Spatio-temporal analysis of public transit gps data: Application to traffic congestion evaluation

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Date

2024

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Aracne Editrice

Abstract

Congestion free mobility has become nearly impossible in most of the metropolitan cities of India especially during peak hours. The understanding of factors inducing congestion demands huge amount of data pertaining to urban traffic. The developed countries have adopted different kinds of automatic data collection systems such as loop detectors, surveillance cameras and radars for the data collection of road traffic condition. In developing countries like India, the collection and monitoring of data related to movement of traffic stream are mostly manual, very time consuming and expensive. In India, Intelligent Transport System (ITS) has been implemented to Mysore City public transport in the year 2012. This study makes use of Global Positioning System (GPS) data of Mysore ITS. The major objective of the present study is to evaluate the congestion on urban roads using public transit GPS data with the help of visualization techniques. Spatio-temporal visualization-based analysis has been carried out to evaluate the traffic congestion patterns of urban roads. Initially, the comparison of traffic states on urban street and arterial road has been carried out. Later, the difference in congestion patterns before and after the operation of grade separator and the impact of route diversion on the congestion patterns have been evaluated. This study shows that public transit GPS data can be a potential data source to evaluate the traffic state or congestion, especially when there are limited sources of traffic data. © 2024, Aracne Editrice. All rights reserved.

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Keywords

Data acquisition, Data visualization, Developing countries, Global positioning system, Intelligent vehicle highway systems, Motor transportation, Roads and streets, Security systems, Traffic congestion, Urban transportation, Visualization, Global positioning system data, Intelligent transport, Intelligent transportation systems, Public transit, Public transport, Spatiotemporal analysis, Spatiotemporal visualization, Traffic state, Transport systems, Urban road, Intelligent systems

Citation

Advances in Transportation Studies, 2024, 62, , pp. 111-124

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