Date of Award

7-7-2020

Publication Type

Master Thesis

Degree Name

M.A.Sc.

Department

Civil and Environmental Engineering

First Advisor

Hanna Maoh

Rights

info:eu-repo/semantics/openAccess

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Abstract

In recent years, an increasing number of researchers and practitioners have shown an interest in model freight transportation activities. These activities have been growing at a significant rate due to globalization and the dependence on goods that are produced in offshore markets. Prior freight models were often aggregated, which made them less reliable for policy analysis. A remedy to overcome the limitations in aggregate model is to develop agent-based micro-simulation transportation models. These models are more comprehensive, thereby allowing them to calculate more accurate predictions. The current study utilizes data extracted from truck GPS records to model freight movements as the outcome of truck tours. A modeling framework is proposed for use in simulating the tours of individual trucks. The framework starts by predicting the number of tours per individual establishments. This is followed by micro-simulating each tour travel time, duration, and exact starting time. A stop generation model was used to predict the number of stops per tour and then the purpose of all intermediate stops within the tour. Next, the location of truck stops and the dwelling time at each stop are simulated. The focus of this research is to study the destination and duration of truck tour stops, and the analysis of the tours will make use of advanced statistical and geo-spatial modeling techniques. The results allow us to identify the significant factors that impact the movement of heavy trucks on the road network system. The geospatial and statistical results form the basis for developing a more comprehensive understanding of freight movement processes in Ontario. The models were incorporated in the proposed agent-based simulation model and were then used to predict the destination and duration of truck tour stops at the micro-level.

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