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

Обзор методов оценки дорожных транспортных заторов для создания устойчивой и адаптивной транспортной системы
Tanzina Afrin, Nita Yodo
2020-06-07

congestion measuresresilient transportation systemroad traffic congestionsustainable transportationtraffic management
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.
1
Accurate identification and quantification of congestion are presented as essential for selecting mitigation strategies and improving transportation sustainability and resilience.
2
Data analysis identifies the respective advantages and disadvantages of each congestion measure.
3
Different congestion measures produce significantly different congestion-state values, despite indicating similar overall congestion trends.
4
The paper surveys and compares currently available road traffic congestion measures using daily and weekly historical traffic datasets.
5
The study provides guidance for developing more sustainable and resilient traffic management systems.

road traffic congestion

measurement and quantification of congestion states and trends using historical traffic data

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2020-06-07
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Tanzina Afrin
Nita Yodo
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