Transportation network redundancy: Complementary measures and computational methods

• Published in: Transportation research. Part B: methodological 2018-08, Vol.114, p.68-85
• Main Authors: Xu, Xiangdong, Chen, Anthony, Jansuwan, Sarawut, Yang, Chao, Ryu, Seungkyu
• Format: Article
• Language: English
• Subjects: Computation; Computer applications; Emergency preparedness; Measurement methods; Navigation behavior; Network spare capacity; Redundancy; Route selection; Traffic congestion; Transportation; Transportation networks; Transportation systems; Travel; Travel alternative diversity
• ISSN: 0191-2615; 1879-2367
• DOI: 10.1016/j.trb.2018.05.014

•Develop network-based measures for systematically characterizing the network redundancy.•Develop computational methods for evaluating the network-based redundancy measures.•Extend the route diversity measure to consider effective routes.•Employ optimization-based approach to determine network spare capacity.•Demonstrate the complementary feature of the two network redundancy measures. Redundancy is vital for transportation networks to provide utility to users during disastrous events. In this paper, we develop two network-based measures for systematically characterizing the redundancy of transportation networks: travel alternative diversity and network spare capacity. Specifically, the travel alternative diversity dimension is to evaluate the existence of multiple modes and effective routes available for travelers or the number of effective connections between a specific origin-destination pair. The network spare capacity dimension is to quantify the network-wide residual capacity with an explicit consideration of travelers’ mode and route choice behaviors as well as congestion effect. They can address two fundamental questions in the pre-disaster transportation system evaluation and planning, i.e., "how many effective redundant alternatives are there for travelers in the normal or disruptive event?" and "how much redundant capacity does the network have?" To implement the two measures in practice, computational methods are provided to evaluate the network redundancy. Numerical examples are also presented to demonstrate the features of the two redundancy measures as well as the applicability of the computational methods. The analysis results reveal that the two measures have different characterizations on network redundancy from different perspectives, and they can complement each other by providing meaningful information to both travelers and planners.