Abstract
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.
Highlights
Continuous growth of motor vehicles has made urban congestion become a serious national problem, one which has been receiving considerable attention from engineers, planners, researchers, and policymakers
Selecting appropriate Key Performance Indicator (KPI) and preparing the spatial-temporal profiles: The resilience-oriented approach is performance-based and an appropriate KPI is needed for indicating various performance levels
There are some potential limitations about this metric and the vehicle trajectory data used [46, 47]
Summary
Continuous growth of motor vehicles has made urban congestion become a serious national problem, one which has been receiving considerable attention from engineers, planners, researchers, and policymakers. The results showed that the time-based approach is more likely to have a high impact as it effectively provides a different perception of congestion and a stronger guidance on major issue identification. Armah et al [8] attempted to study congestion and one of its side effects, air pollution, with a systemic approach. They provided overall systemic thinking flowcharts on urban congestion issue. There are many others and readers can refer to an incomplete list includes: [12,13,14,15] With such ample options of various methods and approaches, an investigation emphasized on comprehensive systemic perspective is still missing for quantitative congestion assessment
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