In Proof-of-Payment Transit Systems (POP-TSs), fare evasion is a crucial issue for Transit Agencies (TAs) and/or Public Transport Companies (PTCs) worldwide. The related research background is based on the standard ratio between evaders and inspected passengers, whereas no research quantified the risk of fare evasion in POP-TSs. The objective of this study is the introduction of a framework covering this gap: it integrates fare evasion factors, prediction models, a risk-based method and returns the risk value on (parts of) routes as a function of the frequency of fare evasion, the related severity and exposure terms. Next, routes are ranked according to the risk value and classified by a 5-level scale, to show the (parts of) routes with the highest risk of evasion. Results show the capability of this framework on about 20,000 real-world data records gathered by a mid-sized Italian bus company through fare inspection logs and passenger surveys. To conclude, this framework is a support tool for TAs/PTCs to improve fare compliance and can be incorporated into any transit managerial system.
Evaluating fare evasion risk in bus transit networks
Barabino B.Conceptualization
;Ventura R.
2023-01-01
Abstract
In Proof-of-Payment Transit Systems (POP-TSs), fare evasion is a crucial issue for Transit Agencies (TAs) and/or Public Transport Companies (PTCs) worldwide. The related research background is based on the standard ratio between evaders and inspected passengers, whereas no research quantified the risk of fare evasion in POP-TSs. The objective of this study is the introduction of a framework covering this gap: it integrates fare evasion factors, prediction models, a risk-based method and returns the risk value on (parts of) routes as a function of the frequency of fare evasion, the related severity and exposure terms. Next, routes are ranked according to the risk value and classified by a 5-level scale, to show the (parts of) routes with the highest risk of evasion. Results show the capability of this framework on about 20,000 real-world data records gathered by a mid-sized Italian bus company through fare inspection logs and passenger surveys. To conclude, this framework is a support tool for TAs/PTCs to improve fare compliance and can be incorporated into any transit managerial system.File | Dimensione | Formato | |
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