Transit Service Reliability Under The Framework Of Intelligent Technologies

Giving priority to the development of urban public transit is the main way to solve urban traffic jam, city pollution and maintain the sustainable development of the urban area. However, whether the urban public transit can take this role depends on not only the policy and planning issues but also the attraction of the transit system itself. As a major method to enhance the attraction of urban transit, how to improve transit service reliability is catching world wide concern. Nowadays, the widespread application of the intelligent transit technologies characterized by automatic vehicle location (AVL) and automatic passenger counting (APC) as the core technologies provides a good key to improve urban transit service reliability. Therefore, it is of both extremely theoretical and practical significance to study the transit service reliability issues under the frame of intelligent transit technologies such as AVL and APC.Based on a comprehensive literature review and a wide survey of some transit agencies in major metropolitan areas of North America about their practices in terms of using intelligent transit technologies such as AVL/APC to improve transit service reliability, this dissertation gives a summary and extraction of the basic theory framework of the research of transit service reliability. It establishes a framework of evaluating and analyzing transit service reliability based on archived AVL data. The route 20 of Chicago Transit Authority (CTA) in America is set as a case study of its service reliability. Data mining and statistics are used to analyze the pattern of service gap and the conditions which tend to lead to service gaps. The results show that the gap propagation exists in several segments and stops on route 20, but there are few typical patterns of gap headways. An early warning system to identify conditions that tend to lead to large gaps and a real-time bus running navigation strategy can be used to prevent these gaps.Considering the fluctuation of passenger demand and the stochastic nature of vehicle running time and their interactive dynamic relationship, as well as the vehicle capacity, the bus route service process under the stochastic situation is analyzed in detail. Based on the availability of AVL/APC data, an adaptable and multipurpose micro simulation model of a fixed route bus service is established using object-oriented simulation modeling method characterized by Object-Oriented Database (OODB) and Discrete Event System (DEVS).Considering the unreliability propagation of the transit service, a bus running navigation strategy is developed to prevent bus service unreliability based on real-time information. Building the real-time dynamic AVL/APC information into the micro simulation model of the bus route service, a bus route service unreliability prevention model is developed integrated with the real-time bus running navigation strategy. Using different scenarios of different route segment running time fluctuation and permitted deviation of the headway, the real-time bus running navigation strategy is tested and evaluated in the micro bus route service simulation model. The simulation result shows that, the real-time bus running navigation strategy has good performance under the situation of good control of the route segment running time.Considering the stochastic conditions of the bus route service, the effects of vehicle overtaking and no-overtaking on service reliability in case of no real-time bus operation control are comparatively tested and analyzed in the micro bus route service simulation model. The simulation results show that, given the example bus route parameters, downstream the route, neither bus overtaking nor bus no-overtaking with any bus operation control could stop the service reliability from declining; but bus no-overtaking could keep better headway adherence than bus overtaking does at the stops in the middle and downstream of the route, which leads to fewer average passenger waiting times at these stops.Finally, considering the passenger demand fluctuation and the vehicle running time randomness, as well as the relationship between the transit service frequency and the transit service reliability, a model for determining optimal bus route service frequency is developed. In this model, the expectation of passengers waiting for buses and the efficiency of running vehicles are aimed to achieve combined optimization. Monte-Carlo method is used to simulate the service process of a high frequency bus route and the optimal service frequency of this example route is calculated given the route parameters. The numerical example shows that this model can be used to determine the departure frequency of a bus route with high frequency service.