Adaptive Traffic Light Signalization - Robotics Institute Carnegie Mellon University
Graphical depiction of the Adaptive Traffic Light Signalization project
Adaptive Traffic Light Signalization
Project Head: Stephen Smith

As part of the Traffic21 initiative at CMU, we are investigating the design and application of adaptive traffic signal control strategies for urban road networks. Our research has three broad themes: (1) development of signalization strategies that allow real-time response to shifts in traffic conditions (accidents, traffic dispersal at completion of major events), (2) low-cost deployment of advanced signalization concepts (implying strategies that work well with limiting sensing and methodologies for incremental insertion of adaptive signal technology), and (3) principled coordination of transit systems and personal vehicles through adaptive traffic signal control. We are currently using a microscopic simulation model of the Pittsburgh downtown road network as an experimental evaluation testbed.

Displaying 6 Publications

2013
Conference Paper, Proceedings 23rd International Conference on Automated Planning and Scheduling (ICAPS '13), pp. 434 - 442, June, 2013
Conference Paper, Proceedings of Transportation Research Board 92nd Annual Meeting Compendium of Papers, 2013
2012
Xiao-Feng Xie, Stephen Smith, Liang Lu, and Gregory Barlow
Journal Article, Transportation Research Part C: Emerging Technologies, Vol. 24, pp. 168 - 189, October, 2012
Xiao-Feng Xie, Stephen Smith, and Gregory Barlow
Conference Paper, Proceedings of 22nd International Conference on Automated Planning and Scheduling (ICAPS '12), pp. 323 - 331, June, 2012
2011
Conference Paper, Proceedings 14th International IEEE Conference on Intelligent Transportation Systems (ITSC '11), pp. 879 - 884, October, 2011
PhD Thesis, Tech. Report, CMU-RI-TR-11-17, Robotics Institute, Carnegie Mellon University, July, 2011

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  • Xiao-Feng Xie