Doctoral Dissertations

Abstract

Despite decades of research focused on reducing ground vehicle traffic congestion, urban traffic networks worldwide continue to experience traffic flows that lead to increased network travel times, largely resulting from the routing decisions of individual vehicles. To address this challenge, this work leverages a Stackelberg game framework to model the interaction between a vehicle agent and a routing authority as a leader–follower game, in which the routing authority proposes routing interventions to which the agent responds. This research contributes to existing traffic mitigation literature by exploring the role of trust in route decision-making and providing trust-aware algorithms that influence vehicle agents to select routes that mitigate network-wide congestion. The first contribution models human drivers as probabilistically compliant to routing interventions based on their trust in a routing authority. The interaction between a driver with selfish routing preferences and a network-optimizing routing authority is formulated as a Stackelberg game, where the routing authority knows the trust level of the driver. An algorithmic solution is developed to enable the routing authority to share personalized route recommendations, aiming to reduce network-wide travel time. The second contribution extends this model by developing a method to infer driver trust from routing decisions in a multi-stage interaction between the driver and the routing authority. The third contribution broadens vehicle decision-making by considering a spectrum of dynamic driving modes, including human driving, ADAS, teleoperation, and full autonomy. A trust-aware traded control algorithm is proposed to allow the routing authority to switch control to the most trustworthy driving mode at each segment of a route. Collectively, these contributions progressively extend existing decision-making models of vehicle operators to better capture human driver sentiment and emerging vehicle autonomy trends, leveraging observable behavior and behavioral biases to design routing interventions that reduce network-wide congestion.

Advisor(s)

Das, Sajal K.
Nadendla, V. Sriram Siddhardh

Committee Member(s)

Wunsch, Donald C.
Zawodniok, Maciej Jan, 1975-
Maity, Suman

Department(s)

Computer Science

Degree Name

Ph. D. in Computer Science

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2026

Journal article titles appearing in thesis/dissertation

Paper I, found on pages 30-75,was published in the Pervasive and Mobile Computing Journal. This journal submission is an extended version of a paper published in the proceedings of the IEEE International Conference on Smart Computing in Osaka, Japan, in June 2024, where it won the Best Paper Award.

Paper II, found on pages 76-103, has been published in the proceedings of the IEEE International Conference on Smart Computing in Cork, Ireland, in June 2025.

Paper III, found on pages 104-129, has been accepted for publication in the proceedings of the IEEE International Conference on Smart Computing in Messina, Italy, in 2026.

Pagination

xiii, 148 pages

Note about bibliography

Includes_bibliographical_references_(pages 137-146)

Rights

© 2026 Doris Evelyn Meredith Brown , All Rights Reserved

Document Type

Dissertation - Open Access

File Type

text

Language

English

Thesis Number

T 12587

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