Evaluating urban traffic dynamics: a study of mobility in Vellore city

Urban mobility is a significantly increasing challenge in fast-growing cities, where efficient traffic management is crucial to ensure smooth movement and enhance the overall quality of life. The research consists of an in-depth analysis of urban mobility for the city under study using a data-driven approach to address day-to-day traffic challenges. It includes a fusion of traffic flow analysis and vehicle count data with weekend and weekday indicators to develop predictive models. The study evaluates the city’s traffic data by examining peak and off-peak periods. We focus on simple contextual variables – specifically, temporal indicators – our models provide an efficient framework for traffic forecasting in complex environments. The findings underscore that meaningful traffic forecasts can be used to provide practical and scalable solutions for urban planners and administrators to optimize traffic management in rapidly expanding cities.

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Publication Details

Journal
Frontiers in Sustainable Cities
Published
2025-08-26
DOI
https://doi.org/10.3389/frsc.2025.1631748
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
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article

Evaluating urban traffic dynamics: a study of mobility in Vellore city

A. Parthiban, S Parkavi
Frontiers in Sustainable Cities
Traffic Prediction and Management Techniques
article

Evaluating urban traffic dynamics: a study of mobility in Vellore city

A. Parthiban, S Parkavi
article en

Abstract

Urban mobility is a significantly increasing challenge in fast-growing cities, where efficient traffic management is crucial to ensure smooth movement and enhance the overall quality of life. The research consists of an in-depth analysis of urban mobility for the city under study using a data-driven approach to address day-to-day traffic challenges. It includes a fusion of traffic flow analysis and vehicle count data with weekend and weekday indicators to develop predictive models. The study evaluates the city’s traffic data by examining peak and off-peak periods. We focus on simple contextual variables – specifically, temporal indicators – our models provide an efficient framework for traffic forecasting in complex environments. The findings underscore that meaningful traffic forecasts can be used to provide practical and scalable solutions for urban planners and administrators to optimize traffic management in rapidly expanding cities.

Frontiers in Sustainable CitiesVol. 7
Vellore Institute of Technology University (IN)
Openalex Percentile: Top 76%
Traffic Prediction and Management Techniques
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