Transit Vehicle Performance Analysis for Service Continuity/Termination: A Data Envelopment Analysis Approach

Document Type

Journal Article

Publication Date

2018

Subject Area

place - north america, mode - bus, mode - paratransit, infrastructure - maintainance, infrastructure - vehicle, infrastructure - fleet management, economics - operating costs, economics - revenue, planning - service improvement, planning - service quality, operations - reliability, operations - performance

Keywords

Public transit agencies, Transit performance analysis, data envelopment analysis (DEA)

Abstract

Public transit agencies aim to improve services while reducing operating costs. Transit performance analysis, as the main approach used to assess operating cost and revenue, has received much attention in recent decades. Most of such studies focus on macro-level performance analysis by comparing across transit agencies or within a transit agency across different parts of its operation. This macro-level analysis assumes that bus drivers and vehicles have identical performance in terms of production and resource consumption, yet they can vary significantly and the variations directly influence service reliability and operational efficiency. As a result, micro-level vehicle performance analysis is needed for operation optimization. This paper introduces an innovative and effective use of the data envelopment analysis (DEA) approach to estimate, project, and compare the operational efficiency of each transit vehicle. Using the paratransit fleet of Utah Transit Authority (UTA) as a case study, the study demonstrates the varying cost structures and operational efficiencies over time associated with different vehicle types. It shows that such variations and time series analysis can be used to guide prioritization of vehicle procurement and service continuity/termination, which further leads to significant cost savings and improvement in reliability of service. The proposed approach is replicable for any transit fleet with available maintenance and operation data. The proposed method provides transit agencies with data-driven analytics to facilitate the decision-making process.

Rights

Permission to publish the abstract has been given by SAGE, copyright remains with them.

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