Stephen G. Ritchie


Professor, Civil & Environmental Engineering
The Henry Samueli School of Engineering

PH.D., Cornell University

Phone: (949) 824-4214, 6848
Fax: (949) 824-8385
Email: sritchie@uci.edu

University of California, Irvine

Mail Code: 3600
Irvine, CA 92697
Research Interests
Transportation Systems Engineering
URL
Research Abstract
Artificial Intelligence Applications for Improving Highway Systems
Investigator: S.G. Ritchie
Research Assistants: B. Abdulhai, M. Kaseko, and H. Zhang
Support: National Science Foundation Presidential Young Investigator Award


This award is permitting continued research into state-of-the-art applications of artificial intelligence technology to improve the management, operation, and rehabilitation of the nation's highway system. Specific areas of study include neural network models, real-time knowledge-based expert systems, methods for integrating multiple knowledge sources in a real-time environment, and the application of these techniques to highway pavement management, non-destructive evaluation and condition assessment, and the rapidly emerging field of intelligent vehicle-highway systems with emphasis on advanced traffic management systems.


Neural Network Models for Automated Detection of Non-Recurring Traffic Congestion
Investigator: S.G. Ritchie
Research Assistants: B. Abdulhai, K. Cheu, S. Khan, R. Komerska, and J. Sheu
Undergraduate Research Assistant: S. Tvedten
Support: California Department of Transportation
Hughes Ground Systems Company
Hughes Missile Systems Company


The goal of this research is to investigate, assess, and develop neural network models for automated detection of non-recurring congestion in integrated freeway and arterial traffic networks. Such capabilities are fundamental to most currently proposed intelligent vehicle-highway systems projects, where advanced systems are required for effective surveillance, control, and management of large and complex networks. A neural networks approach is being used for detecting non-recurring traffic congestion because the problem is viewed as one of pattern recognition. A spatially determined network of sensors or loop detectors provides estimates of the "patterns" associated with anomalous or unusual flow conditions, which then can be verified and responded to by an operator with decision support provided by the system.


Neural Network Models for Freeway Traffic Flow Modeling and Real-Time Ramp Control
Investigator: S.G. Ritchie
Research Assistants: P. Mohta and H. Zhang
Support: California Department of Transportation


This project is investigating the development of neural network models for nonlinear, dynamic modeling of freeway traffic flows, and for advanced hierarchical adaptive control of local and integrated freeway segments. It is hoped that these methods will result in improved real-time operation and control capabilities for integrated freeway and arterial networks.


Real-Time Decision Support for Traffic Surveillance and Control Investigator: S.G. Ritchie
Research Assistants: F. Logi, B. Shao, and R. Stack
Support: California Department of Transportation
GenSym Corporation


The objective of this research is to investigate potential opportunities for real-time knowledge-based expert systems to provide advanced decision support to the staffs of major freeway surveillance and control centers.
Publications
Logi, F. and S. Ritchie (1997). "A knowledge - Based System for integrated Freeway and Arterial Incident Management and Control: Implementation and Validation Results." Proceedings, 8th International Federation of Automated Control (IFAE) Symposium on Transportation System, China, Greece. Edited by M. Papogeorgiou and A. Pouliezos.
 
Kang, S. and S. Ritchie (1998). "Prediction of Short-Term Freeway Traffic Volume Using Recursive Least Squares and Lattice Filtering." Proceedings, 5th International Conference on Application of Advanced Technologies in Transportation, Newport Beach, USA. Edited by C. Hendrickson and S. Ritchie. American Society of Civil Engineers.
 
Logi, F. and S. Ritchie (1998). "A Distributed Approach to Network-Wide Traffic Control Management." Proceedings, 5th International Conference on Application of Advanced Technologies in Transportation, Newport Beach, USA. Edited by C. Hendricksen and S. Ritchie. American Society of Civil Engineers.
 
Sheu, J. and S. Ritchie (1998). "Prototype of a New Framework for Red-Time Road Traffic Congestion Detection." Proceedings, 5th International Conference on Application of Advanced Technologies in Transportation, Newport Beach, USA. Edited by C. Hendricksen and S. Ritchie. American Society of Civil Engineers.
 
Zhang, H. , S.G. Ritchie and W.W. Recker (1996). "Some General Results On the Optimal Ramp Control Problem." Transportation Research C, Pergamon Press.
 
Cheu, R.L. and S.G. Ritchie (1995). "Automated Detection of Lane-Blocking Freeway Incidents Using Artificial Neural Networks." Transportation Research C, Pergamon Press.
Research Center
UCI Institute of Transportation Studies
Last updated
01/08/2016