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Modeling Travel Behavior with the Advent of Electric and Automated Vehicle Technologies

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posted on 01.08.2019, 00:00 authored by Fatemeh Nazari
Motivated by the transformative roles of shared, autonomous, and electric vehicles in future urban mobility and human life, this dissertation investigates humans’ adoption behavior of these technologies and the determinants thereof. Considering privately-owned autonomous vehicle (AV) and multiple configurations of shared-use AVs, the first part of this dissertation aims at jointly modeling the public interest in AVs based on trip purpose with explicit treatment of the possible correlations across the AV types. In doing so, this research explains decision-making process of humans by observable socio-demographic, built-environment, and travel pattern factors, as well as unobservable (latent) subjective attitudes toward technology and lifestyle preferences. Turning focus to the potentially significant impact of consumers’ safety concern about the AV technology on AV adoption, the first part of this research also presents a methodological contribution to the travel behavior literature by exploring the causality between the travelers’ safety concern and their AV adoption behavior. The second part of this research makes an attempt to more realistically model public adoption of electric vehicles (EVs), which is the most recent and publicly available development in vehicle fuel technology. By conducting a first-of-its-kind retrospective vehicle survey at national-level, the proposed model investigates public EV adoption considering the dynamics of decisions over the past decade as well as the latent subjective attitudes, perceptions, and lifestyle preferences.

History

Advisor

Mohammadian, Abolfazl

Chair

Mohammadian, Abolfazl

Department

Civil and Materials Engineering

Degree Grantor

University of Illinois at Chicago

Degree Level

Doctoral

Degree name

PhD, Doctor of Philosophy

Committee Member

Lin, Jie Zou, Bo Kawamura, Kazuya Auld, Joshua

Submitted date

August 2019

Thesis type

application/pdf

Language

en

Issue date

30/07/2019

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