Real-time motion planning methods for autonomous on-road driving: State-of-the-art and future research directions-Reference-Cited by-同舟云学术

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Real-time motion planning methods for autonomous on-road driving: State-of-the-art and future research directions

Published:2015-11 Issue: Volume:60 Page:416-442
ISSN:0968-090X
Container-title:Transportation Research Part C: Emerging Technologies
language:en
Short-container-title:Transportation Research Part C: Emerging Technologies

Author:

Katrakazas Christos,Quddus Mohammed,Chen Wen-Hua,Deka Lipika

Funder

UK Engineering and Physical Sciences Research Council (EPSRC)

Publisher

Elsevier BV

Subject

Computer Science Applications,Transportation,Automotive Engineering,Civil and Structural Engineering

Reference132 articles.

1. Alin, A., Butz, M.V., Fritsch, J., 2012. Incorporating environmental knowledge into Bayesian filtering using attractor functions. In: IEEE Intelligent Vehicles Symposium, pp. 476–481.

2. Althoff, D., Wollherr, D., Buss, M., 2011. Safety assessment of trajectories for navigation in uncertain and dynamic environments. In: 2011 IEEE International Conference on Robotics and Automation, pp. 5407–5412.

3. Model-based probabilistic collision detection in autonomous driving;Althoff;IEEE Trans. Intell. Transport. Syst.,2009

4. Antoniades, A., Kim, H.J., Sastry, S., 2003. Pursuit-evasion strategies for teams of multiple agents with incomplete information. In: 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475), vo. 1, pp. 756–761.

5. Probabilistically safe motion planning to avoid dynamic obstacles with uncertain motion patterns;Aoude;Auton. Robot.,2013

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