A Framework for Intelligent Decision Support System for Traffic Congestion Management System
Mohamad K. Hasan
.
DOI: 10.4236/eng.2010.24037   PDF    HTML     9,140 Downloads   16,787 Views   Citations

Abstract

Traffic congestion problem is one of the major problems that face many transportation decision makers for urban areas. The problem has many impacts on social, economical and development aspects of urban areas. Hence the solution to this problem is not straight forward. It requires a lot of effort, expertise, time and cost that sometime are not available. Most of the existing transportation planning software, specially the most advanced ones, requires personnel with lots practical transportation planning experience and with high level of education and training. In this paper we propose a comprehensive framework for an Intelligent Decision Support System (IDSS) for Traffic Congestion Management System that utilizes a state of the art transportation network equilibrium modeling and providing an easy to use GIS-based interaction environment. The developed IDSS reduces the dependability on the expertise and level of education of the transportation planners, transportation engineers, or any transportation decision makers.

Share and Cite:

M. Hasan, "A Framework for Intelligent Decision Support System for Traffic Congestion Management System," Engineering, Vol. 2 No. 4, 2010, pp. 270-289. doi: 10.4236/eng.2010.24037.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] E. F. Ogunbodede, “Transport Management Techniques of Rapidly Changing Urban Land Use,” The Case of Akure International Journal of Environment and Development, Vol. 1, No. 1, 1998, pp. 81-86.
[2] E. S. Mills, “Studies in the Structure of the Urban Economy,” The Johns Hopkins Press, Baltimore, 1972.
[3] D. C. Gazis, “Optimum Control of a System of Oversaturated Intersections,” Operations Research, Vol. 12, 1964, pp. 815-831.
[4] R. L. Gordon, “A Technique for Control of Traffic at Critical Intersections,” Transportation Science, Vol. 4, 1969, pp. 279-287.
[5] D. Longley, “A Control Strategy for a Congested Computer Controlled Traffic Network,” Transportation Research, Vol. 2, 1968, pp. 391-408.
[6] L. J. Pignataro, W. R. McShane, K. W. Crowley, B. Lee and T. W. Casey, “Traffic control in over saturated conditions,” NCHRP Report, No. 194, 1978.
[7] N. H. Gartner, C. Stamatiadis and P. J. Tarnoff, “Development of Advanced Traffic Signal Control Strategies for Intelligent Transportation Systems: Multilevel Design,” Transportation Research Record, Vol. 1494, 1995, pp. 98-105.
[8] D. J. Quinn, “A review of queue management strategies,” Traffic Engineering and Control, Vol. 33, No. 11, 1992, pp. 600-605.
[9] A. K. Rathi, “A Control Strategy for High Traffic Density Sector,” Transportation Research B, Vol. 22, No. 2, 1988, pp. 81-101.
[10] A. K. Rathi, “Traffic metering: An Effectiveness Study,” Transportation Quarterly, Vol. 45, No. 3, 1991, pp. 421- 440.
[11] T. S. Reddy, E. Madhu and J. V. R. Reddy, “TSM Actions to Improve the Traffic Operations-A Case Study,” ACE, Vol. 2, 2002, pp. 922-932.
[12] J. V. R. Reddy, “Application of TSM Actions-A Case Study on Mathura Road in Delhi,” Master’s Thesis, University of Baroda, Vadodra, 1998.
[13] J. M. Thomson, “Reflections on the Economics of Traffic congestion,” Journal of Transport Economics and Policy, Vol.32, No. 1, 1998, pp. 93-112.
[14] Adefolalu, “Traffic Management and Enhanced Urban Environment in Nigeria: A Discussion,” In: E. O. Adeniyi and I. B. Bell-Imam Ed., Op Cit, 1977.
[15] S. O. Oyefesobi, “Measures to Improve Traffic Flow and Reduce Road Accidents in Nigeria,” In: S. O. Onakomaiya and K. F. Ekanem Ed., Transportation in Nigerian. National Development Proceedings of a National Conference, Ibadan, July 1977, pp. 4-9.
[16] J. M. A. Orioke, “Traffic Education and Flow in Ibadan City,” In: S. O. Onakomaiya and N. F. Ekanm Ed., Op. Cited, 1981.
[17] M. A. Kennedy and K. Walter, “TSM Measures for Major Activity Centers,” Transportation Engineering Journal, Vol. 105, No. 5, 1979, pp. 499-511.
[18] E. Lindquist, “Assessing Effectiveness Measures in the ISTEA Management Systems,” Southwest Region University Transportation Center, Texas Transportation Institute, College Station, Texas, 1999.
[19] http://www.countyofkings.com/kcag/Plans_Programs/Regional%20Transportation %20Plan%20Section/Final-TS
[20] http://www.madisonareampo.org/Plan%20Elements/CongstMngt.pdf
[21] http://www.marc.org/transportation/cms/policy.pdf
[22] http://www.gvmc.org/transportation/CongestionManage
[23] S. Ossowski, J. Hernandez, M. Belmonte, A. Fernandez, A. Garcıa-Serrano, J. Pe´rez-de-la-Cruz, J. Serrano and F. Triguero, “Decision Support for Traffic Management Based on Organizational and Communicative Multiagent Abstractions,” Transportation Research Part C, Vol. 13, 2005, pp. 272-298.
[24] S. French, “Decision Analysis and Decision Support Systems,” University of Manchester, Manchester, 2000.
[25] M. Silver, “Systems that Support Decision Makers,” John Wiley, Berlin, 1991.
[26] M. Klein and L. Methlie, “Knowledge-Based Decision Support Systems,” John Wiley, Berlin, 1995.
[27] J. Hernandez and J. Serrano, “Environmental Emergency Management Supported by Knowledge Modelling Techniques,” AI Communications, Vol. 14, No. 1, 2001, pp. 13-22.
[28] J. Hernandez and J. Serrano, “Reflective Knowledge Models to Support an Advanced HCI for Decision Management,” Expert Systems with Applications, Vol. 19, No. 4, 2000, pp. 289-304.
[29] I. Vlahavas, N. Bassiliades, I. akellariou, M. Molina, S. Ossowski, I. Futo, Z. Pasztor, J. Szeredi, I. Velbitskiyi, S. Yershov and I. Netesin, “Expernet—An Intelligent multi-agent System for WAN Management,” IEEE Intelligent Systems, Vol. 16, No. 7, 2002, p. 62.
[30] J. Cuena, S. Ossowski, “Distributed models for decision support,” In: Weiss Ed., MIT Press, Cambridge, 1999, pp. 459-504.
[31] S. Ossowski, J. Hernandez, C. Iglesias and A. Fernandez, “Engineering Agent Systems for Decision Support,” In: T. Zambonelli Eds., Engineering Societies in an Agent World III, Springer, Berlin, 2002, pp. 234-274.
[32] C. Iglesias, M. Garijo Ayestara´n and J. Gonza´lez, “A Survey of Agent-Oriented Methodologies,” Intelligent Agents V, Springer, Berlin, 1999, pp. 317-330.
[33] K. Hoa Dam, M. Winikoff, “Comparing agent-oriented methodologies,” In: Giorgini et al. Eds., Agent-Oriented Information Systems, Springer, Berlin, 2003, pp. 78-93.
[34] C. W. Holsapple, “Decision Support Systems. Encyclopedia of Information Systems,” Vol. 1, 2003, pp. 551- 565.
[35] H. L. Zhang, “Agent-Based Open Connectivity for Decision Support Systems,” Ph.D. Thesis, School of Computer Science and Mathematics, Victoria University, 2007.
[36] M. K. Hasan and H. M. Dashti, “A Multiclass Simultaneous Transportation Equilibrium Model,” Networks and Spatial Economics, Vol. 7, No. 3, 2007, pp. 197-211.
[37] J. De Cea, J. E. Fernandez, V. Dekock, A. Soto and T. L.Friesz, “ESTRAUS: A Computer Package for Solving Supply-Demand Equilibrium Problem on Multimodal urban Transportation Networks with Multiple User classes,” The Annual Meeting of the Transportation Research Board, Washington, DC, 2003.
[38] M. Florian, J. H. Wu and S. He, “A Multi-Class Multi-Mode Variable Demand Network Equilibrium Model with Hierarchical Logit Structures,” In: Current Trends, M. Gendreau and P. Marcotte Eds. Dordrecht, 2002, pp. 1131-1119.
[39] D. E. Boyce, H. Bar-Gera, “Multiclass Combined Models for Urban Travel Forecasting,” Networks and Spatial Economics, Vol. 4, 2004, pp.115-124.
[40] J. De Cea, and J. E. Fernandez, “Transit Assignment for Congested Public Transport Systems: An Equilibrium Model,” Transportation Science, Vol. 27, No. 2, 1993, pp. 133-147.
[41] K. N. A. Safwat, and T. L. Magnanti, “A Combined Trip Generation, Trip Distribution, Modal Split and Traffic Assignment Model,” Transportation Science, Vol. 22, No. 1, 1988, pp. 14-30.
[42] N. Oppenheim, “Urban Travel Demand Modeling: From Individual Choices to General Equilibrium,” John Wiley and Sons, New York, 1995.
[43] B. Ran and D. E. Boyce, “Modeling Dynamic Trans- portation Networks,” Springer-Verlag, Berlin, 1996.
[44] M. J. Smith, “The Existence, Uniqueness and Stability of Traffic Equilibria,” Transportation Research B, Vol. 13, 1979, pp. 295-304.
[45] M. J. Smith, “The Existence and Calculation of Traffic Equilibria,” Transportation Research B, Vol. 17, 1983, pp. 291-303.
[46] S. C. Dafermos, “An Iterative Scheme for Variational Inequalities,” Mathematical Programming, Vol. 26, 1983, pp. 40-47.
[47] S. C. Dafermos, “Relaxation Algorithm for the General Asymmetric Traffic Equilibrium Problem,” Transportation Science, Vol. 16, No. 2, 1982, pp. 231-240.
[48] M. Florian and H. Spiess, “The Convergence of Diagonalization Algorithms for Asymmetric Network Equilibrium Problems,” Transportation Research B, Vol. 16, 1982, pp. 447-483.
[49] H. S. Mahmassani and K. C. Mouskos, “Some Numerical Results on the Diagonalization Network Assignment Algorithm with Asymmetric Interactions between Cars and Trucks,” Transportation Research B, Vol. 22, 1988, pp. 275-290.
[50] Y. Sheffi, “Urban Transportation Networks: Equilibrium Analysis with Mathematical Programming Methods,” Prentice-Hall, Englewoods Cliffs, 1985.
[51] K. N. A. Safwat and B. Brademeyer, “Proof of Global Convergence of an Efficient Algorithm for Predicting Trip Generation, Trip Distribution, Modal Split and Traffic Assignment Simultaneously on Large-Scale Networks,” International Journal of Computer and Mathematics with Applications, Vol. 16, No. 4, 1988, pp. 269- 277.
[52] S. Rosenbloom, “Peak-Period Traffic Congestion: A State-Of-The-Art Analysis and Evaluation Of Effective Solutions,” Transportation, Vol. 7, 1978, pp. 167-191.
[53] T. Efraim, et al., “Decision Support and Business Intelligence Systems,” 8th Edition, Pearson Prentice Hall, New Jersey, 2007.
[54] W. Inmon, “Building the Data Warehouse, 4th Edition, Wiley, New York, 2005.
[55] D. Boyce, “Forecasting Travel on Congested Urban Transportation Networks: Review and Prospects for Network Equilibrium Models,” Networks and Spatial Economics, Vol. 7, 2007, pp. 99-128.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.