol. 25, no. 8, pp. 425 – 466, 2008.
- Liu C. and Tomizuka M., "Enabling Safe Freeway Driving for Automated Vehicles," in American Control Conference, 2016.
- Sadigh D., Sastry S., Seshia S. A. and Dragan A. D., "Planning for Autonomous Cars that Leverage Effects on Human Actions," in Proceedings of the Robotics: Science and Systems Conference (RSS), 2016.
- Zhan W., Liu C., Chan C.-Y. and Tomizuka M., "A non-conservatively defensive strategy for urban autonomous driving," in Intelligent Transportation Systems Conference (ITSC), 2016.
- Paden B., Cap M., Yong S. Z., Yershov D. and Frazzoli E., "A Survey of Motion Planning and Control Techniques for Self-driving Urban Vehicles," in arXiv preprint arXiv:1604.07446, 2016.
- Dolgov D., Thrun S., Montemerlo M. and Diebel J., "Practical search techniques in path planning for autonomous driving," Ann Arbor, vol. 1001, p. 48105, 2008.
- Frazzoli E., Dahleh M. A. and Feron E., "Real-time motion planning for agile autonomous vehicles," Journal of Guidance, Control, and Dynamics, vol. 25, no. 1, pp. 116 – 129, 2002.
- Levinson J., Askeland J., Becker J., Dolson J., Held D., Kammel S., Kolter J. Z., Langer D., Pink O., Pratt V. and , "Towards fully autonomous driving: Systems and algorithms," in IEEE Intelligent Vehicles Symposium (IV), 2011.
- Rigatos G. and Tzafestas S., "Extended Kalman filtering for fuzzy modelling and multi-sensor fusion," Mathematical and computer modelling of dynamical systems, vol. 13, no. 3, pp. 251 –266, 2007.
- "Next generation simulation (NGSIM) high-level data plan," [Online]. Available: http://ops.fhwa.dot.gov/trafficanalysistools/ngsim.htm..
- Liu C. and Tomizuka M., "Control in a safe set: Addressing safety in human robot interactions," in ASME Dynamics and Control Conference, 2014.
- Liu C. and Tomizuka M., "Safe Exploration: Addressing Various Uncertainty Levels in Human Robot Interactions," in American Control Conference, 2015.
- Shladover S. E., Desoer C. A., Hedrick J. K., Tomizuka M., Walrand J., Zhang W.-B., McMahon D. H., Peng H., Sheikholeslam S. and McKeown N., "Automated vehicle control developments in the PATH program," IEEE Transactions on vehicular technology, vol. 40, no. 1, pp. 114 – 130, 1991.
- "Bullit physics library," [Online]. Available: http://www.bulletphysics.org/Bullet/phpBB3/.