IoT Based Traffic Management in Smart Cities

Farheen, Asma; Ashwini, S; Priyanka, Kosireddy; Divya, P. R.; R.Bhagya,

doi:10.1007/978-3-030-03146-6_121

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…As computational technologies advance rapidly, the conventional traffic management systems have evolved to become more intelligent with the help of IoT (Internet of Things). IoT-based traffic management systems and congestion mitigation techniques are often developed for smart urban areas [27,78,79]. Different data-driven approaches are employed to predict the time, probability, and the level of congestion [29,[80][81][82].…”

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confidence: 99%

A Survey of Road Traffic Congestion Measures towards a Sustainable and Resilient Transportation System

2020

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Traffic congestion is a perpetual problem for the sustainability of transportation development. Traffic congestion causes delays, inconvenience, and economic losses to drivers, as well as air pollution. Identification and quantification of traffic congestion are crucial for decision-makers to initiate mitigation strategies to improve the overall transportation system’s sustainability. In this paper, the currently available measures are detailed and compared by implementing them on a daily and weekly traffic historical dataset. The results showed each measure showed significant variations in congestion states while indicating a similar congestion trend. The advantages and disadvantages of each measure are identified from the data analysis. This study summarizes the current road traffic congestion measures and provides a constructive insight into the development of a sustainable and resilient traffic management system.

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