MS in Civil Engineering (M.S.C.E.)
Degree Granting Department
Civil and Environmental Engineering
Abdul R. Pinjari, Ph.D.
Pei-Sung Lin, Ph.D.
Seckin Ozkul, Ph.D.
Probe Data, Map-matching, Route Generation, Route Choice, Route Variability
Over the past few decades, the value and weight of freight shipments have grown steadily in both developed and developing countries. A recent statistic in the U.S. reveals that weight of shipments increased from 18,879 to 19,662 million tons between 2007 and 2012 (1). It is also expected that this amount will increase to 28,520 million tons by 2040 (1). It is worth mentioning that 67 percent of shipments are shipped by truck mode in 2012. The monetary value of freight is expected to escalate even faster than weight. This value is estimated to rise from US$ 882 per ton in 2007 to US$ 1,377 per ton in 2040. As a result, freight transportation management and modeling has aroused the interest of both public sector and groups of firms to improve the efficiency of the business operations. Traffic assignment plays a central role in the current freight modeling, and freight route analysis is of fundamental importance in understanding the truck flows explicitly.
In the first part of this thesis, large streams of truck-GPS data from the American Transportation Research Institute (ATRI) are cleaned, processed, and analyzed using easy to implement and practical procedures to study the diversity of observed truck routes between a given origin-destination (OD) pair. This is because, for any given OD pair, the analyst could observe and compare the route choices of a large number of trips, as opposed to observing only one or a few trips. Doing so helps in quantifying the number of different routes taken by trucks between an OD pair and paves the way for a systematic analysis of the “diversity” in route choices between any OD pair. This thesis develops methods to measure the diversity of routes between a given OD pair and identifies unique routes used between the given OD pair. From a practical standpoint, such analysis of the diversity in observed route choices helps in improving the existing route choice set generation algorithms.
In the second part of the thesis, the methodologies developed in the first part are implemented in an FDOT sponsored project entitled “GPS Data for Truck-Route Choice Analysis of Port Everglades Petroleum Commodity Flows”. This project aims to use truck-GPS data from ATRI to derive petroleum tanker trucks’ travel path (or route) information, describing the routes that the tanker trucks take to travel from Port Everglades to their final delivery points.
Scholar Commons Citation
Kamali, Mohammadreza, "Development of Truck Route Choice Data Using Truck GPS" (2015). USF Tampa Graduate Theses and Dissertations.