Doctor of Philosophy

dissertationAs the nation's traffic system becomes more congested for various periods of the day, more research in the area of intelligent transportation systems is needed. Traditional solutions of adding more highways and widening the existing system are not feasible anymore due to rapidly increasing demand and lack of room for expansion. The national interest is therefore focused on congestion mitigation methods that promote efficient use of existing infrastructure. Some of the key aspects of congestion management techniques include Intelligent Transportation Systems (ITS) elements. These ITS elements can play a role in drivers' interaction, route choice, and traffic controls. Combined Traffic Assignment and Control (CTAC) framework-based models can capture the ITS elements- based control-driver interaction in traffic systems. The CTAC method has been the topic of scientific research for the last three decades. Several solution algorithms, model formulations, and implementation efforts have been well documented. Although proven in research, the use of the combined traffic assignment and control modeling framework is rare in practice. Typically, the engineering practice tends to keep Traffic Assignment and Control Optimization processes separate. By doing so, the control-driver interaction in the traffic system is ignored. Previous research found that CTAC models could capture the control-driver interaction and the combined modeling framework should be used in practice

A Framework for Developing and Integrating Effective Routing Strategies Within the Emergency Management Decision-Support System, Research Report 11-12

This report describes the modeling, calibration, and validation of a VISSIM traffic-flow simulation of the San José, California, downtown network and examines various evacuation scenarios and first-responder routings to assess strategies that would be effective in the event of a no-notice disaster. The modeled network required a large amount of data on network geometry, signal timings, signal coordination schemes, and turning-movement volumes. Turning-movement counts at intersections were used to validate the network with the empirical formula-based measure known as the GEH statistic. Once the base network was tested and validated, various scenarios were modeled to estimate evacuation and emergency vehicle arrival times. Based on these scenarios, a variety of emergency plans for San José’s downtown traffic circulation were tested and validated. The model could be used to evaluate scenarios in other communities by entering their community-specific data

Analysis of road urban transport network capacity through a dynamic assignment model: validation of different measurement methods

Abstract Network capacity in a transportation system becomes an important measurement for transport planning and management because it addresses its capability to satisfy an efficient network traffic flow reducing the inefficiency of congestion phenomena. This work provides a discussion of road urban transport network capacity including existing definitions in literature and the validation of new measurement methods. The study explores some of the properties of network-wide traffic flow relationships in a large-scale complex urban street network using real-time simulated results obtained from a dynamic traffic assignment model, periodically updated by data from radar sensors through rolling horizon technics. The basic variables used in the methodology, such as network flows and speeds, are characterized using a network model calibrated in the urban area of Catania (Italy). For a comprehensive yet simple analysis, equations and graphs are utilized to resume the obtained results related to different days and several time intervals of the day. This procedure proved to be suitable to investigate the properties of network-level traffic flow relationships and concluding remarks include suggestions for further research in this highly promising area

A simple contagion process describes spreading of traffic jams in urban networks

The spread of traffic jams in urban networks has long been viewed as a complex spatio-temporal phenomenon that often requires computationally intensive microscopic models for analysis purposes. In this study, we present a framework to describe the dynamics of congestion propagation and dissipation of traffic in cities using a simple contagion process, inspired by those used to model infectious disease spread in a population. We introduce two novel macroscopic characteristics of network traffic, namely congestion propagation rate \b{eta} and congestion dissipation rate {\mu}. We describe the dynamics of congestion propagation and dissipation using these new parameters, \b{eta}, and {\mu}, embedded within a system of ordinary differential equations, analogous to the well-known Susceptible-Infected-Recovered (SIR) model. The proposed contagion-based dynamics are verified through an empirical multi-city analysis, and can be used to monitor, predict and control the fraction of congested links in the network over time.Comment: 10 pages, 8 figure