An approach for accessibility assessment and vulnerability analysis of national multimodal transport systems

Abstract

A series of ambitious accessibility‐oriented policies have been launched in the world, which center around improving accessibility via the national multimodal transport systems including road, airline, and railway. The national multimodal transport accessibility assessment is one of the “basic” analyses for the design and implementation of these policies, whereas existing national‐scale accessibility studies either focus on single‐mode or two‐mode transport or ignore the schedule‐dependent nature of railway and airline. This article models the integrated road, railway, airline, and walking transport as a four‐layer network with the consideration of their interdependencies. An algorithm is then developed to accurately assess the travel time‐based accessibility on the four‐layer network with the consideration of the daily schedule of trains and flights. The proposed approach is applied to map accessibility to 363 cities in mainland China and analyze the optimal travel modes. In addition, this article investigates the travel time‐based vulnerability of the national multimodal transport system in mainland China under the extreme storm recently occurred in Zhengzhou (July 2021). The findings in this work provide insightful suggestions for transport planners to design the national multimodal transport systems and for stakeholders to schedule travels.

Rethinking Global Supply Chain Management in a Changing Environment to Develop an Integrated Freight Transportation System in Bangladesh

“…In terms of designing the multi-modal transport system, the factors affecting the transport system should be considered [38]. Research has been conducted on the four-way multi-modal plan through bus, train, air, and walking freight transportation where in many countries they use one or two modes of transportation while taking cargo inland [41]. However, vulnerabilities like storms can affect this kind of system.…”

Study on Road Network Vulnerability Considering the Risk of Landslide Geological Disasters in China’s Tibet

“…Based on the general requirements of soil Erosion Classification Standard SL190-96 of the People's Republic of China, the degree of soil erosion in the study area was divided into five grades: slight, mild, moderate, intense, and violent. According to experimental requirements, of the 2521 geological disaster points in Tibet in recent years, 70% were randomly extracted as training sample points [37], and the remaining 30% were used to test and verify model accuracy.…”

“…There is no unified definition of road network vulnerability, owing to a lack of clear measures. Although the global attack-defense model and map of landslide sensitivity, analysis of the road transportation network vulnerability, travel mode, and travel time affect the capacity and emissions [36,37], capacity-weighted spectrum analysis is used to identify potential key links, cloud model-based urban road network traffic system congestion status, and many road vulnerability and risk assessment studies [14,20,21,38,39]. However, vulnerability analysis application in road disasters research is still in the exploration and development stages, and its theory and methods require further improvement.…”

“…• ) (0-8),(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18),(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29),(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41), Topographic relief (m) (0-14),(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29),(29)…”

“…Primary VariableEnvironmental Evaluation Factors Sources/Quantization Level Topography Slope (°) (0-8),(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18),(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29),(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41), (41-87) Topographic relief (m) [0-14), (14-29), (29-48), (48-76), (76-1101) Soil-vegetation conditions Soil erosion intensity Slight, mild, moderate, intense, violent NDVI (0-0.07), (0.07-0.19), (0.19-0.36), (0.36-0.59), (0.59-1) Hydrology Annual mean precipitation (mm) (103-307), (307-414), (414-558), (558-702), (702-1292) Distance from river system (m) (0-2683), (2683-5161), (5161-7892), (7892-12369), (12369-32160) Distance from glacier snow (m) (0-22,847), (22,847-50,636), (50,636-84,646), (84,646-133,843), (133,843-254,081)…”