01518566

Component

https://doi.org/10.3141/2430-15

http://scholar.google.com...hits&publication_year=2014

The development of a vehicle fleet composition and utilization model system that may be incorporated into a larger activity-based travel demand model is described. It is of interest and importance to model household vehicle fleet composition and utilization behavior because the energy and environmental impacts of personal travel are dependent not only on the number of vehicles but also on the mix of vehicles that a household owns and the extent to which different vehicles are used. A vehicle composition (fleet mix) and utilization model system was developed for integration into the activity-based travel demand model that was being developed for the greater Phoenix metropolitan area in Arizona. At the heart of the vehicle fleet mix model system is a multiple discrete continuous extreme value model capable of simulating vehicle ownership and use patterns of households. Vehicle choices are defined by a combination of vehicle body type and age category and the model system is capable of predicting vehicle composition and utilization patterns at the household level. The model system is described and results are presented of a validation and policy sensitivity analysis exercise demonstrating the efficacy of the model.

01543148

14-4236

English

0000-0002-0715-8121

pp 145–154

2014

Transportation Research Record: Journal of the Transportation Research Board

9780309295185

Print

Figures (1) ; References (14) ; Tables (7)

Activity choices; Fleet management; Households; Traffic forecasting; Travel demand; Travel patterns; Vehicle fleets; Vehicle mix

Phoenix Metropolitan Area

Highways; Planning and Forecasting; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Jan 27 2014 3:27PM

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• Impact of Proposed Land Use and Transportation Investments on Future Travel Patterns in California
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• Modeling Nonmotorized Travel Demand at Intersections in Calgary, Canada: Use of Traffic Counts and Geographic Information System Data
• Multidimensional Indicator Analysis for Transport Policy Evaluation
• Safety and Security in Discretionary Travel Decision Making: Focus on Active Travel Mode and Destination Choice
• Using Origin–Destination Centrality to Estimate Directional Bicycle Volumes
• Validation of Origin–Destination Data from Bluetooth Reidentification and Aerial Observation
• Wildfire Evacuation Scenario in Colorado: Comparison of Adapted Four-Step Metropolitan Planning Organization Modeling Results and Planning Process Findings with Actual Experience