Robustness assessment of multimodal freight transport networks. (March 2021)

• Record Type: Journal Article
• Authors: He, Zhidong; Navneet, Kumar; van Dam, Wirdmer; Van Mieghem, Piet
• Is Part Of: Reliability engineering & system safety. Volume 207(2021)
• Publication Date: 2021-03
• Subjects: Robustness assessment -- Multimodal transport -- Interdependency -- Scale-free property; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2020.107315
• Languages: English
• ISSNs: 0951-8320

Abstract

Abstract: Multimodal freight transport allows switching among different modes of transport to utilize transport facilities more efficiently. This paper proposes an approach on network modeling and robustness assessment for multimodal freight transport networks, where the nodes represent junctions, terminals and crossings, and the links represent pathways. The network model captures the features of interconnection and interdependency. Freight can switch between different modalities at interconnected terminals, while disruption of a single interdependent node (e.g., bridge, tunnel, railway crossing) affects multiple modalities. Considering disruptions of infrastructure elements and capacity degradation of pathways as perturbations, the network robustness is evaluated as the increment of the total travel time caused by these perturbations. We apply our robustness assessment model to the Dutch freight transport, taking into account three modalities: inland waterway, road and railway. The node criticality, defined as the impact of a node removal on the total travel time, resembles a power-law distribution, independent of different traffic assignments. This scale-free property implies a relatively robust state of the network against single random disruptions. Further, we show that the most critical nodes can be roughly identified by their topological properties. Our research helps to schedule the maintenance by assigning priority to the critical infrastructure. Highlights: The network model features interconnection and interdependency of multimodal transport. Scale-free robustness for element disruptions under different traffic assignments. Topological properties roughly indicate the critical infrastructure.