/Adaptive Traffic Light Signalization

Adaptive Traffic Light Signalization

Portrait of Adaptive Traffic Light Signalization
Head: Stephen Smith
Contact: Stephen Smith
Associated Lab: Intelligent Coordination and Logistics Laboratory
Homepage
Last Project Publication Year: 2013

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
Smart Urban Signal Networks: Initial Application of the SURTRAC Adaptive Traffic Signal Control System
Stephen Smith, Gregory Barlow, Xiao-Feng Xie and Zack Rubinstein

Conference Paper, Proceedings 23rd International Conference on Automated Planning and Scheduling, June, 2013
SURTRAC: Scalable Urban Traffic Control
Stephen Smith, Gregory Barlow, Xiao-Feng Xie and Zack Rubinstein

Conference Paper, Transportation Research Board 92nd Annual Meeting Compendium of Papers, January, 2013
Schedule-driven intersection control
Xiao-Feng Xie, Stephen Smith, Liang Lu and Gregory Barlow

Conference Paper, Transportation Research Part C: Emerging Technologies, 24: 168-189, October 2012., October, 2012
Schedule-Driven Coordination for Real-Time Traffic Network Control
Xiao-Feng Xie, Stephen Smith and Gregory Barlow

Conference Paper, Proceedings 22nd International Conference on Automated Planning and Scheduling, Atibaia, Sao Paulo, Brazil, June 2012., June, 2012
Platoon-Based Self-Scheduling for Real-Time Traffic Signal Control
Xiao-Feng Xie, Gregory Barlow, Stephen Smith and Zack Rubinstein

Conference Paper, Proceedings 14th International IEEE Conference on Intelligent Transportation Systems, Washington DC, October, 2011., October, 2011
Improving memory for optimization and learning in dynamic environments
Gregory Barlow

PhD Thesis, Tech. Report, CMU-RI-TR-11-17, Robotics Institute, Carnegie Mellon University, July, 2011

Current RI People

Past Project People

  • Xiao-Feng Xie
2017-09-13T10:40:14+00:00