Freight Travel Demand Modeling: Synthesis of Approaches and Development of a Framework

It is increasingly being recognized at all levels of decision making that freight transportation and economic development are inextricably linked. As a result, many urban entities and states are embarking upon comprehensive freight transportation planning efforts aimed at ensuring safe, efficient, and smooth movement of freight along multimodal and intermodal networks. Over the past few decades there has been considerable published research on (1) freight transportation factors, (2) freight travel demand modeling methods, (3) freight transportation planning issues, and (4) freight data needs, deficiencies, and collection methods. A synthesis of the body of knowledge in these four areas is provided with a view to developing a comprehensive statewide freight transportation planning framework. The proposed framework consists of two interrelated components that facilitate demand estimation and decision making in the freight transportation sector.

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Transportation Planning: Travel Demand Modeling Forecast: Model Conversion from TransCAD to Cube Voyager

Plan, Build, and Manage Transportation Infrastructure in China ◽

10.1061/40952(317)4 ◽

2008 ◽

Author(s):

Ka-Fai Wong

Keyword(s):

Transportation Planning ◽

Travel Demand ◽

Forecast Model ◽

Travel Demand Modeling ◽

Demand Modeling ◽

Model Conversion

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Investigation of Freight Agents’ Interaction Considering Partner Selection and Joint Decision Making

Sustainability ◽

10.3390/su12093636 ◽

2020 ◽

Vol 12 (9) ◽

pp. 3636

Author(s):

Dapeng Zhang ◽

Xiaokun (Cara) Wang

Keyword(s):

Decision Making ◽

Travel Demand ◽

Partner Selection ◽

Freight Transportation ◽

The Body ◽

Estimation Methods ◽

Mcmc Methods ◽

Demand Model ◽

Joint Decision ◽

Proposed Model

Freight transportation plays an increasingly important role in sustainable development. However, freight travel demand has not been understood comprehensively, due to its unique features: freight activities are the result of collaboration among freight agents. It distinguishes freight transportation from passenger transportation, in which travel decisions are made mostly by individuals. Specifically, two processes in the collaboration can be observed: partner selection and joint decision making. Using the supplier-customer collaboration as an example, partner selection is a process for suppliers and customers to evaluate their potential partners and select the best one. Joint decision making allows suppliers and customers to seek common interests and make compromises. As a traditional travel demand model cannot model the two processes effectively, this research develops an innovative econometric model, spatial matching model, to bridge the gap. The proposed model is specified based on freight agents’ behavioral, estimated by Bayesian MCMC methods, and demonstrated by numerical examples. The proposed model and estimation methods can recover the coefficient values in the econometric models, and establish the relationship between the influential factors and the observed matching behavior. The analysis improves the understanding of freight travel demand in a behavioral-consistent manner and enriches the body of freight demand modeling literature.

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