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Page 71
Suggested Citation:"Chapter 7 - Gap Assessment." National Academies of Sciences, Engineering, and Medicine. 2018. The Relationship Between Transit Asset Condition and Service Quality. Washington, DC: The National Academies Press. doi: 10.17226/25085.
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Page 71
Page 72
Suggested Citation:"Chapter 7 - Gap Assessment." National Academies of Sciences, Engineering, and Medicine. 2018. The Relationship Between Transit Asset Condition and Service Quality. Washington, DC: The National Academies Press. doi: 10.17226/25085.
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Page 72

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71 Gap Assessment As part of the research, an assessment was made of gaps in available data and business prac- tices that might limit uses of the framework presented in Chapter 3. Table 7-1 summarizes the results of the assessment and identifies gaps and approaches for addressing them. The above analysis focuses on gaps related to prediction of EJT. Previous reviews (Spy Pond Partners et al. 2012, Robert et al. 2014b, McCollom and Berrang 2011, Spy Pond Partners et al. 2015) have identified other gaps related to transit asset management (e.g., gaps in EAM systems, maintenance records, and customer data) that may further complicate assessment of transit service quality. Further, a general gap exists that, outside of the guidance for NTD reporting, there is a lack of criteria or standards for reporting and assessing the quality of the data required for an EJT analysis. C H A P T E R 7

72 The Relationship Between Transit Asset Condition and Service Quality Gap Description Potential Approach for Addressing the Gap Standard adjustment factors for different types of passenger time Various studies are available establishing adjustment factors for types of activities, such as walking, standing, and waiting. However, no authoritative set of adjustment factors has been established in the U.S. Inclusion of recommended adjustment factors for types of passenger time in future revisions of Transit Capacity and Quality of Service Manual TCRP Report 165 and/or other service quality guidance. Adjusting for customer perceptions of vehicle conditions Relatively few studies are available that have yielded an adjustment factor or time equivalent to account for perceptions of vehicle condition. The available studies tend to combine condition with other factors. Additional stated preference and revealed preference surveys to better establish the effect of vehicle condition on customer perceptions. Data on scheduled versus actual headways and headway standard deviations Published performance data often include a summary of on-time performance, such as a percentage of trips within a given threshold of the schedule. Few data are publicly available documenting actual system headways and headway standard deviations. Independent research to archive publicly available AVL data and/or expansion of existing clearinghouses for compiling performance data. Improved measures for vehicle failure rates MDBF is widely used but problematic as a measure, given variation among transit agencies in maintenance practices and what defines a failure. Research supplementing MDBF with additional measures of the frequency of specific types of vehicle repairs. This would support defining separate models for the frequency of repairs (which may increase with age or mileage) and likelihood that a vehicle requiring repair will fail in service (which depends on details of the service and may vary greatly among transit agencies). Guideway failure rates Limited data are available documenting the frequency of failures of track, signals, and other guideway components. Development of standard conventions for what constitutes an asset failure, in addition to improved tracking of these failures. Impacts of cascading failures for fixed guideway systems Individual vehicle or guideway failures can create cascading delays. Parameters are provided to approximate the Additional analysis of available data, such as AVL data sets, to quantify the effects of a vehicle or guideway failure on other vehicles. effect in the EJT Calculator, but it may be difficult to populate these parameters. Standards for evaluating service quality The research proposes EJT as an integrated service quality metric, but there are no standards for establishing what constitutes a desired or acceptable EJT. Development of guidance for establishing target and acceptable levels for EJT or a comparable service quality measure for selected O-D pairs. Table 7-1. Gap assessment results.

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TRB's Transit Cooperative Research Program (TCRP) Research Report 198: The Relationship Between Transit Asset Condition and Service Quality documents the development of a quantitative method for characterizing service quality and demonstrates how this quantitative measure varies with changes in asset condition. It provides guidance on how asset condition and transit service quality relate in terms of investment prioritization.

Three Excel spreadsheets–a simplified Effective Journey Time (EJT) Calculator, a comprehensive EJT Calculator, and a worked example demonstrating the use of the comprehensive EJT Calculator—provide quantitative methods. Transit agencies may use this report and tools to better manage existing transit capital assets and make more efficient and effective investment decisions.

Disclaimer - This software is offered as is, without warranty or promise of support of any kind either expressed or implied. Under no circumstance will the National Academy of Sciences, Engineering, and Medicine or the Transportation Research Board (collectively "TRB") be liable for any loss or damage caused by the installation or operation of this product. TRB makes no representation or warranty of any kind, expressed or implied, in fact or in law, including without limitation, the warranty of merchantability or the warranty of fitness for a particular purpose, and shall not in any case be liable for any consequential or special damages.

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