Toward Intelligent Variable Message Signs in Freeway Work Zones: Neural Network Model
Publication: Journal of Transportation Engineering
Volume 130, Issue 1
Abstract
An increasingly popular method of managing freeway traffic is to use variable message signs (VMS). A neural network model is presented for real-time control of a VMS system in freeway work zones. The neural network is trained to detect the start of a queue in a work zone and provide a message in the freeway upstream. The travelers are informed about the congestion in a work zone when a queue starts to form. The intelligent VMS system can be trained with data for different periods within a day, such as morning and evening rush hours, nonrush hours during the day, and night, for a more detailed traffic flow prediction over the period of one day. Two different neural network training rules are used: the simple backpropagation (BP) and the Levenberg–Marquardt BP algorithms. The network is trained using data adapted from the measured data. Based on different numerical experiments it is observed that the convergence speed of the Levenberg–Marquardt BP algorithm is at least one order of magnitude faster than the simple BP algorithm for the work zone traffic queue detection problem.
Get full access to this article
View all available purchase options and get full access to this article.
References
Adeli, H.(2001). “Neural networks in civil engineering, 1989–2000.” Comput. Aided Civil and Infrastructure Eng., 16(2), 126–147.
Adeli, H., and Hung, S. L.(1994). “An adaptive conjugate gradient learning algorithm for effective training of multilayer neural networks.” Appl. Math. Comput., 62(1), 81–102.
Adeli, H., and Hung, S. L. (1995). Machine learning—Neural networks, genetic algorithms, and fuzzy systems, Wiley, New York.
Adeli, H., and Karim, A. (2001). Construction scheduling, cost optimization, and management—A new model based on neurocomputing and object technologies, Spon, London.
Adeli, H., and Park, H. S. (1998). Neurocomputing for design automation, CRC, Boca Raton, Fla.
Al-Kaisy, A. F., and Hall, F. L. (2000). “The effect of darkness on the capacity of long-term freeway reconstruction zones.” Transportation Research Circular E-C018, 164–174.
Al-Kaisy, A. F., Zhou, M., and Hall, F. (2000). “New insights into freeway capacity work zones.” Transportation Research Record, 1710, Transportation Research Board, Washington, D.C., 154–160.
Bazaraa, M. S., Sherali, H. D., and Shetty, C. M. (1993). Nonlinear programming theory and algorithms, Wiley, New York.
Chien, S., and Schonfeld, P.(2001). “Optimal work zone length for four-lane highways.” J. Transp. Eng., 127(2), 124–131.
Dixon, K. K., and Hummer, J. E. (1996). Capacity and delay in major freeway construction zones, Center for Transportation Engineering Studies, Dept. of Civil Engineering, North Carolina State Univ.
Dixon, K. K., Hummer, J. E., and Lorscheider, A. R. (1996). “Capacity for North Carolina freeway work zones.” Transportation Research Record, 1529, Transportation Research Board, Washington, D.C., 27–34.
Garber, N. J. and Hoel, L. A. (1999). Traffic and highway engineering, PWS, Boston.
Garber, N. J., and Srinivasan, S. (1998). “Influence of exposure duration on the effectiveness of changeable-message signs in controlling vehicle speeds at work zones.” Transportation Research Record, 1650, Transportation Research Board, Washington, D.C., 62–70.
Hagan, M. T., Demuth, H. B., and Beale, M. (1996). Neural network design, PWS, Boston.
Hagan, M. T., and Menhaj, M. B.(1994). “Training feedforward networks with Marquardt algorithm.” IEEE Trans. Neural Netw., 5(6), 989–993.
Hall, F. L., Hurdle, V. F., and Banks, J. H. (1992). “Synthesis of recent work on nature of speed-flow and flow-occupancy (or density) relationships on freeways.” Transportation Research Record, 1365, Transportation Research Board, Washington, D.C., 12–18.
HCM (1965). Highway capacity manual, Special Rep. No. 87, Highway Research Board, National Research Council, Washington, D.C.
HCM (1985). Highway capacity manual, Special Rep. No. 209, Transportation Research Board, National Research Council, Washington, D.C.
HCM (2000). Highway capacity manual, Transportation Research Board, National Research Council, Washington, D.C.
Krammes, R. A., and Lopez, G. O. (1994). “Updated capacity values for short-term freeway work zone lane closures.” Transportation Research Record, 1442, Transportation Research Board, Washington, D.C., 49–56.
Lewis, R. M. (1989). “Work-zone traffic control concepts and terminology.” Transportation Research Record, 1230, Transportation Research Board, Washington, D.C., 1–11.
Marquardt, D. W.(1963). “An algorithm for least-squares estimation of nonlinear parameters.” J. Soc. Ind. Appl. Math., 11(2), 431–441.
Martinelli, D. R., and Xu, D.(1996). “Delay estimation and optimal length for four-lane divided freeway work zones.” J. Transp. Eng., 122(2), 114–122.
McCoy, P. T., and Mennega, D. J. (1998). “Optimum length of single-lane closures in work zone on rural four-lane freeways.” Transportation Research Record, 1650, Transportation Research Board, Washington, D.C., 55–61.
Rouphail, N. M., and Tiwari, G. (1985). “Flow characteristics at freeway lane closures.” Transportation Research Record, 1035, Transportation Research Board, Washington, D.C., 50–58.
Rumelhart, D. E., Hinton, G. E., and Williams, R. J. (1986). “Learning internal representation by error propagation.” D. E. Rumelhart, James L. McClelland, and the PDP Research Group, Parallel distributed processing: Explorations in the microstructure of cognition, MIT Press, Cambridge, Mass., 318–362.
Vemuri, A. T., Policarpou, M. M., and Pant, P. D.(1998). “Short-term forecasting of traffic delays in highway construction zones using on-line approximators.” J. Math. Comput. Modelling, 27(9–11), 311–322.
Wright, P. H. (1996). Highway engineering, 6th ed., Wiley, New York.
Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 130 • Issue 1 • January 2004
Pages: 83 - 93
Copyright
Copyright © 2004 American Society of Civil Engineers.
History
Received: Oct 25, 2001
Accepted: Feb 12, 2003
Published online: Dec 15, 2003
Published in print: Jan 2004
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.