Transportation System Vulnerability Assessment considering Environmental Impact

• Published in: Journal of advanced transportation Vol. 2022; pp. 1 - 12
• Main Authors: Lin, Juanjuan, Lin, Wangbing
• Format: Journal Article
• Language: English
• Published: London Hindawi 26.05.2022; Hindawi Limited; Wiley
• Subjects: Critical components; Degradation; Earthquakes; Efficiency; Emissions; Environmental impact; Infrastructure; Infrastructure (Economics); Literature reviews; Long-term planning; Network topologies; Road transportation; Short-term planning; Topology; Traffic assignment; Traffic congestion; Transportation; Transportation authorities; Transportation industry; Transportation networks; Transportation systems; Travel; Travel time; China; Henan China; United States > US; New York City New York
• ISSN: 0197-6729; 2042-3195
• DOI: 10.1155/2022/8711894

Transportation system has a close bearing on the prosperity of society. However, transportation infrastructures are highly vulnerable to extreme events. Therefore, identifying the most critical component of the transportation system is among the first priorities of transportation network planners and managers. This paper proposes a novel framework to identify the most vulnerable component for a road transportation system. A key characteristic of vulnerability assessment is the travelers’ response to the changes in the transportation network topology and capacity after an extreme event. Hence, the problem is formulated as a nonlinear programme with equilibrium constraints, considering travelers’ route choice behavior. In the methodology, two types of vulnerability measures are developed to assess the vulnerability of road transportation system, namely, system travel time-based vulnerability (STTV) and system emissions-based vulnerability (SEV). The former is developed on the basis of short-term planning, while the latter is put forward on the basis of long-term planning. With these vulnerability measures, the proposed framework is then demonstrated using an extended Nguyen-Dupuis network under different demand levels and different capacity degradation levels, taking into account two modes: bus and car. The results indicate that different vulnerability measures can identify similar vulnerable components. Moreover, it is shown that the SEV can find more critical components than the STTV regardless of capacity degradation or demand growth. Our research helps to create a recovery plan by assigning priority to the critical transportation infrastructures.