Bus Transit Network Research Articles

Evaluating Fare Evasion Risk in Bus Transit Networks

Evaluating Fare Evasion Risk in Bus Transit Networks

Life cycle CO₂ footprint reduction comparison of hybrid and electric buses for bus transit networks

To control the global warming by ensuring the greenhouse gas emissions reduction of the automotive sector, the standards or norms are getting ever stricter globally, specifically in the past few years. In view of this, great emphasis is currently being given to the shift towards electric vehicles. However, it is very important to critically evaluate the overall life cycle of different powertrain technologies. In this study, such analysis has been carried out for the bus rapid transit networks in the 4 largest cities of Spain: Madrid, Barcelona, Valencia and Seville. Ten different lines were selected from each city and their driving-cycles were designed by extracting real time data from GPS used for simulating 3 different bus powertrains (diesel, hybrid and electric) for real-life results of the vehicles on each route. A life cycle analysis of the different bus configurations was done considering a wide perspective from manufacturing, use, maintenance to end-of-life stages, to compare the CO₂ footprints of the 3 evaluated powertrains using the database of the software GREET. The CO₂ footprints of the electric bus was also estimated for the years 2030 and 2050, using the predictions for cleaner electricity grids for future perspective. Compared to the standard diesel bus results, the overall results for hybrid and electric bus show 40% decrement and 30% increment of CO₂ well-to-tank emissions, respectively, 40% and 60% decrement of CO₂ life cycle emissions; 30% increment and 60% decrement of the buses’ driving range and, 2.5% and 30% addition in the life cycle cost.

WALK MODELLING WHEN DESIGNING SMALL BUS TRANSIT NETWORKS

Models for the design of public bus transit networks are usually based on the historically observed origin-demand travel patterns of potential passengers. The option of a passenger choosing to walk is, however, not usually incorporated into the design models for such networks. We argue that the absence of this model feature might lead to significant sub-optimality, especially in the design of small public bus transit networks. A novel approach to including this feature in the bus frequency setting aspect of public bus transit network design models is demonstrated in this paper, in which passenger transit modal choices are modelled on the basis of an existing optimal strategy transit assignment model. The newly proposed bi-objective route design and frequency setting models are applied to a realistic case study involving the establishment of a public bus transit system for students on a university campus; and this model implementation is used to gain insight into passenger route choice behaviour, based on individual preferences between walking or using buses. It is shown in the context of this case study that including the option of a passenger walking in the design models for public bus transit networks can affect the efficacy of the final network, especially if the network is small.

A Multi-Objective Meta-Heuristic Approach to Improve the Bus Transit Network: A Case Study of Fargo-Moorhead Area

In this study, the Transit Network Design Problem (TNDP) is studied to determine the set of routes and frequency on each route for public transportation systems. To ensure the important concerns of planners like route length, route configuration, demand satisfaction, and attractiveness of the transit routes, the TNDP is solved to generate a set of routes by proposing an initial route set generation (IRSG) procedure embedded into the NSGA-II algorithm. The proposed IRSG algorithm aims to produce high-quality initial route set solutions to reach better optimization procedures. Moreover, the Multi-Objective Mixed-Integer Non-Linear Programming (MOMINLP) model is proposed to formulate the frequency setting problem on each route by minimizing the total travel time of passengers (user costs) and operator costs simultaneously, while maximizing the service coverage area near all the bus stops. The MOMINLP model is solved by applying the NSGA-II algorithm to produce a Pareto front between the first and the second objective functions. The model was applied to the Fargo-Moorhead Area (FMA), a small urban area. Results were compared with the existing transit network to measure the efficiency of the NSGA-II solution methodology. The proposed algorithm was found to considerably decrease the total travel time of passengers.

Evaluating the Capacity Coordination in the Urban Multimodal Transport Network

The urban multimodal transport network is composed of multiple layers of networks; thus, coordinating the capacity equilibrium among different sub-transport networks plays a crucial role to keep the entire network running efficiently. To quantify and evaluate the passenger flow distribution in an urban multimodal transport network, this research proposes a method to evaluate the capacity coordination in an urban multimodal transport network on the basis of assignment results calculated by the Stochastic User Equilibrium (SUE) model considering the link and path impedance of different sub-transport networks. It suggests evaluation functions for the indicator level of service (LOS) of the multimodal transport network, Gini coefficient of transport network, and mode share of transport modes, and it shows how the functions were estimated. Then, it reports on results with the evaluation scheme collected in a multimodal example application for roadway network, transit networks (bus transit network and urban rail transit network), and connection network. The evaluation results under different assumed origin–destination (OD) demand show the coordination degree and can be used to recognize shortcomings of the network. Moreover, the OD demand interval of real network with good coordination can be deduced, which can also help transport planners to find the optimal strategy.

Comparing the time-varying topology-based dynamics between large-scale bus transit and urban rail transit networks from a mesoscopic perspective

Comparing the time-varying topology-based dynamics between large-scale bus transit and urban rail transit networks from a mesoscopic perspective

Bus Transit Network Structure Selection With Multiple Objectives

Bus transportation is the essential mode of public transportation available for intra-district movements in India. The planning of different stages of bus transportation planning is usually done in an ad-hoc manner on the basis of the experience of the operators. For a rational design of the bus transit system, it is essential to take into account the objectives of different interest groups. Selection of an appropriate network structure is an essential part of the planning process. In this paper, a model developed for generating a number of alternative network structures using link deletion concept is presented. One of these alternatives can be selected on the basis of the trade-off between the user and operator objectives. The model has been applied to a case study of bus transit network of Visakhapatnam region in Andhra Pradesh.

Development of bus transit system control measures with open transit data

The purpose of this study is to analyse the accuracy of the static schedule of bus transit network in Delhi using real-time data available from Delhi’s Open Transit Data (OTD) platform. To access and organise the data, an algorithm that can convert real-time data into a General Transit Feed Specification (GTFS) format, needs to be designed. Further, this study intends to develop a methodology, which can convert raw data of bus locations into link travel times, which consequently, helps in identifying problematic links. As researchers continue to make use of the data available via GTFS, they may well be aware of the fact that such data may differ systematically from actual transit operations. Continuous improvement of the accuracy of the GTFS static file would benefit its users.

Bus crash risk evaluation: An adjusted framework and its application in a real network

Greater attention to bus safety can lead to relevant benefits for public transport companies in terms of higher service performance, reliability, and lower insurance costs. Therefore, measuring the crash risk on bus routes provides an opportunity to improve the safety performance of transit operators. Previous research has explored the effects of many factors regarding the frequency and severity of bus crashes, whereas only a handful of studies have defined some crash risk indexes. Conversely, to the best of our knowledge, almost no research has been done regarding the crash risk in the bus transit network that integrates frequency, severity, and the exposure factors. This paper proposes a new framework to assess the crash risk for each transit bus route by the integration of safety factors, prediction models and risk methods. More precisely, this framework identifies several safety factors and specifies the risk components in terms of frequency, severity and exposure factors that may affect bus crashes. Then, it models their relationships to build a bus crash risk function. Lastly, according to the values returned by the previous function, the crash risk for each route is computed and a safety performance ranking for each route is provided. The feasibility of this framework is demonstrated in a real case study by using bus crash data provided by a mid-sized Italian bus operator. The findings show that transit managers could implement this framework in a road traffic safety management system to evaluate the risk of crashes on routes, monitor the safety performance of each route and qualify each route according to recent safety norms.

A cross-city exploratory analysis of the robustness of bus transit networks using open-source data

A robust bus transit network is of fundamental importance for sustainable development by alleviating urban problems. This paper aims to explore the robustness of 57 bus transit networks from the aspect of transferability. Bus transit networks are constructed using open-source data from the same data source for ensuring a consistent comparison, and the network robustness is analyzed using giant component (GC) to represent the maximum scale of transferability and network efficiency (NE) that characterizes the overall efficiency of transferability. (1) The results reveal a universal heavy-tailed distribution of network betweenness irrespective of cities and indicate target attack is more destructive to network robustness than random attack. (2) Different cities have different degrees of robustness, where most large cities tend to be more vulnerable than small cities and NE is more likely to be affected by target attack than GC. (3) The impact of target attack may become weaker than random attack after removing a certain percentage of nodes, which varies in different cities. (4) Thereafter, we present clusters of cities according to similarities of their network robustness. Thus, our comparative results can benefit transit planners and policymakers by enhancing the robustness of bus transit networks.

Assessing the Risk of Bus Crashes in Transit Systems

Although public transport buses may be considered a safe transportation mode, bus safety is a crucial issue from the perspectives of operators, passengers and local authorities owing to the relevant implications it generates. Therefore, assessing the risk of crashes on bus routes may help improve the safety performance of transit operators. Much research has identified patterns of bus crashes to understand the effects of many factors on the frequency and the severity of them. Conversely, to the best of our knowledge, the research measuring the risk of crashes in bus transit networks is seldom faced. This paper adjusts existing methods to assess the safety on bus transit networks by the integration of safety factors, prediction models and risk methods. More precisely, first, the methodology identifies several safety factors as well as the exposure risk factors. Second, this methodology specifies the risk components in terms of frequency, severity and exposure factors that may affect bus crashes and models their relationships in a risk function. Third, this methodology computes the risk of crashes for each route and provides a ranking of safety performance. A real case study demonstrates the feasibility of this methodology using 3,457 bus crashes provided by a mid-sized Italian bus operator. This experiment shows that transit managers could adopt this methodology to perform an accurate safety analysis on each route. Moreover, this methodology could be implemented in a road traffic safety management system in order to evaluate the risk of crashes on routes, monitor the safety performance of each route and qualify each route according to recent safety norms.

Mathematical formulations for the bimodal bus-pedestrian social welfare network design problem

We face the problem of designing a bus transit network, locating the most convenient bus stops and defining the set of bus lines without considering an a priori set of candidate lines. In order to model the problem, we consider a bimodal network composed of two layers, each one corresponding to a different transportation mode: pedestrian and bus. We propose two exact formulations and compare them by means of the ϵ-constraint method, thus obtaining a set of efficient solutions that simultaneously consider the total user travel time (composed of in-bus travel time, waiting time, walking time and transfer time) and service operator objectives. Finally, the best formulation is tested in a real case scenario.

Joint Optimization of Regular Charging Electric Bus Transit Network Schedule and Stationary Charger Deployment considering Partial Charging Policy and Time-of-Use Electricity Prices

Electric buses (EBs) have been implemented worldwide and exhibited great potential for air pollution reduction and traffic noise control. In regular charging scenarios, the deployment of charging facilities and the operational scheduling of the transit system is crucial to bus transit system management. In this paper, we proposed a joint optimization model of regular charging electric bus transit network schedule and stationary charger deployment considering partial charging policy and time-of-use electricity prices. The objective of the model is to minimize the total investment cost of the transit system including the capital and maintenance cost of EBs and chargers, the power consumption cost, and time-related in-service cost. A solving procedure based on the improved adaptive genetic algorithm (AGA) is further designed and a transit network at inner Anting Town, Shanghai, with 8 individual bus routes and 867 daily service trips is adopted for the model validation. The validation results illustrated that the methodology considering the partial charging policy can arrange the charging schedule adaptive to the time-of-use electricity prices. Compared with the benchmark of single line separate scheduling, the proposed model can yield 3 million RMB investment saving by highly utilizing EBs and battery chargers.

Directionality‐centric bus transit network segmentation for on‐demand public transit

The recent growth in real-time, high-capacity ride-sharing has made on-demand public transit (ODPT) a reality. ODPT systems serving passengers using a vehicle fleet that operates with flexible routes, strive to minimise fleet travel distance. Heuristic routing algorithms have been integrated in ODPT systems in order to improve responsiveness. However, route computation time in such algorithms depends on problem complexity and hence increases for large scale problems. Thus, network segmentation techniques that exploit parallel computing have been proposed in order to reduce route computation time. Even though computation time can be reduced using segmentation in existing techniques, it comes at the cost of degradation of route quality due to static demarcation of boundaries and disregarding real road network distances. Thus, this work proposes, a directionality-centric bus transit network segmentation technique that exploits parallel computation capable of computing routes in near real-time while providing high scalability. Additionally, a dynamic fleet allocation algorithm that exploits proximity and flexibility to minimise vehicle detours while maximising fleet utilisation is proposed. Experimental evaluations on a real road network confirm that the proposed method achieves notable speed-up in flexible route computation without compromising route quality compared to a widely used unsupervised learning technique.

Vulnerability assessment and visualization of large-scale bus transit network under route service disruption

Having a vulnerability assessment of a large-scale bus transit network (LBTN), an essential part of urban vulnerability assessment, is indispensable for developing urban transportation sustainability. The complex network approach is usually used to realize this goal because it focuses on a mesoscopic perspective and has a unique advantage of calculation efficiency in large-scale networks. However, the vulnerability assessment of LBTNs is usually tested based on node attacks or edge attacks rather than route attacks because of the widely existing “route collinear problem”, which makes the infrastructure disruption and the route service disruption indistinguishable. This paper establishes a novel vulnerability assessment and visualization framework under the perspective of route service disruption. This framework provides a novel perspective for understanding complex systems, lays the foundation for LBTN risk identification, and significantly lowers the availability barrier of the required data, thereby extending the vulnerability study framework based on a complex network approach, from statistical physics to engineering.

A bi-objective decision model and method for the integrated optimization of bus line planning and lane reservation

The increasingly serious traffic congestion makes the bus system more and more inefficient. It is recognized all over the world that designing an attractive bus transit network is primordial to alleviate traffic congestion and reduce pollution, but it is a big challenge from an economic and technical point of view. In the literature, dedicated bus lanes are generally set up to improve the efficiency of bus transit network without considering bus line planning. This study investigates a new bi-objective bus line planning and lane reservation integrated optimization problem that is a complex combinatorial optimization problem. The objective is to minimize the total travel time of passengers and the lane reservation negative impact, simultaneously. For the problem, a bi-objective integer linear programming model is first formulated and the problem complexity is proved to be NP-hard. Then, problem properties are explored to reduce search space for optimal solutions, and an iterative and fuzzy method based on $$\varepsilon $$ -constraint is proposed to yield the Pareto frontier and suggest a preferred solution for decision-makers. Experimental results on a case study and randomly generated instances demonstrate the effectiveness and efficiency of the proposed model and method.

Topological properties of bus transit networks considering demand and service utilization weight measures

We present a complex weighted network analysis of a bus transport network. We model the network as graphs in L-space and P-space and evaluate the statistical properties in unweighted and weighted cases. The weights considered include number of overlapping routes and passenger demand between two bus stops. We also introduce a new supply-based edge weight called Service Utilization Factor (SUF) and define it as the passenger demand per service between two stops. We extract the origin and destination of the passenger trips from bus ticket information. In the bus system under study, the tickets are issued between ’stages’ instead of between bus stops. We propose a points of interest based procedure to map the passenger demand between stages to between bus stops. The network has scale-free behaviour with preferential attachment of nodes and is similar to small-world networks. It is well-connected with an average of 1.4 transfers required to travel between any two points in the network. We identify redundant routes in the network from strength values in the SUF weighted networks. Disassortativity in the demand weighted network indicated that bus stops with higher attractiveness are not necessarily situated contiguously along a route. The SUF weighted network is assortative indicating presence of well-serviced stops along the same the route. We identified the stops with higher betweenness centrality, that can be ideal candidates for being developed as hubs. Our conclusions exemplify the importance of considering route overlaps, passenger demand and service utilization in bus network analysis and for building an efficient bus network.

Quantifying and classifying the robustness of bus transit networks

This study adopts Complex Network Theory in the context of bus transit network. The study aims at quantifying the topological characteristics and assessing the validity of static-robustness metrics as expressive measures of transit networks robustness. In addition, dynamic-robustness indices, that consider transit operational profile, are utilized to measure the cascading impacts of disruptive events. The analysis is based on a dataset of 40 bus transit networks. The results indicate that bus networks don’t conform to any major network class: scale-free, small-world, or random. Furthermore, the static-robustness metrics produced contradictory results, which raises valid concerns on their applicability. The dynamic-robustness indices developed in the current study indicated significant cascading impacts resulting from node removal relative to the removal of links. This behaviour was further examined through a two-step cluster analysis, which resulted in three distinct network clusters: small node-sensitive; small link-sensitive; and medium less-sensitive networks. These findings are directed to inform a robustness-based design of bus transit networks.

A comparative analysis of underground and bus transit networks through graph theory

The aim of this paper is to study the topographical features of a transportation infrastructure through graph theory. First, we construct a planar, connected, and simple graph for each considered infrastructure; then, we compute some normalized indices associated to the graph, namely largest eigenvalue, gap, a Betti number, and codimension. The set of indices proposed in this paper is new for this application. These indices are computed from either the adjacency matrix or the edge ideal of the graph, and so they depend on the overall topology of the graph itself; furthermore, since the normalized indices are scale-free, they allow us a more effective comparison between different transportation infrastructures. Two scenarios are considered in order to understand advantages and limits of the proposed approach: the first scenario concerns a set of underground networks of certain large cities in the world, whereas the second one concerns a set of bus transit networks of several medium-sized cities in Italy. Indices calculated for both scenarios show two types of results. First, they show that the proposed indices are able to estimate the different topologies of the considered networks: networks with the same number of vertices and of edges but not with the same graph have different indices. Second, they show that the values of the indices in the two scenarios not only belong to the same curve separately but fit well also into the same curve: the transportation networks, no matter whether underground or bus transit, seem to be controlled by similar mechanisms.

Synchronized Timetables for Bus Rapid Transit Networks in Small and Large Cities

The quality of public transportation service has major effects on people’s quality of life. During frequency and timetable setting, synchronization is a very important and complicated issue which can directly influence the utility and attractiveness of the system. In this paper, a mixed-integer nonlinear programming model is proposed that aims at setting timetables on a bus transit network with the maximum synchronization and the minimum number of fleet size. The proposed model is shown to be applicable for both small and large-scale transit networks by employing it for setting timetables on two samples of both sizes. As an illustrative example, a simple version of the model is coded and run in GAMS Software and a completely reasonable timetable is obtained. As the second example, the proposed model is used to set timetables on Tehran BRT networks through the genetic algorithm; then the NSGA-II is used to obtain the Pareto optimal solutions of the problem for five different scenarios. The Pareto optimal solutions are used to draw the Pareto optimal fronts which act as an essential decision making tool. The overall results show that the proposed model is efficient enough to be employed setting timetables on transit networks with different sizes.