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Estimation of saturation flow at signalised intersections of developing cities: a micro-simulation modelling approach

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  • Hossain, M.

Abstract

Traffic characteristics and operations at the signalised intersections of developing cities are significantly different from those at the similar intersections of cities in developed countries. Considering this, a new microscopic simulation technique, where a co-ordinate approach to modelling vehicle location is adopted, has been used for modelling the traffic operations at signalised intersections of developing cities. The model has been calibrated and validated on the basis of data collected from Dhaka, the capital of Bangladesh. It has been found that the concept of passenger car unit (PCU), which is widely used as a signal design parameter, is not applicable in case of mixed traffic comprising of both motorised and non-motorised vehicles. Therefore, using the developed simulation model the saturation flows at signalised intersections are investigated in an aggregate form of vehicles per hour. It has also been found that saturation flows in terms of aggregate vehicles are very much dependent on the approach width, turning proportion and composition of the traffic mix. Using the simulation results, an equation has also been regressed in order to be able to estimate the saturation flow from the influencing variables like road width, turning proportion, percentage of heavy and non-motorised vehicles.

Suggested Citation

  • Hossain, M., 2001. "Estimation of saturation flow at signalised intersections of developing cities: a micro-simulation modelling approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(2), pages 123-141, February.
    • Handle: RePEc:eee:transa:v:35:y:2001:i:2:p:123-141
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    1. Paul L. Olson & Richard W. Rothery, 1961. "Driver Response to the Amber Phase of Traffic Signals," Operations Research, INFORMS, vol. 9(5), pages 650-663, October.
    2. Kimber, R. M. & McDonald, M. & Hounsell, N., 1985. "Passenger car units in saturation flows: Concept, definition, derivation," Transportation Research Part B: Methodological, Elsevier, vol. 19(1), pages 39-61, February.
    3. Hossain, Moazzem & Mcdonald, M., 1998. "Modelling the impacts of reducing non-motorised traffic in urban corridors of developing cities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(4), pages 247-260, May.
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    1. Egbendewe-Mondzozo, Aklesso & Higgins, Lindsey M. & Shaw, W. Douglass, 2010. "Red-light cameras at intersections: Estimating preferences using a stated choice model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(5), pages 281-290, June.
    2. Tan, Jiyuan & Li, Li & Li, Zhiheng & Zhang, Yi, 2013. "Distribution models for start-up lost time and effective departure flow rate," Transportation Research Part A: Policy and Practice, Elsevier, vol. 51(C), pages 1-11.
    3. Saha, Arpita & Chakraborty, Souvik & Chandra, Satish & Ghosh, Indrajit, 2018. "Kriging based saturation flow models for traffic conditions in Indian cities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 38-51.

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