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Master of Science in Civil Engineering (M.S.C.E.)
Year Degree Awarded
Month Degree Awarded
Risk Attitude, Traveler Behavior, User Equilbrium, Transportation, Route Choice
The traffic network is subject to random disruptions, such as incidents, bad weather, or other drivers’ random behavior. A traveler’s route choice behavior in such a network is thus affected by the probabilities of such disruptions, his/her attitude towards risk, and real-time information on revealed traffic conditions that could potentially reduce the level of uncertainty due to the disruptions. As the road network’s performance is de-termined collectively by all travelers’ choices, it is also affected by these factors. This thesis features the development of a multi-class user equilibrium model based on hetero-geneous risk attitude distributions and a user equilibrium model based on various disrup-tion probabilities and information penetration rates that can be used to perform sensitivity analyses for a traffic network. The method of successive average (MSA) is used to solve for the equilibrium conditions. Laboratory experimental data are used to calibrate the risk attitude model. A sample sensitivity analysis is performed to show the disruption and in-formation penetration effects on network performance. Initial calibrations show promis-ing results for route flow predictions in a congested network with respect to heterogene-ous attitude. With respect to disruption probability and information access, having too v high information penetration will not improve the network’s performance, while having a small disruption probability can improve traffic conditions in the network