Planning for autonomous cars that leverage effects on human actions

Robotics: Science and Systems

Volumn 12, Issue , 2016, Pages

  Sadigh, Dorsa ^a   Sastry, Shankar ^a   Seshia, Sanjit A ^a   Dragan, Anca D ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DYNAMICAL SYSTEMS; HUMAN ROBOT INTERACTION; INVERSE PROBLEMS; REINFORCEMENT LEARNING; ROBOT PROGRAMMING; ROBOTICS;

HUMAN ACTIONS; HUMAN DRIVERS; INVERSE REINFORCEMENT LEARNING; LEVERAGE EFFECTS; REWARD FUNCTION; ROBOT PLAN; TWO-LANE; USER STUDY;

AUTONOMOUS VEHICLES;

EID: 85041945463     PISSN: None     EISSN: 2330765X     Source Type: Conference Proceeding    
DOI: 10.15607/rss.2016.xii.029     Document Type: Conference Paper

References (29)

1. Pieter Abbeel and Andrew Y Ng. Exploration and apprenticeship learning in reinforcement learning. In Proceedings of the 22nd international conference on Machine learning, pages 1-8. ACM, 2005.
2. Galen Andrew and Jianfeng Gao. Scalable training of L1-regularized log-linear models. In Proceedings of the 24th international conference on Machine learning, pages 33-40. ACM, 2007.
3. Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, James Bergstra, Ian J. Goodfellow, Arnaud Bergeron, Nicolas Bouchard, and Yoshua Bengio. Theano: new features and speed improvements. Deep Learning and Unsupervised Feature Learning NIPS 2012 Workshop, 2012.
4. James Bergstra, Olivier Breuleux, Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, Guillaume Desjardins, Joseph Turian, David Warde-Farley, and Yoshua Bengio. Theano: a CPU and GPU math expression compiler. In Proceedings of the Python for Scientific Computing Conference (SciPy), June 2010.Oral Presentation.
5. MWMG Dissanayake, Paul Newman, Steven Clark, Hugh F Durrant-Whyte, and Michael Csorba. A solution to the simultaneous localization and map building (SLAM) problem. Robotics and Automation, IEEE Transactions on, 17(3):229-241, 2001.
6. Paolo Falcone, Francesco Borrelli, Jahan Asgari, Hongtei Eric Tseng, and Davor Hrovat. Predictive active steering control for autonomous vehicle systems. IEEE Transactions on Control Systems Technology, 15(3): 566-580, May 2007.
7. Paolo Falcone, Francesco Borrelli, H Eric Tseng, Jahan Asgari, and Davor Hrovat. Integrated braking and steering model predictive control approach in autonomous vehicles. In Advances in Automotive Control, volume 5, pages 273-278, 2007.
8. Paolo Falcone, H. Eric Tseng, Francesco Borrelli, Jahan Asgari, and Davor Hrovat. MPC-based yaw and lateral stabilisation via active front steering and braking. Vehicle System Dynamics, 46(sup1):611-628, September 2008.
9. Alison Gray, Yiqi Gao, J Karl Hedrick, and Francesco Borrelli. Robust predictive control for semi-autonomous vehicles with an uncertain driver model. In Intelligent Vehicles Symposium (IV), 2013 IEEE, pages 208-213. IEEE, 2013.
10. Christoph Hermes, Christian Wohler, Kurt Schenk, and Franz Kummert. Long-term vehicle motion prediction. In 2009 IEEE Intelligent Vehicles Symposium, pages 652-657, 2009.
11. Markus Kuderer, Henrik Kretzschmar, Christoph Sprunk, and Wolfram Burgard. Feature-based prediction of trajectories for socially compliant navigation. In Proceedings of Robotics: Science and Systems, Sydney, Australia, July 2012.doi: 10.15607/RSS.2012.VIII.025.
12. Markus Kuderer, Shilpa Gulati, and Wolfram Burgard. Learning driving styles for autonomous vehicles from demonstration. In Proceedings of the IEEE International Conference on Robotics & Automation (ICRA), Seattle, USA, volume 134, 2015.
13. Stéphanie Lefèvre, Ashwin Carvalho, Yiqi Gao, H Eric Tseng, and Francesco Borrelli. Driver models for personalised driving assistance. Vehicle System Dynamics, 53(12): 1705-1720, 2015.
14. John Leonard, Jonathan How, Seth Teller, Mitch Berger, Stefan Campbell, Gaston Fiore, Luke Fletcher, Emilio Frazzoli, Albert Huang, Sertac Karaman, et al. A perceptiondriven autonomous urban vehicle. Journal of Field Robotics, 25(10):727-774, 2008.
15. Sergey Levine and Vladlen Koltun. Continuous inverse optimal control with locally optimal examples. arXiv preprint arXiv:1206.4617, 2012.
16. Jesse Levinson, Jake Askeland, Jan Becker, Jennifer Dolson, David Held, Soeren Kammel, J Zico Kolter, Dirk Langer, Oliver Pink, Vaughan Pratt, et al. Towards fully autonomous driving: Systems and algorithms. In 2011 IEEE Intelligent Vehicles Symposium (IV), pages 163-168.
17. Brandon Luders, Mangal Kothari, and Jonathan P How. Chance constrained rrt for probabilistic robustness to environmental uncertainty. In AIAA guidance, navigation, and control conference (GNC), Toronto, Canada, 2010.
18. Manfred Morari, CE Garcia, JH Lee, and DM Prett. Model predictive control. Prentice Hall Englewood Cliffs, NJ, 1993.
19. Andrew Y Ng, Stuart J Russell, et al. Algorithms for inverse reinforcement learning. In Proceedings of the 17th international conference on Machine learning, pages 663-670, 2000.
20. Stefanos Nikolaidis, Ramya Ramakrishnan, Keren Gu, and Julie Shah. Efficient model learning from joint-action demonstrations for human-robot collaborative tasks. In Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction, pages 189-196. ACM, 2015.
21. Vasumathi Raman, Alexandre Donzé, Dorsa Sadigh, Richard M Murray, and Sanjit A Seshia. Reactive synthesis from signal temporal logic specifications. In Proceedings of the 18th International Conference on Hybrid Systems: Computation and Control, pages 239-248. ACM, 2015.
22. Dorsa Sadigh and Ashish Kapoor. Safe control under uncertainty. arXiv preprint arXiv:1510.07313, 2015.
23. Masamichi Shimosaka, Tetsuya Kaneko, and Kentaro Nishi. Modeling risk anticipation and defensive driving on residential roads with inverse reinforcement learning. In 2014 IEEE 17th International Conference on Intelligent Transportation Systems (ITSC), pages 1694-1700. IEEE, 2014.
24. Peter Trautman and Andreas Krause. Unfreezing the robot: Navigation in dense, interacting crowds. In 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 797-803.
25. Chris Urmson, Joshua Anhalt, Drew Bagnell, Christopher Baker, Robert Bittner, MN Clark, John Dolan, Dave Duggins, Tugrul Galatali, Chris Geyer, et al. Autonomous driving in urban environments: Boss and the urban challenge. Journal of Field Robotics, 25(8):425-466, 2008.
26. Ramanarayan Vasudevan, Victor Shia, Yiqi Gao, Ricardo Cervera-Navarro, Ruzena Bajcsy, and Francesco Borrelli. Safe semi-autonomous control with enhanced driver modeling. In American Control Conference (ACC), 2012, pages 2896-2903. IEEE, 2012.
27. Michael P Vitus and Claire J Tomlin. A probabilistic approach to planning and control in autonomous urban driving. In 2013 IEEE 52nd Annual Conference on Decision and Control (CDC), pages 2459-2464.
28. Brian D Ziebart. Modeling purposeful adaptive behavior with the principle of maximum causal entropy. 2010.
29. Brian D Ziebart, Andrew L Maas, J Andrew Bagnell, and Anind K Dey. Maximum entropy inverse reinforcement learning. In AAAI, pages 1433-1438, 2008.