Urban Multi-modal Public Transit Network Design And Optimization

In order to comprehensively improve the service quality of urban public transit,better meet people’s demands for diversified and personalized travel,analyze the influence mechanism of various participants on public transit,and optimize the allocation of multi-modal public transit network resources,it is urgent to have an overall planning of the multi-level public transport network and further improve its design.However,the traditional theory of public transit network design targeting at system optimization may lead to interest losses in some regions during the process of network optimization.In this context,this work takes the multi-modal public transit system composed of two typical modes of conventional bus transit and rail transit and demand-responsive bus as the research object.An equity lens is introduced into the design and optimization of multi-modal public transit network,which has important theoretical value and practical significance for improving the overall public transit service level.Firstly,as for the boarding and alighting stations inferring of passengers under a flat fare in the multi-modal public transit system,this work introduces a clustering algorithm to infer boarding stations based on urban multi-source public transit data(e.g.,smart card data,transit network data,bus GPS,and bus trajectory data)fusion.Based on the trip chaining theory and analysis of the whole process of travel,different passenger travel modes are categorized into four types according to whether the transfer between rail transit and bus traffic exist.The corresponding alighting station inferring methods are proposed for different travel modes,based on which passenger trip origin-destination(OD)matrices are estimated.Then the OD matrix will provide data support for the analysis on passenger travel characteristics and the design and optimization of public transit network.Secondly,this work proposes an algorithm to build the public transit trip chain and identify transfer stops under different travel modes based on the trip chaining theory and OD pairs.Based on the multi-source public transit data of Nanjing,the trip chain structure under different travel modes of passengers in Nanjing is built.Then,statistical analysis of travel characteristics such as travel modes,travel time,travel distance and transfer characteristics like transfer coefficient and transfer times is implemented.Considering the public welfare nature of urban public transit is mainly featured in the aspect of basic support for commuting needs,further analysis was made of commuting demand characteristics,hereby indicating the gap in commuting time and distance by public transit between urban center and suburbs.Compared with other areas within a city,new job growth,rapid,reliable and large-capacity public transport resources are concentrated in city centers,which causes the fairness issues of public transit network.Thirdly,the equity of multi-modal public transit network in this thesis is defined in macro and micro levels,respectively.Moreover,the index systems to measure the equity in transport modes and spatial equity are constructed.Specifically,the macro level focuses on the overall urban transport system measured by public transportation competitiveness index which indicates the gap in travel time between travels by public transit and car.The micro level focuses on the spatial equity of public transit system,which assessing the accessibility of various activities by public transit network for passengers from different areas or groups within a city.The index that calculates the spatial distribution of public transit resources including the coverage percentage of the public transport station,public transit stop density,average nearest neighbor index,location quotient index,Moran’s I index and public transit services index,and the spatial distribution of job accessibility by transit network are chosen to measure the micro level equity.Then this work use Lorenz curves and Theil index to geographically compare the level of multi-modal transit services and job accessibility by multi-modal transit network in Nanjing.The results show that the public transportation competitiveness index of different areas in Nanjing,on average,is about 2.19.The Gini coefficient of public transit services index is 0.53 while the Gini coefficient of job accessibility is about 0.44,all of which indicate the inequity of distribution of multi-modal public transit services throughout areas and groups.Therefore,it is necessary and important to introduce the concept of equity in the process public transit network design and optimization.Fourthly,the equity in transport modes and spatial equity are introduced into the methods of multi-modal transit network design.A model of double objective(i.e.public transportation competitiveness index attains superior and minimize the total cost of public transport system)for settling design problems of multi-modal transit network is built by constraints of spatial equity measured by the difference in public transit supply index across areas or groups.Based on the public transport demand between nodes,two types of alternative bus route sets are set as the initial ones from the perspective of passengers and public transport operators,respectively.Then the genetic algorithm is applied to solve the model.The rationality and validity of the proposed model and algorithm are verified by applying a case based on a Mandl network analysis.Finally,due to the difference in travel demand,infrastructure and operation cost of pub lic transit of different areas within a city,the corresponding optimization strategy is proposed for different areas based on the design of multi-modal public transit network.As for the central area of a city,a route optimization model of feeder bus for meeting the high demand offirst/last mile service to and from the major fixed-route railway transit networks is built by constraints of minimizing the travel cost of passengers based on the design of multi-modal transit network.Optimum transit networks of feeder bus have been achieved using single-objective approaches via tabu search algorithms.The used input data and study area are based on the real transit network of central area of the city of Suzhou.With regard to the suburbs or areas with low travel demand within a city,a route planning model of demand-responsive bus that connecting stations in a multi-modal transit network for extending the scope of the services of the public transit network.This modal realizes the reasonable location of dynamic bus stops through the improved ST-DBSCAN algorithm,based on which a VRPTW(vehicle routing problem with time-windows)model of double-objective optimization to minimize the travel cost of passengers and maximize the profits of public transport company is established.A penalty of the actual arrival time minus the latest feasible arrival time is assigned to the estimated route.The NSGA-Ⅱ algorithm was constructed to solve the VRPTW,and the applicability of the proposed model and algorithm was verified by an example.