Determinants of Bus Dwell Time
Kenneth Dueker, Thomas J. Kimpel, James G. Strathman, Steve Callas
Abstract
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Kenneth Dueker, Thomas J. Kimpel, James G. Strathman, Steve Callas
Abstract
Open-access reader
Bus dwell time data collection typically involves labor-intensive ride checks. This paper reports an analysis of bus dwell times that use archived automatic vehicle location (AVL)/automatic passenger counter (APC) data reported at the level of individual bus stops. The archived data provide a large number of observations that serve to better understand the determinants of dwells, including analysis of rare events, such as lift operations. The analysis of bus dwell times at bus stops is applicable to TriMet, the transit provider for the Portland metropolitan area, and transit agencies in general. The determinants of dwell time include passenger activity, lift operations, and other effects, such as low floor bus, time of day, and route type.
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Bus dwell time data collection typically involves labor-intensive ride checks. This paper reports an analysis of bus dwell times that use archived automatic vehicle location (AVL)/automatic passenger counter (APC) data reported at the level of individual bus stops. The archived data provide a large number of observations that serve to better understand the determinants of dwells, including analysis of rare events, such as lift operations. The analysis of bus dwell times at bus stops is applicable to TriMet, the transit provider for the Portland metropolitan area, and transit agencies in general. The determinants of dwell time include passenger activity, lift operations, and other effects, such as low floor bus, time of day, and route type.
Key concepts: Dwell time, Lift (data mining), Metropolitan area, Transit (satellite), Computer science, Transport engineering, Real-time computing, Arrival time