Electronic Theses and Dissertations

Jesse Simpson

Date

2020

Document Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Civil Engineering

Committee Chair

Sabyasachee Mishra

Committee Member

Mihalis Gkolias

Committee Member

Charles Camp

Committee Member

Mohammed Osman

Abstract

This dissertation presents and tests a methodology for predicting the adoption rate of Connected Autonomous Trucks (CATs) in transportation organizations using peer effects. There are a number of different factors that must be considered when developing innovation adoption models for organizations. This dissertation briefly describes each of the relevant variables and combines them into a discrete choice model for predicting the adoption rate of CATs by transportation organizations. The model incorporates new peer effect modeling techniques to simulate competition and the informal communication network. A stated-preference survey is conducted, and information from 400 freight transportation organizations is gathered. The survey focuses on two hypothetical CAT adoption scenarios; the first scenario loosely describes a level 3 autonomous vehicle, and the second scenario describes a level 4 autonomous vehicle which is introduced 10 years after the first generation of CATs are made available. By analyzing the responses to these scenarios, we are able to generate a prediction for how quickly freight transportation organizations will choose to test and adopt CATs. Smaller organizations were far more likely to reject CATs than larger organizations, and almost all of the responses agreed that the first generation of CATs are a high-risk investment. Despite this, roughly 30% of organizations claim that they plan to fully adopt and integrate CATs into their fleet as soon as they are made available and safe.

Comments

Data is provided by the student.

Library Comment

Dissertation or thesis originally submitted to ProQuest

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