| As the transportation and environment in many cities deteriorate,it has been widely recognized that developing good public transportation system to meet the travel demand may be the only solution.Bus Rapid Transit Planning(BRT)has the advantages of the traditional public transportation and subway.It is not only comfortable,fast and efficient,but also relatively cheap which can be put in use after a short construction period to produce quick effect.So it has been implemented in lots of cities.The research on BRT network planning and optimization will be critical to improve the service,to avoid unreasonable investment,to attract more passengers and to realize the sustainable development of public transport.This thesis presents the mathematical models for BRT network planning and optimization.The objective functions include maximization of covered population,maximization of served trips and the multiple-objective function to pursue the highest cost benefit and the optimal transfer rate.The constraint set contains geometrical constraint,distance constraint,expense constraint,bidirectional constraint and non-linear coefficient constraint,etc.The non-linear coefficient,although an important index to the bus route quality,has been widely ignored in previous research.The shortest path algorithm is applied to calculate the distances between candidate stations and a construction heuristic algorithm is developed to solve the mathematical models.A case study is conducted using the network data from the City of Luoyang.The road network information and trip investigation are put into the model and algorithm.According to the models feasibility,models are made and solved separately.From the case study,the route or network can be got to meet Luoyang demand well.Also,it is discovered that routes in the scheme from multiple-object are more gathering than the trip maximization model because of what their objects pursue.It is proved that the model and algorithm in this research are practical.It can give the governors planning suggestion with enough theory.It is meaningful to BRT planning and optimization. |
