In the multi-modal public transit system, the separation of the planning and management processes intensifies the patronage competition between different public transit systems, and results in the wasting of transit capacity resources. In order to alleviate the passenger flow competition inside the multi-modal transit systems and improve the overall benefit of the urban public transit system, an integrated method for designing the multi-modal public transit network is urgently needed.
Three functional levels of backbone transit network, trunk transit network and local transit network in the multi-modal public transit network are classified. Transit stations, transit line sections and transfer links are defined as the key elements of multi-modal public transit networks. The network representation models with transit stations and transit lines as nodes respectively for analyzing the features of the multi-modal public transit network are formulated. The network performance indexes of transit stations and transit line sections are defined to analyze the basic network characteristics of the multi-modal public transit network; by examinating the distribution of the geometric performance indicators of transit lines, the statistical characteristics of the multi-modal transit network of each functional level are explored; through the distribution of the total number of shared stations between transit lines of different functional levels and between transit lines of the same functional level, the connectivity feature of the multi-modal public transit network is discussed.
The distributions of the total trip distance and trip distance in access and egress trip stages for multi-modal trips and uni-modal trips in multi-modal public transit system are compared. The travel mode choice behavior in access and egress trip stages of multi-modal trips is investigated. Concentrating on the transfer stages of multi-modal trips, the transfer times, transfer distance and transfer penalties are explored. By conducting the correlation analysis between passengers’ attitudes to congestion delay, transfer times and transit time and public transit usage willingness, passengers’ choice behavior characteristics at stations are inferred.
Based on the definations of the relationship between passenger flow, operating speed and functional level of transit lines, and the aggregation of passenger flow, a heuristic method for generating initial transit lines in the multi-modal transit network is present. Based on the demand of OD pairs, the subset of OD pairs is formed. The OD pairs are selected as the current OD pair one by one. For the current OD pair, the shortest path algorithm is used to determine the current OD pair’s shortest path in the road network and the shortest path in the road-transit hybrid network. By comparing these two shortest paths, whether the aggregation of passenger flow happens is judged. When the aggregation of passenger flow occurs, a method for generating a candidate line based on OD pair insertion, that is, by changing the route of the existing initial transit line to serve the current OD pair, is proposed. When the OD pair insertion conditions are not satisfied, a candidate route is formd by splitting the second shortest path. If all of the above conditions are not satisfied, the first type of expected shortest path is chosed as the route to generate a new candidate transit line. If the new candidate transit line satisfies the overlapping condition and the line length constraint condition, it is added to the initial transit line set. Finally the service frequency is determined based on the maximum link flow for each initial transit line.
According to passengers’ travel route choice hypothesis and fail-to-board hypothesis in multi-modal transit system, the virtual transit network nodes and arcs are used to represent the transit vehicles operation and the passenger travel process, the transfer passenger flow inside the same station, or between different stations, and the originating passenger flow are distinguished, and a multi-modal transit network representation model for passenger flow assignment is established. Under the capacity constraint of the multi-modal transit system, a passenger flow assignment method in multi-modal transit network, which is based on the method of successive averages, is proposed. Based on the hyperpath theory, the formula for calculating flow split probability for arcs at different dummy nodes is defined, an improved shortest hyperpath model is constructed, and an improved shortest hyperpath search algorithm is designed. According to the passenger flow conservation condition, methods for calculating the passenger flow at dummy nodes and on dummy arcs and the passenger fail-to-board probability are determined.
Taking the sum of passengers’ total travel cost and agencies’ total operating cost of transit systems as objective function, and taking the maximum vehicle investment, the maximum construction buget of backbone network and the minimum coverage of transit demand as constraints, a combinatorial optimization model for multi-modal public transit networks is constructed. Based on the basic genetic algorithm, a solution algorithm for the optimization model is designed.