Time-dependent effects in freight trip generation models
Authors
Herazo Padilla, Nilson Sebastian
ORCID
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Other Contributors
HolguÃn-Veras, José
He, Xiaozheng (Sean)
Wang, Xiaokun (Cara)
He, Xiaozheng (Sean)
Wang, Xiaokun (Cara)
Issue Date
2017-08
Keywords
Transportation engineering
Degree
MS
Terms of Use
Attribution-NonCommercial-NoDerivs 3.0 United States
This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
Full Citation
Abstract
Freight trip generation models are a key input to transportation system planning studies, transportation infrastructure design and policy making processes since estimations from these models are commonly used to forecast the traffic impact of freight transportation. Therefore, accurate models for freight trip generation are vital to avoid negative impacts on the costs of transportation system improvement initiatives and prevent the implementation of ineffective policies with the consequent misuse of public funds. A common assumption in the case of passenger trip generation applications is that models are stable over the time and can be used for different periods of time. This is not necessarily the case for freight trip generation models since the number of trips either attracted or produced by a commercial establishment is an expression of a multiplicity of economic factors subject to variation over the time.
The results suggest that time-dependent effects are highly significant in freight trip generation models and ignoring such effects when using these models to forecast traffic demand could lead to serious under/overestimation errors that could cause planning processes, regulations and policies based on these models to be completely ineffective. The comparative analysis conducted reveal that models including time-dependent effects and revenue have a good fit to the data and produce better estimations than those reported in previous studies. The study also demonstrates that models including time-dependent effects and revenue are highly responsive to market disruptions such as those caused by a financial crisis. These types of models are also well-suited to be used with both explanatory and forecasting purposes.
This research conducts an extensive modeling process to determine and analyze time-dependent effects in freight trip generation models and their implications for planning and policy making purposes. The set of models estimated for freight trip generation includes fixed and continuous time-dependent factors with different functional forms. Models that include revenue are also analyzed along with their effects and interaction with time-dependent variables. A comparative analysis with previous models from the literature related to freight trip generation is also presented.
The results suggest that time-dependent effects are highly significant in freight trip generation models and ignoring such effects when using these models to forecast traffic demand could lead to serious under/overestimation errors that could cause planning processes, regulations and policies based on these models to be completely ineffective. The comparative analysis conducted reveal that models including time-dependent effects and revenue have a good fit to the data and produce better estimations than those reported in previous studies. The study also demonstrates that models including time-dependent effects and revenue are highly responsive to market disruptions such as those caused by a financial crisis. These types of models are also well-suited to be used with both explanatory and forecasting purposes.
This research conducts an extensive modeling process to determine and analyze time-dependent effects in freight trip generation models and their implications for planning and policy making purposes. The set of models estimated for freight trip generation includes fixed and continuous time-dependent factors with different functional forms. Models that include revenue are also analyzed along with their effects and interaction with time-dependent variables. A comparative analysis with previous models from the literature related to freight trip generation is also presented.
Description
August 2017
School of Engineering
School of Engineering
Department
Dept. of Civil and Environmental Engineering
Publisher
Rensselaer Polytechnic Institute, Troy, NY
Relationships
Rensselaer Theses and Dissertations Online Collection
Access
CC BY-NC-ND. Users may download and share copies with attribution in accordance with a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. No commercial use or derivatives are permitted without the explicit approval of the author.