An Optimization Research For Train Plan Of Urban Rail Transit With The Consideration Of Passengers’ Travel Efficiency

With the deepening of urbanization and the increasing of urban population, urban traffic congestion problems become more and more serious. Owing to its greater capacity, higher efficiency, lower energy consumption and better environmental protection, urban rail transit systems are particularly important to metropolises to overcome traffic congestion problems. And in recent years, a massive construction of urban rail transit can be found in cities of Mainland China with the support of local governments. However, operators in those cities always create a timetable based on point check (maximum load) data, which will hamper the improvement of service quality of urban rail transit.To improve the service quality of urban rail transit, this research will focus on the timetable design problem (TDP) of both urban rail line and urban rail network. Firstly, the crucial influence factors of TDP are summarized based on the review of related studies; and then an analysis framework is presented. With the achievements above, three optimization models are presented for TDP of urban rail transit system. Obviously, constraints of operation requirement, supply ability, socio-economic level, and so on will be considered in these models. Main contents and conclusions of the dissertation are shown as follows.(1) Influence factors of TDP are analyzed systematically from four aspects, namely urban development, passenger demand, operation requirement, and supply ability, based on the related literatures. And then, an analysis framework of TDP of urban rail transit is presented.(2) After analyzing the time-dependent characteristic of passenger demand, a scheduling model is proposed for an urban rail line. In this model, the constraints of station and train capacities, operation safety headway, first and last service, available fleet et al., are fully considered. And the objective of model is to find the departure schedule of trains at the start terminal to minimize the system cost, which includes passenger waiting cost and operating cost. Then, a two-stage simulation-based genetic algorithm is introduced to find the best solution. In the simulation processes, strict constraints of station and train capacities are considered. It assumes that all passengers access a station or broad a train based on a first-come-first-service principle. The whole travel process of a passenger can be described as, arriving at a station, queuing to enter a station, accessing the platform, waiting for trains at platform, boarding, alighting, and egressing the station. Numerical results show that, comparing with the optimal result of even-timetable, the optimal system costs are reduced by 10.03%,9.60%, and 8.04%when the time interval 8 equals to 5s,10s, and 30s respectively.(3) A bi-level TDP is proposed for a peak-hour urban rail line based on the analysis of feedback of timetable to passenger demand. This bi-level optimal model aims at determining the departure schedule of trains at start terminal to minimize the system cost, which includes passenger travel cost and operating cost. And the calculation method of peak-hour passenger travel cost is elaborated. Numerical results show that the proposed model can reflect the relationship between passengers’behavior and timetable. It also can keep a balance between passengers and operators.(4) Aimed at a typical unconnected urban rail network, calculation methods of passenger cost and operating cost for the urban rail network are presented based on the analysis of periodicity characteristics of unban rail network. Then an optimization model is proposed to minimize the system cost, which includes passenger travel cost and operating cost. This model aims to determine the headways of each line in the network and offset times between different lines under the constraints of operation safety headway, station and train capacities, operating subsidy, and so on. To solve the problem, a simulation-based genetic algorithm is introduced. Finally, a numerical example is given to demonstrate the effectiveness and superiority of the proposed model. Results show that model in this paper works well than models proposed in previous researches and service indicators obtained by our model, such as maximum load of trains and stations, are all in the range of security.