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Identification and quantification of link vulnerability in multi-level public transport networks: a passenger perspective
Identification and quantification of link vulnerability in multi-level public transport networks: a passenger perspective
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Identification and quantification of link vulnerability in multi-level public transport networks: a passenger perspective
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Identification and quantification of link vulnerability in multi-level public transport networks: a passenger perspective
Identification and quantification of link vulnerability in multi-level public transport networks: a passenger perspective

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Identification and quantification of link vulnerability in multi-level public transport networks: a passenger perspective
Identification and quantification of link vulnerability in multi-level public transport networks: a passenger perspective
Journal Article

Identification and quantification of link vulnerability in multi-level public transport networks: a passenger perspective

2018
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Overview
Robust public transport networks are important, since disruptions decrease the public transport accessibility of areas. Despite this importance, the full passenger impacts of public transport network vulnerability have not yet been considered in science and practice. We have developed a methodology to identify the most vulnerable links in the total, multi-level public transport network and to quantify the societal costs of link vulnerability for these identified links. Contrary to traditional single-level network approaches, we consider the integrated, total multi-level PT network in the identification and quantification of link vulnerability, including PT services on other network levels which remain available once a disturbance occurs. We also incorporate both exposure to large, non-recurrent disturbances and the impacts of these disturbances explicitly when identifying and quantifying link vulnerability. This results in complete and realistic insights into the negative accessibility impacts of disturbances. Our methodology is applied to a case study in the Netherlands, using a dataset containing 2.5 years of disturbance information. Our results show that especially crowded links of the light rail/metro network are vulnerable, due to the combination of relatively high disruption exposure and relatively high passenger flows. The proposed methodology allows quantification of robustness benefits of measures, in addition to the costs of these measures. Showing the value of robustness, our work can support and rationalize the decision-making process of public transport operators and authorities regarding the implementation of robustness measures.