2009Unpublished venueOpen access

Real-Time Socio-Economic Data for Travel Demand Modeling and Project Evaluation

Kevin Ford, Jon D. Fricker

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Abstract

Small and medium-sized communities often lack data that are complete, current, representative of the community, and appropriate for the travel demand models/software to be applied. To aid such communities, this research was conducted to meet the following objectives: (1) Identify and facilitate the communication of data that is updated more frequently than the Decennial Census for Indiana Travel Demand Models; (2) Allow the use of cross-classification techniques within trip generation for planning organizations that lack the time and resources to conduct travel demand/household surveys; (3) Evaluate the sensitivity of travel demand model outputs to varied parameters and inputs so as to help focus data collection and guide parameter selection; and (4) Apply risk management strategies to travel demand modeling so as to help planners program the most resourceefficient projects.

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Small and medium-sized communities often lack data that are complete, current, representative of the community, and appropriate for the travel demand models/software to be applied. To aid such communities, this research was conducted to meet the following objectives: (1) Identify and facilitate the communication of data that is updated more frequently than the Decennial Census for Indiana Travel Demand Models; (2) Allow the use of cross-classification techniques within trip generation for planning organizations that lack the time and resources to conduct travel demand/household surveys; (3) Evaluate the sensitivity of travel demand model outputs to varied parameters and inputs so as to help focus data collection and guide parameter selection; and (4) Apply risk management strategies to travel demand modeling so as to help planners program the most resourceefficient projects.

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Available abstract

Small and medium-sized communities often lack data that are complete, current, representative of the community, and appropriate for the travel demand models/software to be applied. To aid such communities, this research was conducted to meet the following objectives: (1) Identify and facilitate the communication of data that is updated more frequently than the Decennial Census for Indiana Travel Demand Models; (2) Allow the use of cross-classification techniques within trip generation for planning organizations that lack the time and resources to conduct travel demand/household surveys; (3) Evaluate the sensitivity of travel demand model outputs to varied parameters and inputs so as to help focus data collection and guide parameter selection; and (4) Apply risk management strategies to travel demand modeling so as to help planners program the most resourceefficient projects.

Key concepts: Travel time, Software, Computer science, Operations research, Transport engineering, Environmental economics, Data science, Economics

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