Main Article Content

Abstract

Purpose: Level of Service is a widely adopted terminology to determine the efficiency of any transport system. From the literature it was studied that the multiple linear regression models established by many researchers to determine PLoS evolved with addition or removal of one or more physical parameters or with respect to the perception of users from different locations. At an intersection, there is little or no established methodology developed so far to determine a quantitative approach for PLoS similar to Vehicular Level of Service (VLoS). It was also pointed out that under heterogeneous traffic conditions, pedestrians are most vulnerable at intersections and they share the same space with motorized vehicles for crossing movements.


Methodology: Thus, this study was built on the hypothesis that pedestrian delay of a signalized intersection is quantitatively dependent on pedestrian volume, vehicular volume and cycle time. Two signalized intersections operating as fully actuated and fixed cycle time were considered for study for period of four hours each, covering two hours of morning peak and off-peak hour traffic data.


Main Findings: Using various statistical techniques, an empirical model was developed between the pedestrian delay and independent variables namely cycle time, pedestrian volume and vehicular volume. PLoS range was also determined through k-means clustering technique.


Implications: The empirical model developed was validated and the application of this research was also explained.


Novelty: The study is a new quantitative approach to determine PLoS and was limited to two intersections. Increase in the data may improve the accuracy of the model.

Keywords

Empirical Model Pedestrian Level of Service Pedestrian delay Vehicular Volume Cycle time.

Article Details

How to Cite
Gopalakrishnan, A., Ram, S., & Sarkar, P. K. (2018). QUANTITATIVE APPROACH TO DETERMINE PEDESTRIAN DELAY AND LEVEL OF SERVICE AT SIGNALIZED INTERSECTION. International Journal of Students’ Research in Technology & Management, 6(1), 06–13. https://doi.org/10.18510/ijsrtm.2018.612

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