A resilience-oriented approach for quantitatively assessing recurrent spatial-temporal congestion on urban roads

Traffic congestion brings not only delay and inconvenience, but other associated national concerns, such as greenhouse gases, air pollutants, road safety issues and risks. Identification, measurement, tracking, and control of urban recurrent congestion are vital for building a livable and smart comm...

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Bibliographic Details
Published in:PloS one 2018-01, Vol.13 (1), p.e0190616-e0190616
Main Authors: Tang, Junqing, Heinimann, Hans Rudolf
Format: Article
Language:English
Subjects:
Air pollution
Analysis
Biology and Life Sciences
Civil engineering
Control
Datasets
Disturbance
Documentation
Driving conditions
Earth Sciences
Ecology and Environmental Sciences
Elasticity
Engineering and Technology
Environmental risk
Greenhouse effect
Greenhouse gases
Metadata
Methods
Multiplexing
Outdoor air quality
Parameter identification
Parameter robustness
Parameter sensitivity
Phase transitions
Physical Sciences
Pollutants
Research and Analysis Methods
Resilience
Risk assessment
Roads & highways
Robustness
Safety engineering
Statistical analysis
Streets
Studies
Tracking control
Traffic
Traffic accidents & safety
Traffic congestion
Traffic delay
Traffic flow
Transportation planning
Vehicles
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Summary:Traffic congestion brings not only delay and inconvenience, but other associated national concerns, such as greenhouse gases, air pollutants, road safety issues and risks. Identification, measurement, tracking, and control of urban recurrent congestion are vital for building a livable and smart community. A considerable amount of works has made contributions to tackle the problem. Several methods, such as time-based approaches and level of service, can be effective for characterizing congestion on urban streets. However, studies with systemic perspectives have been minor in congestion quantification. Resilience, on the other hand, is an emerging concept that focuses on comprehensive systemic performance and characterizes the ability of a system to cope with disturbance and to recover its functionality. In this paper, we symbolized recurrent congestion as internal disturbance and proposed a modified metric inspired by the well-applied "R4" resilience-triangle framework. We constructed the metric with generic dimensions from both resilience engineering and transport science to quantify recurrent congestion based on spatial-temporal traffic patterns and made the comparison with other two approaches in freeway and signal-controlled arterial cases. Results showed that the metric can effectively capture congestion patterns in the study area and provides a quantitative benchmark for comparison. Also, it suggested not only a good comparative performance in measuring strength of proposed metric, but also its capability of considering the discharging process in congestion. The sensitivity tests showed that proposed metric possesses robustness against parameter perturbation in Robustness Range (RR), but the number of identified congestion patterns can be influenced by the existence of ϵ. In addition, the Elasticity Threshold (ET) and the spatial dimension of cell-based platform differ the congestion results significantly on both the detected number and intensity. By tackling this conventional problem with emerging concept, our metric provides a systemic alternative approach and enriches the toolbox for congestion assessment. Future work will be conducted on a larger scale with multiplex scenarios in various traffic conditions.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0190616