Chapter
Apr 26, 2012
Urban Arterial Travel Time Prediction Using State Space Neural Network with Adaptive Filters
Authors: Yan Li [email protected]. and Transportation Infrastructure and Systems Engineering, Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA 24061., Abbas Montasir, and Xiucheng Guo [email protected].Author Affiliations
Publication: International Conference on Transportation Engineering 2009
Abstract
Urban arterial travel time is one of the most critical components for advanced traveler information and advanced traffic management systems. This paper used state space neural network (SSNN) with adaptive filters to predict the urban arterial travel time. The SSNN's network topology is derived from urban travel time prediction problem, so the design of SSNN reflects the relationships that exist in physical traffic systems. To improve SSNN effectiveness, the adaptive filters is proposed to train the SSNN instead of conventional approaches. Model performance was tested with urban arterial data of Odem. Performance of the proposed model is compared with that of SSNN and BP neural network. Results of the comparisons indicate that the proposed model predicts complex nonlinear urban arterial travel times with satisfying effectiveness, robustness and reliability.
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© 2009 American Society of Civil Engineers.
History
Published online: Apr 26, 2012
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ASCE Technical Topics:
- Adaptive systems
- Aerospace engineering
- Artificial intelligence and machine learning
- Computer programming
- Computing in civil engineering
- Engineering fundamentals
- Environmental engineering
- Filters
- Filtration
- Infrastructure
- Neural networks
- Space exploration
- Systems engineering
- Systems management
- Traffic engineering
- Traffic management
- Transportation engineering
- Travel time
- Urban and regional development
- Urban areas
- Water treatment
Authors
Affiliations
Transportation College, Southeast University, Nanjing, Jiangsu, 210096. E-mail: [email protected]. and Transportation Infrastructure and Systems Engineering, Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA 24061.
Abbas Montasir
Transportation Infrastructure and Systems Engineering, Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA 24061.
Transportation College, Southeast University, Nanjing, Jiangsu, 210096. E-mail: [email protected].
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