Urban Rail Transit Feeder-bus Routes Design Issues

The urban traffic congestion problem has become one of the key factors that restrict China's economic and social development. Construction of an integrated public transport system is an effective means to alleviate urban traffic congestion, which contains rail transit as the skeleton, and conventional public transit as the main body. The feeder problem of rail transit station and conventional public transit is an important part of the integrated public transportation. However, the coordination between rail transit and conventional public transit has not been fully considered during the continuous and rapid constructions of rail transit.. This leads to the competition between rail transit and conventional public transit, low efficiency of the transportation system, and a great delay on the progress of integrating public transport systems. Based on above background, the urban rail transit Feeder-bus route design problem has been comprehensively studied in this thesis.Firstly, this thesis made a comprehensive comparison on the technical characteristic, social economic efficiency, comfort and service scope of urban rail transit and conventional public transit, determined the function and orientation of the rail transit and conventional public transit, and analyzed the goals and principles, service scope, site selection and layout mode of Feeder-bus routes. Then, passenger travel time costs and transit vehicle operating costs of Feeder-bus system are extensively analyzed. Radiation and ring optimization model are proposed to formulate urban rail transit Feeder-bus route design problem. The proposed model considers bus line layout constraints, passenger flow conservation constraints, and vehicle capacity constraints, and aims to minimize the total cost of the Feeder-bus system by optimizing bus line layout and frequency.According to model characteristics of radiation and ring Feeder-bus routes, the artificial bee colony algorithm, genetic algorithm and hybrid particle swarm optimization are introduced to solve the proposed model. Several numerical examples showed that the proposed algorithms are able to solve the optimal layout and operation frequency of the Feeder-bus routes, which verify the feasibility and effectiveness of the model and algorithm. According to the contrast between the algorithms, we found that the artificial bee colony algorithm outperforms the genetic algorithm in terms of solution quality, stability and efficiency, which provides the experience for reference for solving related model.