Urban Transit Network Research Articles

Optimal Design of the Feeder-Bus Network Based on the Transfer System

This paper studied the classic feeder-bus network design problem (FBNDP), which can be described as follows: for the passenger travel demand between rail stations and bus stops on a given urban transit network, it designs the optimal feeder bus routes and frequencies so as to minimize the passengers’ travel expense and the operator’s cost. We extended the demand pattern of M-to-1 in most existing researches to M-to-M. We comprehensively considered the passenger travel cost, which includes the waiting and riding cost on the bus, riding cost on rail, and transfer cost between these two transportation modes, and presented a new genetic algorithm that determines the optimal feeder-bus operating frequencies under strict constraint conditions. The numerical examples under different demand patterns have been experienced and analysed, which showed the robustness and efficiency of the presented algorithm. We also found that the distribution pattern of the travel demand has a significant influence on the feeder-bus network construction.

An Algorithm for Connecting Suburban Rail Line to Urban Rail Transit Network

A greedy search based heuristic algorithm was proposed to solve the problem of connecting suburban rail line to existing urban mass transit network, aiming to provide efficient trips for passengers from satellite towns within metropolises to urban area. Optimum connection scheme set was sorted out from the perspectives respectively regarding optimization searching process and different transfer coefficients that reveal the predominance of transfer in path length. And at the same time, the searching process can also assure as short rail line and few connection stations be built as possible when adding more connection stations. High quality of connection design schemes can be ensured by these optional designs, which can also cover various connection modes of different station spacing, providing solid basis for evaluation and selection in future stage. Finally, the aforementioned algorithm was implemented in an example, generating an optimized connection scheme set, which proves the applicability of this algorithm in large scale rail network connection problem.

Discussion on the Future Building of Urban Rail Traffic Network of Hohhot

Based on the detailed analysis of the characteristics of urban rail traffic planning，and with analyzing city current situation of Hohhot，the necessity and sufficiency of the future network of urban rail transit in Hohhot are firstly analyzed .Then，according to the economic and social development goals of Hohhot，city scale and the present traffic situation as well as the city traffic construction planning and urban population forward distribution, the future sort of the project construction here is discussed. Finally,from the perspective of view of the economical society, some suggestions are put forward on integrated planning of urban rail transit network—— railway in order to enrich the theories and the methodology of the urban mass transit network planning.

Urban Mass Transit Network Project Selection Using the Fuzzy Expandable Engineering Optimization Model

Abstract. Mass transit line network’s option is a fuzzy optimization problem. Its line network evaluation is multi-objective and multi-hierarchy and the evaluation subsystems are incompatible. First, considering the urban development coordination, construction implementation, rationality of urban mass transit line network structure and comprehensive effect, researches established the appraisal index system of urban mass transit network using an assistant decision-making tool of system-analysis. Second, the study established extension and fuzzy optimization model with a vague idea of fuzzy mathematics, the knowledge of extenics and TOPSIS, explored the fuzzy and incompatibility issues on urban mass transit line network evaluation. The study introduced negotiation theory into weight construction, expanded single AHP to multi-experts weighting methods and combined it with entropy theory to form a new weight construction method. Last, as a validation, Changsha urban mass transit line network were evaluated and verified the feasibility and practicality of the model and method mentioned above.

A Decision Making Model for Urban Mass Transit Planning

The urban transit network planning is considered as a group decision making problem with multiple objectives and multiple decision makers, due to the its planning characteristics. A new group decision making method is presented to overcome the problem in current group decision making. With the idea of integration and collaboration, the group decision making problem is turned into the group decision making with multiple objectives and decision makers, and the two stage decision model is established. The dynamic index is transformed into static index with the dynamic multi-valued context, and the first stage decision model is established by entropy weight theory. The weight is given by experts with cluster analysis, and the aggregation model of group decision making is established with relative entropy, in the second stage.

Development of Location Method for Urban Public Transit Networks Based on Hub-and-Spoke Network Structure

A location method is presented for an urban public transit (PT) network based on the hub-and-spoke network structure model. The proposed method integrates the PT lines with transfer hubs. PT lines fall into four major service levels: subway, bus rapid transport, bus, and feeder bus. The transfer hubs fall into three major categories: intermodal terminals, transfer centers, and transfer stations. Every level of PT line is located by connecting the different classes of transfer hubs. The optimization objectives, constraints, and procedures for PT line locations are present, and they vary by level of PT service. The design and implementation of the proposed method are illustrated by a case study for the city of Fuzhou, China. The proposed allocation method offers a new approach for increasing the PT level of service of a high-density city. The procedure for allocating PT lines is practical and maneuverable.

Numerical Modeling of Affection of Foundation Pit Excavation on Metro Tunnel

With the development of urban construction, urban transit network has been gradually improved, but subway tunnel under its normal operation is inevitably affected by underground engineering activities such as foundation pit engineering. Based on the deep excavation near the effects of tunnel, the research content of 3d finite element analysis, from the qualitative research based on different situations of foundation excavation, is near to optimize the design and construction to provide the beneficial reference.

Hybrid Evolutionary Metaheuristics for Concurrent Multi-Objective Design of Urban Road and Public Transit Networks

This paper addresses a bi-modal multi-objective discrete urban road network design problem with automobile and bus flow interaction. The problem considers the concurrent urban road and bus network design in which the authorities play a major role in designing bus network topology. The road network design deals with the decision making for new street constructions, lane additions to existing streets, lane allocations for two-way streets, and the orientations and locations of one-way streets. The bus network design is performed by keeping the terminal stations of the existing bus lines unchanged and redesigning the forth and back routes of each line. Four measures, namely user benefit, the demand coverage of the bus network, the demand share of the bus mode, and the average travel generalized cost of bus passengers, are used to evaluate the network design scenarios. The problem is formulated as a multi-objective optimization model in which a modal-split/assignment model is included to depict the mode and route choice behaviors of travelers. The model is solved by the hybrid genetic algorithm and the hybrid clonal selection algorithm. The performance of these algorithms is presented and investigated by solving a number of test networks.

Urban Transit Coordination Using an Artificial Transportation System

An urban transit system usually consists of several modes, including busses, streetcars, a subway, and light rail. Unfortunately, coordination among different modes remains a challenging problem. Difficulties arise when modifying the transit network structure on a strategic level or when synchronizing timetables on a tactical level. Traditional transit network design and timetabling intend to solve a network-optimization problem based on static origin-destination (OD) information, with passenger assignment as a subproblem. In this paper, we propose an artificial urban transit system (AUTS) based on agent-based modeling and simulation. With AUTS, which is a special type of artificial transportation system (ATS), we are able to dynamically model the passenger's behavior and route choice and use the system to predict transit demand on a simplified transit network. The AUTS has the following important potential applications: forecasting transit flow; setting key parameters for urban transit networks - such as service frequencies and the capacity of subway trains - evaluating alternative modifications to subway rail and bus routes; and predicting the impact of special/emergency events to the transit network. We create a demonstration system of the Beijing transit network and present its applications in experiments.

Frequency design in urban transit networks with variable demand: Model and algorithm

The goal of this study is to present a methodology for modeling the transit frequency design problem with variable demand. A bilevel optimization model based on a non-cooperative Stackelberg game is used to describe the problem. The upper-level operator problem is formulated as a non-linear optimization model to maximize demand while considering fleet size and frequency constraints. The lower-level user problem is formulated as a capacity-constrained stochastic user equilibrium assignment model with variable demand, considering transfer delays between transit lines. An efficient algorithm is also developed for solving the proposed model. The upper-level model is solved by a gradient projection method. The gradient of the objective function is calculated at each iteration considering the fixed equilibrium overload delays determined by the lower-level model. The lower-level model is solved by an extant iterative balancing method, which was slightly modified for this study. An application of the proposed model and algorithm is presented using a small test network. The results of this application show that the developed algorithm converges well to an optimal point.

Equilibrium model and algorithm of urban transit assignment based on augmented network

The passenger flow assignment problem for the urban transit network is relatively complicated due to the complexity of the network structure and many factors influencing the passengers’ route and line choices. In the past three decades, many models have been proposed to solve the passenger flow assignment problem. However, the common-line problem remains challenging in transit flow assignment. In this paper, the characteristics of the urban transit network is analysed and a new technique of augmented network is proposed to represent the urban transit system. The purpose is to eliminate the complex common-line problem when modeling transit passenger flow assignment. Through this augmentation technique, the urban transit system can be represented by an augmented network-it then behaves like a simple network and can be used as a generalized network for traffic assignment or network analysis. This paper presents a user equilibrium model for the urban transit assignment problem based on such a technique. A numerical example is also provided to illustrate the approach.

Robustness Analysis of Urban Transit Networks Based on Bipartite Graph Model

Robustness is an important performance index of urban transit networks. The robustness analysis will lead to better evaluation and optimization measures of urban transit systems. In this paper, first, three types of urban transit system models are proposed based on the bipartite graph model, namely the original transit network(OTN), the transit stations network(TSN) and the transit lines network(TLN). Then a robustness index is defined to meet the practical requirement of traffic transit networks. A rapid robustness analysis algorithm based on a shortest path analysis is designed for the robustness analysis of urban transit networks. Finally, the robustness of Beijing transit system under the random attack and intentional attack is analyzed.

Regularity analysis for optimizing urban transit network design

Transit network planners often propose network structures that either assume a certain level of regularity or are even especially focused on improving service reliability, such as networks in which parts of lines share a common route or the introduction of short-turn services. The key idea is that travelers on that route will have a more frequent transit service. The impact of such network designs on service regularity is rarely analyzed in a quantitative way. This paper presents a tool that can be used to assess the impact of network changes on the regularity on a transit route and on the level of transit demand. The tool can use actual data on the punctuality of the transit system. The application of such a tool is illustrated in two ways. A case study on introducing coordinated services shows that the use of such a tool leads to more realistic estimates than the traditional approach. Second, a set of graphs is developed which can be used for a quick scan when considering network changes. These graphs can be used to assess the effect of coordinating the schedules and of improving the punctuality.

Urban rapid transit network capacity expansion

This paper examines a multi-period capacity expansion problem for rapid transit network design. The capacity expansion is realized through the location of train alignments and stations in an urban traffic context by selecting the time periods. The model maximizes the public transportation demand using a limited budget and designing lines for each period. The location problem incorporates the user decisions about mode and route. The network capacity expansion is a long-term planning problem because the network is built over several periods, in which the data (demand, resource price, etc.) are changing like the real problem changes. This complex problem cannot be solved by branch and bound, and for this reason, a heuristic approach has been defined in order to solve it. Both methods have been experimented in test networks.

Urban rapid transit network design: accelerated Benders decomposition

This paper presents an urban rapid transit network design model, which consists of the location of train alignments and stations in an urban traffic context. The design attempts to maximize the public transportation demand using the new infrastructure, considering a limited budget and number of transit lines. The location problem also incorporates the fact that users can choose their transportation mode and trips. In real cases, this problem is complex to solve because it has thousands of binary variables and constraints, and cannot be solved efficiently by Branch and Bound. For this reason, some algorithms based on Benders decomposition have been defined in order to solve it. These algorithms have been compared in test networks.

Measuring transit use variability with smart-card data

The potential of smart-card data for measuring the variability of urban public transit network use is the focus of this paper. Data collected during 277 consecutive days of travel on a Canadian transit network are processed for this purpose. The organization of data using an object-oriented approach is discussed. Then, measures of spatial and temporal variability of transit use for various types of card are defined and estimated using the data sets presented. Data mining techniques are also used to identify transit use cycles and homogenous days and weeks of travel among card segments and at various times of the year.

Multimodal traveling and its impact on urban transit network design

AbstractMultimodal trip making, that is trips using a combination of several modes between origin and destination, is expected to be beneficial to society and might offer advantages to the traveler as well. This article looks at some of the implications of multi‐modality in trip making for the design of urban transit systems since these play an important role in multi‐modal transportation systems. In this respect, the article looks at the strategic design characteristics of urban transit networks, that is line density, stop density and service frequencies for the case of multimodal access to urban transit networks and for hierarchical network structures in urban transit systems. The analyses show that multimodal access does not require alternative network structures. For hierarchical network structures it is concluded that these are primarily determined by the hierarchy in demand densities and thus by hierarchy in urban structures.

Genetic Algorithms for Optimal Urban Transit Network Design

This article attempts to highlight the effectiveness of genetic algorithm (GA)–based procedures in solving the urban transit network design problem (UTNDP). The article analyzes why traditional methods have problems in solving the UTNDP. The article also suggests procedures to alleviate these problems using GA–based optimization technique. The thrust of the article is three–fold: (1) to show the effectiveness of GAs in solving the UTNDP, (2) to identify features of the UTNDP that make it a difficult problem for traditional techniques, and (3) to suggest directions, through the presentation of GA–based methodologies for the UTNDP, for the development of GA–based procedures for solving other optimization problems having features similar to the UTNDP.

Multiuser-Class Urban Transit Network Design

In transit network design it is common to use characteristics of the average traveler to describe travel behavior, while in reality different traveler groups can be distinguished that react differently with respect to transport service quality. A study is conducted of the possible consequences of basing the design of urban transit networks on the preferences of specific traveler groups. To that end, an analytical network optimization model is developed that considers a mix of different traveler groups simultaneously. Results from the analyses show that focusing on specific traveler groups leads to clearly different network design characteristics. However, the optimal network design developed for the average traveler proved to be the best network for all traveler groups. Furthermore, it was found that focusing on traveler groups having good transport alternatives led to very low values of consumer surplus and social welfare. Optimizing transit networks while considering different traveler groups simultaneously results in networks that are similar to those using the traditional single-user-class approach based on the average traveler. Differences in preferences for traveler groups are balanced by the size of the resulting transit patronage. Apparently, a more realistic description of the demand side is not essential for urban transit network design.

Resolving splits in location/allocation modeling: a heuristic procedure for transit center decisions

Abstract A heuristic procedure is developed to assign buses to transit centers (garages) in such a way that all the buses on a particular route are assigned to a single transit center. This research builds on an optimal mixed integer programming location/allocation model that splits the bus assignments when capacity limitations were reached at a transit center. The heuristic procedure adopts a two-step process: namely, assignment of all buses of a route to a unique transit center, then switching of routes to alternative transit centers to enforce capacity limitations. The procedure is shown to still provide cost savings over current locations and allocations for the Vancouver Regional Transit System (VRTS), Canada's largest urban transit network.