Author

Seungkyu Ryu

Date of Award:

2015

Document Type:

Dissertation

Degree Name:

Doctor of Philosophy (PhD)

Department:

Civil and Environmental Engineering

Advisor/Chair:

Anthony Chen

Abstract

The Path Flow Estimator (PEE) concept was originally developed to estimate path flows (hence origin-destination flows) and link flows for a whole road network (given some counts at selected roads). It is now further developed as an alternative for modeling different transportation planning applications: (1) a bicycle network analysis tool for non-motorized transportation planning, (2) a multi-class traffic assignment model for freight planning, and (3) a simplified travel demand forecasting framework for small community planning.

The first application of the redeveloped PFE is to develop a two-stage bicycle traffic assignment model for estimating/predicting bicycle volumes on a transportation network. The first stage considers key criteria (e.g., distance related attributes, safety related attributes, air quality related attributes etc.) to generate a set of non-dominated (or efficient) paths, while the second stage adopts several traffic assignment methods to determine the flow allocations to the network. This two-stage approach can be used as a stand-alone bicycle traffic assignment to the transportation network given a bicycle origin-destination (O-D) matrix. The second application aims to enhance the realism of traffic assignment models for freight planning by incorporating different modeling considerations into the multi-class traffic assignment problem. These modeling considerations involve developing both model formulation and customized solution algorithm, which in turn involve asymmetric interactions among different vehicle types (i.e., cars versus trucks), a path-size logit (PSL) model (for accounting random perceptions of network conditions with explicit consideration of route overlapping), and various traffic restrictions imposed either individually or together to multiple vehicle types in a transportation network. In the third application, a simplified planning framework is developed to perform planning applications in small communities where limited planning resources hinder the development and application of a full four-step model. Two versions (i.e., base year and future year) of the PFE are proposed to address the specific transportation planning issues and needs of small communities.

These new PFE developments for planning applications are tested with different realistic transportation networks. The results suggest that the new PFE applications proposed in this dissertation provide an alternative to the traditional four-step travel demand forecasting model that can be used as a stand-alone application with better modeling capability and fewer resources.

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