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Accommodating Exogenous Variable and Decision Rule Heterogeneity in Discrete Choice Models: Application to Bicyclist Route Choice
Title
Accommodating Exogenous Variable and Decision Rule Heterogeneity in Discrete Choice Models: Application to Bicyclist Route Choice.
Creator
Dey, Bibhas, Eluru, Naveen, Abdel-Aty, Mohamed, Anowar, Sabreena, University of Central Florida
Abstract / Description
The thesis contributes to our understanding of incorporating heterogeneity in discrete choice models with respect to exogenous variables and decision rules. Specifically, we evaluate latent segmentation based mixed models that allow for segmenting population based on decision rules while also incorporating unobserved heterogeneity within the segment level decision rule models. In our analysis, we choose to consider the random utility framework along with random regret minimization approach....
Show moreThe thesis contributes to our understanding of incorporating heterogeneity in discrete choice models with respect to exogenous variables and decision rules. Specifically, we evaluate latent segmentation based mixed models that allow for segmenting population based on decision rules while also incorporating unobserved heterogeneity within the segment level decision rule models. In our analysis, we choose to consider the random utility framework along with random regret minimization approach. Further, instead of assuming the number of segments (as 2), we conduct an exhaustive exploration with multiple segments across the two decision rules. Within each segment we also allow for unobserved heterogeneity. The model estimation is conducted using a stated preference data from 695 commuter cyclists compiled through a web-based survey. The probabilistic allocation of respondents to different segments indicates that female commuter cyclists are more utility oriented, however the majority of the commuter cyclist's choice pattern is consistent with regret minimization mechanism. Overall, cyclists' route choice decisions are influenced by roadway attributes, cycling infrastructure availability, pollution exposure, and travel time. The analysis approach also allows us to investigate time based trade-offs across cyclists of different classes. Interestingly, we observed that the trade-off values in regret and utility based segments for roadway attributes are similar in magnitude; but the values differ greatly for cycling infrastructure and exposure attributes, particularly for maximum exposure levels.
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Date Issued
2018
Identifier
CFE0007398, ucf:52059
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007398
Fusing Freight Analysis Framework and Transearch Data: An Econometric Data Fusion Approach
Title
Fusing Freight Analysis Framework and Transearch Data: An Econometric Data Fusion Approach.
Creator
Momtaz, Salah Uddin, Eluru, Naveen, Abdel-Aty, Mohamed, Anowar, Sabreena, Zheng, Qipeng, University of Central Florida
Abstract / Description
A major hurdle in freight demand modeling has always been the lack of adequate data on freight movements for different industry sectors for planning applications. Freight Analysis Framework (FAF), and Transearch (TS) databases contain annualized commodity flow data. The primary motivation for our study is the development of a fused database from FAF and TS to realize transportation network flows at a fine spatial resolution (county-level) while accommodating for production and consumption...
Show moreA major hurdle in freight demand modeling has always been the lack of adequate data on freight movements for different industry sectors for planning applications. Freight Analysis Framework (FAF), and Transearch (TS) databases contain annualized commodity flow data. The primary motivation for our study is the development of a fused database from FAF and TS to realize transportation network flows at a fine spatial resolution (county-level) while accommodating for production and consumption behavioral trends (provided by TS). Towards this end, we formulate and estimate a joint econometric model framework grounded in maximum likelihood approach to estimate county-level commodity flows. The algorithm is implemented for the commodity flow information from 2012 FAF and 2011 TS databases to generate transportation network flows for 67 counties in Florida. The data fusion process considers several exogenous variables including origin-destination indicator variables, socio-demographic and socio-economic indicators, and transportation infrastructure indicators. Subsequently, the algorithm is implemented to develop freight flows for the Florida region considering inflows and outflows across the US and neighboring countries. The base year models developed are employed to predict future year data for years 2015 through 2040 in 5-year increments at the same spatial level. Furthermore, we disaggregate the county level flows obtained from algorithm to a finer resolution - statewide transportation analysis zone (SWTAZ) defined by the FDOT. The disaggregation process allocates truck-based commodity flows from a 79-zone system to an 8835-zone system. A two-stage factor multiplication method is proposed to disaggregate the county flow to SWTAZ flow. The factors are estimated both at the origin and destination level using a random utility factional split model approach. Eventually, we conducted a sensitivity analysis of the parameterization by evaluating the model structure for different numbers of intermediate stops in a route and/or the number of available routes for the origin-destinations.
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Date Issued
2018
Identifier
CFE0007763, ucf:52384
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007763
Understanding How, Where and How much Freight Flows Using 2012 Commodity Flow Survey Data
Title
Understanding How, Where and How much Freight Flows Using 2012 Commodity Flow Survey Data.
Creator
Keya, Nowreen, Eluru, Naveen, Abdel-Aty, Mohamed, Anowar, Sabreena, Uddin, Nizam, University of Central Florida
Abstract / Description
In recent years, with increased economic globalization, growing e-commerce and internet based shopping, freight movement patterns are undergoing a transformative change. The shipment size distribution is moving towards a higher share of smaller size shipments affecting transportation mode and vehicle type requirements. In addition, freight transportation mode is closely affected by the destination location (and its attributes). In our dissertation, we contribute to freight research by...
Show moreIn recent years, with increased economic globalization, growing e-commerce and internet based shopping, freight movement patterns are undergoing a transformative change. The shipment size distribution is moving towards a higher share of smaller size shipments affecting transportation mode and vehicle type requirements. In addition, freight transportation mode is closely affected by the destination location (and its attributes). In our dissertation, we contribute to freight research by developing a comprehensive framework to examine the how, where and how much freight flows in US. Specifically, we study the following dimensions of freight flow: (1) transportation mode, (2) mode and shipment weight choice and (3) mode and destination choice. For analyzing mode choice, an advanced discrete freight mode choice model- a hybrid utility-regret based model system has been estimated while accommodating for shipper level unobserved heterogeneity. To demonstrate the applicability of the proposed model system, detailed policy analyses examining the implementation of vehicle fleet automation and rerouting of freight movements away from a region were considered. While shipment weight could be considered as an explanatory variable in modeling mode choice (or vice-versa), it is more likely that the decision of mode and shipment choice is a simultaneous process. This joint decision is investigated both simultaneously employing a closed form copula structure and sequentially employing latent segmentation based sequence model. For destination choice, we investigated the connection between shipping mode and destination choice of shipment in a latent segmentation based sequential form. The analysis for the dissertation is conducted using 2012 Commodity Flow Survey (CFS) data.
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Date Issued
2018
Identifier
CFE0007574, ucf:52569
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007574