Date of Completion

5-6-2014

Embargo Period

5-7-2014

Keywords

Surface Transportation Networks, Small Worlds, Scale Free Networks, Betweeness Centrality, Clustering Co-efficient, Node Degree, User Equilibrium, Network Topology, Resilience, Complex Networks, Graph Theory, Biomimicry, Slime Mold

Major Advisor

Nicholas E. Lownes

Associate Advisor

John Ivan

Associate Advisor

Norman W. Garrick

Associate Advisor

Jeffrey Osleeb

Field of Study

Civil Engineering

Degree

Doctor of Philosophy

Open Access

Campus Access

Abstract

This dissertation is composed of three journal styled academic papers, which presents research on characterizing surface transportation network structure and resilience. The papers leverage tools in network science, biomimicry, and complex networks to investigate structure and resilience in surface transportation networks. The analysis was conducted using examples of existing road and rail transportation networks, and a feeding network of Physarum Polycephalum (slime mold).

The first study investigated the networks’ structure to determine if they exhibited scale free and small world characteristics. The hypothesis was that a network’s structure endowed it with certain characteristics that made it more efficient and robust in its performance. The second study evaluated resilience in surface transportation networks from a topological structure perspective. The networks were subjected to link based disruptions that deactivated them from the network using two strategies; a targeted and a random strategy.

The last study evaluated resilience of surface transportation networks to random disruptions using a user equilibrium framework. Using real life demand data, the networks were loaded with vehicle trip data and randomly disrupted. The networks were evaluated based on the deterioration in total system travel time with random link disruption. It was observed that the biological slime mold network was able to provide a higher level of resilience to degradation in total system travel time in response to disruption, because it contained redundant and alternative link connections between its nodes. It was established that the availability of alternative links to provide redundant capacity in the network, minimized impacts of disruptions.

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