One of the major impediments to developing a larger body of knowledge in travel behavior than we currently have is the lack of sufficient data at very detailed levels. The lack of sufficient data is the result of the inherent complexity of gathering and subsequently analyzing observations of the phenomena of interest. This is particularly true for route choice, a topic on which scant link-by-link data appear to be available, especially at multi-day level. In fact, very little empirical work is based on real world observation. This dissertation studies the factors that influence morning commuters route choice and route switching based on objective real-world observations of travel behavior during multi-day period.
This dissertation tests the current route choice model assumption that travel time or travel distance is the only factor influencing drivers route choice decision. Investigation of the objective route choice factors confirms that minimizing travel time, although very important, is not the only factor that impacts route choice. Several other factors have been identified that impact commuters route choice. This dissertation examines the choice between using single or multiple morning commute routes. The results indicate the strong explanatory power of work schedule flexibility and trip-chaining on the choice of single or multiple commute routes compared to the commuters socio-demographic characteristics and commute route related attributes. This dissertation also presents an extensive effort in analyzing GPS-based travel behavior data and develops a methodology to subtract route choice information and trip-level travel information from the GPS-based vehicle activity data.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/7602 |
| Date | 30 November 2004 |
| Creators | Li, Hainan |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | 3716800 bytes, application/pdf |
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