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Modelling Pedestrian Travel Time and the Design of Facilities: A Queuing Approach

Overview of attention for article published in PLOS ONE, May 2013
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Title
Modelling Pedestrian Travel Time and the Design of Facilities: A Queuing Approach
Published in
PLOS ONE, May 2013
DOI 10.1371/journal.pone.0063503
Pubmed ID
Authors

Khalidur Rahman, Noraida Abdul Ghani, Anton Abdulbasah Kamil, Adli Mustafa, Ahmed Kabir Chowdhury

Abstract

Pedestrian movements are the consequence of several complex and stochastic facts. The modelling of pedestrian movements and the ability to predict the travel time are useful for evaluating the performance of a pedestrian facility. However, only a few studies can be found that incorporate the design of the facility, local pedestrian body dimensions, the delay experienced by the pedestrians, and level of service to the pedestrian movements. In this paper, a queuing based analytical model is developed as a function of relevant determinants and functional factors to predict the travel time on pedestrian facilities. The model can be used to assess the overall serving rate or performance of a facility layout and correlate it to the level of service that is possible to provide the pedestrians. It has also the ability to provide a clear suggestion on the designing and sizing of pedestrian facilities. The model is empirically validated and is found to be a robust tool to understand how well a particular walking facility makes possible comfort and convenient pedestrian movements. The sensitivity analysis is also performed to see the impact of some crucial parameters of the developed model on the performance of pedestrian facilities.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
South Africa 1 1%
Unknown 71 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 17%
Student > Master 11 15%
Student > Bachelor 8 11%
Lecturer > Senior Lecturer 2 3%
Student > Doctoral Student 2 3%
Other 10 14%
Unknown 27 38%
Readers by discipline Count As %
Engineering 21 29%
Design 4 6%
Computer Science 3 4%
Mathematics 3 4%
Economics, Econometrics and Finance 2 3%
Other 9 13%
Unknown 30 42%