Abstract
As demonstrated for extreme events, the resilience concept is used to evaluate the ability of a transportation system to resist and recover from disturbances. Motivated by the high cumulative impact of recurrent perturbations on transportation systems, we have investigated resilience quantification as a performance assessment method for high-probability low-impact (HPLI) disturbances such as traffic congestions. Resilience-based metrics are supplementary to conventional travel-time-based indices in literature. However, resilience is commonly quantified as a scalar variable despite its multi-dimensional nature. Accordingly, by hypothesizing increased information gain in performance assessment, we have investigated a multi-dimensional approach (mD-Resilience) for resilience quantification. Examining roadways’ resilience to recurrent congestions as a contributor to sustainable mobility, we proposed to measure resilience with several attributes that characterize the degradation stage, the recovery stage, and possible recovery paths. These attributes were integrated into a performance index by using Data Envelopment Analysis (DEA) as a non-parametric method. We demonstrated the increased information gain by quantifying the performance of major freeways in Los Angeles, California using Performance Measurement System (PeMS) data. The comparison of mD-Resilience approach with the method based on area under resilience curves showed its potential in distinguishing the severity of congestions. Furthermore, we showed that mD-Resilience also characterizes performance from the lens of delay and bottleneck severities.
Highlights
Resilience concept has been traditionally used in the context of extreme events to evaluate the operation of transportation systems
It is clear that extreme disastrous events can dramatically impact the mobility and the performance of transportation systems; high-probability low-impact (HPLI) disturbances can play an important role in reducing the efficiency of such systems, mainly in the form of congestions, which in turn have a significant impact on sustainable mobility
The research efforts that have used resilience for performance assessment of congestion events have argued that the use of resilience concept in the quantification of performance has resulted in added information to conventional metrics, such as the delay in travel time [7] and relative congestion index (RCI) [25], which measures the ratio of travel time in congestion to free flow
Summary
Resilience concept has been traditionally used in the context of extreme events to evaluate the operation of transportation systems. HPLI disturbances cause delays and inconvenience, and result in negative consequences such as air and noise pollution, high energy consumption, lower safety levels, and significant economic loss. These disturbances can happen due to numerous reasons such as bad weather [1], poor condition of local infrastructure [2], different speed regimes, the high volume of traffic [3], or infrastructure design and operational configurations. Several indices are used for the purpose of quantification including Travel Time Index (TTI), Travel Delay, Level of Service (LOS), and Buffer Index, among others These metrics provide information on the severity of potential problems at different spatiotemporal scales.
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