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 OJMSi  Vol.2 No.2 , April 2014
Predicting Traffic Congestion: A Queuing Perspective
Abstract: Mobility is an indispensable activity of our daily lives and road transport is one popular approach to mobility. However road congestion occurrence can be irritating and costly. This work contributes to the modeling and therefore predicting road congestion of a Ghanaian urban road by way of queuing theory using stochastic process and initial value problem framework. The approach is used to describe performance measure parameters, allowing the prediction of the level of queue built up at a signalized intersection as an insight into road vehicular congestion there and how such congestion occurrence can be efficiently managed.
Cite this paper: Lartey, J. (2014) Predicting Traffic Congestion: A Queuing Perspective. Open Journal of Modelling and Simulation, 2, 57-66. doi: 10.4236/ojmsi.2014.22008.
References

[1]   The Ministry of Information Ghana (2011) Meet the Press Series.
www.ghana.gov.gh/index.php/information/meet-the-press/3786-meet-the-press

[2]   Abane, A.M. (1993) Tackling Traffic Congestion in Accra, Ghana: A Road User’s Perspective. Journal of Advanced Transportation, 27, 193-206. http://dx.doi.org/10.1002/atr.5670270205

[3]   Cox, D.R. and Smith, W.L. (1961) Queues. John Wiley, New York.

[4]   Kleinrock, L. (1976) Queueing Systems. John Wiley & Sons, New York.

[5]   Kelly, F.P. (1979) Reversibility and Stochastic Networks. John Wiley & Sons, New York.

[6]   Daduna, H. (2001) Queueing Networks with Discrete Time Scale. Lecture Notes in Computer Science. 2046 Volumes. Springer-Verlag, Berlin Heidelberg, 1-7.

[7]   Kothari, C.R. (2007) Quantitative Techniques. Vigas, Bnagalore.

[8]   Waters, D. (2008) Quantitative Methods for Business. Printice Hall, Essex.

[9]   Gupta, M.P. and Khanna, R.B. (2007) Quantitative Techniques for Decision Making. Prentice Hall, New Delhi.

[10]   Gross, D. and Harris, C. (1998) Fundamentals of Queuing Theory. 3rd Edition, John Wiley, Chichester.

[11]   Forbs, C., Evans, M., Hasting, N. and Peacock, B. (2011) Statistical Distribution. John Wiley & Sons Inc., New York.

[12]   Castanda, L.B., Arunachalam, V. and Dharmaraja, D.D. (2012) Introduction to Probability and Stochastic Processes with Applications. John Wiley, New York.
http://dx.doi.org/10.1002/9781118344972

[13]   Medhi, J. (2003) Stochastic Models in Queueing Theory. 2nd Edition, Esevier Inc., Berlin.

[14]   Calvert, J. and Voxman, W. (1994) Finite Mathematics. McGraw-Hill, New York.

[15]   Weisstein, W. (1984) CRC Concise Encyclopedia of Mathematics. Chapman and Hall, New York.

[16]   Cox, D.R. (1955) A Use of Complex Probabilities in the Theory of Stochastic Processes. Mathematical Proceedings of the Cambridge Philosophical Society, 51, 313-319.

[17]   Krajewski, L.J., Ritzman, L.P. and Malhotra, M.K. (2007) Operations Management: Process and Value Chains. 8th Edition, Printice Hall, New York.

[18]   ONeil, P.V. (1993) Advabced Engineering Mathematics. 3rd Edition, PWS, Boston.

[19]   Boyce, W.E. and Di Prima, R.C. (1992) Elementary Differential Equations and Boundary Value Problems. 5th Edition, John Wiley & Sons, New York.

 
 
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