| With the growth of population and urbanization, traffic congestion has become one of the most serious problems in most cities all over the world. It really affects the healthy development of a city and social economy. To develop the effective measure alleviating traffic congestion, it is needed to perfectly understand the behavior of travelers'travel choice. This dissertation studies four traffic conditions:traffic network with Advanced Traveler Information System (ATIS), multi-modal traffic network, the urban railway network, and the stochastic traffic network. The corresponding day-to-day traffic assignment model would be presented, and some traffic management measures are developed based on the analysis of travel choice in these traffic coditions. The specific contents of the dissertation are as follows:(1) The travel information of ATIS is classfied into two classes:accurate travel information and inaccurate travel information. Two day-to-day dynamic assignment models are respectively developed to study the travel choice of day-to-day and the stability of traffic system for the both cases. Based on the numerical results, it is found that the market penetration of ATIS, traffic demand, the perceived error all have effect on the stability of traffic system in both cases of the accuracy of travel information.(2) A traffic management measure is presented by combining the route guidance of ATIS and the continue network design (CNDP). With the measure, the travelers are recommended to choose the shortest path with user constraints. The problem is described by a bi-level program, and the feasible domain of its lower level is determined by the deterministic variable of upper level. The Simulated Annealing algorithm is improved to solve the bi-level problem. And the path-based traffic algorithm is developed to calculate the traffic assignment problem under the route guidance. Compared to the present results of CNDP, the measure presented in this dissertation can better alleviate the traffic congestion.(3) A bounded rationality based day-to-day urban railway dynamic assignment model is developed to study the day-to-day evolution of urban railway passenger flow. The passengers'bounded rationality is described as follows:If the difference between their expect pericevied travel cost and their expericed travel cost is more than the tolerance of passengers on a day, they would reconsider their travel choice in the next day; otherwise, they would use the same route in the next day. The travel cost in the model considers the cost casued by the congestion in carriage of urban railway. It is founded that the parameter of travelers' tolerance and traffic demand can obviously affect the convergency of the evolution of urban railway system. The travel cost has less effect on the system's convergnecy, and it has influence on the total travel cost significantly.(4) Based on a day-to-day traffic dynamic assignment model, the stability of bi-modal (car and bus) traffic system is studied both in mixed traffic conditions and traffic network with dedicated bus lane. Meanwhile, the travelers' transferring behavior is considered in the study. It is found that, both considering and without transferring behavior, traffic system with dedicated bus lane can maintain stable with more traffic demand than that in mixed traffic conditions.(5) In stochastic traffic network, a Markovian assignment model with stochastic traffic demand is presented. The traffic demand is grouped into two parts:commuters or regular travelers with fixed traffic demand and irregular travelers with bounded discrete random demand. With some wild conditions, it is proved that our Markovian assignment model is ergodic and has unique stable distribution. An algorithm is also developed to describe the Markovian model. Based on a simple tested example, it is found that the length of commuters' memory has less effect on the stable distribution, but the traffic demand and the commuters' perceived error has remarkable influence on the stable distribution. |
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