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Impossibility of Transit in Atlanta: GPS-Enabled Revealed-Drive Preferences and Modeled Transit Alternatives for Commute Atlanta Participants

This thesis compared revealed-preference automobile morning work commute trip data from GPS-equipped instrumented vehicles of Commute Atlanta participants with transit commute alternatives identified in the regional planning model transit network. The Transit Capacity and Quality of Service Manual (TCQSM) travel time level of service (LOS) measure for transit was applied to these GPS automobile and modeled transit data. To quantify system-level transit availability, the TCQSM service coverage LOS was applied to the Atlanta region and Atlanta s transit service area LOS was calculated as C. Most of the commuters in this study would experience transit-auto travel time LOS of F. The analyses revealed that revealed automobile travel times were 45% shorter than the model-reported automobile travel time skims for the same origin and destination zones. Transit traces, calculated by manually tracing the trips from origin to destination via the most preferable transit mode, were about 24% longer than the minimum travel-demand-modeled transit skims. Only about 9% of commuters drove directly to work more than 95% of the time and only 6% of commuters left home within five minutes of their median departure time more than 95% of the time, indicating that the convenience and flexibility of the automobile is likely to be a significant element in these commute mode decisions. Commuters perceive the total transit trip time as between being 1.25 and 2.5 as long as the actual (modeled) time, and only about 25% of commuters could take transit without having to transfer. The calculated total cost of driving to work exceeded the cost of transit, but automobile operating costs alone did not exceed transit costs for about half the sample.

Identiferoai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/19788
Date15 November 2007
CreatorsZuehlke, Kai M.
PublisherGeorgia Institute of Technology
Source SetsGeorgia Tech Electronic Thesis and Dissertation Archive
Detected LanguageEnglish
TypeThesis

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