Monash University, Institute of Transport Studies: World Transit Research (WTR)
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Modulated spatiotemporal clustering of smart card users
No full textSmart card data offers an in-depth understanding of the travel behavior of public transport users. An efficient way to analyze public transport users is to group them into different clusters with similar behaviors. However, this clustering process should take into account space and time because both of these dimensions characterize daily trips. Depending on the outcome, we might wish to give more importance to space or to time, or we might wish to balance the two. In this study, we present a spatiotemporal clustering tool that permits modulation regarding the importance of space versus time. We then test this tool with different values for the space–time balance parameter to evaluate the influence of this parameter on the results. The method has been applied to 769,614 smart card transactions of the Réseau de transport de la Capitale (Quebec City, Canada). Results show that the influence of space and time can indeed be controlled, and that the types of clusters obtained vary whether one or both of the dimensions are considered
G2Viz: an online tool for visualizing and analyzing a public transit system from GTFS data
No full textPublic transit agencies have amassed substantial data through on-board and off-board sensors over the years. While data collection was the primary focus, there is now a shift towards deriving actionable insights from this wealth of information. As data-driven decision making becomes increasingly vital, there is a growing need for effective ways to visualize and convey complex insights to decision makers. This study addresses this need by introducing G2Viz, a visualizer for public transit operations. The development process of G2Viz spans requirement gathering, planning, and design, encompassing software architecture, data models, user interfaces, and system components. Rigorous implementation and testing ensure the tool’s functionality and effectiveness. G2Viz, designed to dynamically visualize public transit operations using General Transit Feed Specification (GTFS) data, is a web application accessible globally via any web browser. Its open-source nature, robustness, and versatility facilitate communication among transit agencies, users, researchers, and city authorities. G2Viz empowers transit planners to make well-informed decisions about public transportation
Prioritizing Outlier Parcels for Public Transport-Based Crowdshipping in Urban Logistics
No full textThe continuous growth of e-commerce puts pressure on logistic service providers to fulfill more parcel deliveries. Concurrently, there are increasing calls from governments and society to carry this out sustainably. Crowdshipping is one possible innovative logistic service that addresses these challenges. Crowdshipping enlists members of the public to fulfill parcel deliveries, ideally en route along their pre-committed journeys. In this paper, we consider a setting where public transport passengers can serve as crowdshippers and propose a comprehensive framework to organize the scheme. Firstly, outlier parcels are identified as being suitable for crowdshipping. Then, these outlying parcels are matched with crowdshippers, who pick up parcels from a set of selected parcel lockers. We also investigate the viability of crowdshipping with real-world data. By comparing a carrier’s performance to a base case without crowdshipping, the results show that delivery vehicle kilometers traveled and associated carbon dioxide emissions can reduce by up to 20%. A total of 11% of parcels can be redirected to be delivered via crowdshipping. Crowdshipping using public transport has the potential to be a sustainable way to fulfill urban logistics in a dense city
Auto-Oriented Communities in Developing Countries: Bus Rapid Transit Implementation Prospects
No full textPublic transportation services often face challenges in middle- and low-income nations from both public acceptance and economic constraints. Jordan is classified as a middle-income country with a population of over 10 million, 4 million of whom live in Amman, the capital. The development and operation of a bus rapid transit (BRT) system in Amman city was recently proposed. The BRT project is anticipated to offer a solution to the city’s escalating congestion problem. This study’s objective is to conduct a “before” analysis to identify the variables that affect the willingness of people to use the Amman BRT system. The socioeconomic characteristics and travel habits of individuals were used to model the willingness to use BRT. An online survey was distributed to Amman residents and 238 valid responses were returned. Two popular techniques were utilized: binary logistic regression and Bayesian networks. Ten models were developed: one binary logistic model and nine Bayesian network models. The results of these models were compared based on accuracy, sensitivity, specificity, area under the Receiver Operating Characteristic (ROC) curve, complexity, and number of selected variables. It was found that Bayesian networks were more effective in modeling willingness to use BRT. Willingness to use BRT was shown to be higher among households without cars, youths, females, and university students, and if there were fewer transfers along the route. It became clear that introducing a new public transportation system is well appreciated, particularly in areas with low income, insufficient existing public transportation services, and where driving a car is the norm
Evaluating Equity: A Method for Analyzing the Transit Accessibility of Affordable Housing Units
No full textImproving transit access for people in low-income communities is an important consideration for transit providers. However, there has only been a limited amount of research on the transit accessibility of affordable housing units. This paper aims to develop a method for evaluating the transit equity of existing affordable housing units and propose easy-to-implement modifications to local bus services to increase transit accessibility levels (assuming housing locations do not change in the short term). The proposed method has three steps, and it is applied to three cities in Tennessee with primarily bus-based transit systems. The first step measures the transit accessibility of specific affordable housing locations and citywide transit accessibility levels using a web-based platform built using open-source software. The second step evaluates the transit equity of affordable housing programs at the city level using Lorenz curves and Gini coefficients, and the transit equity of specific affordable housing locations by proposing a simple inequity index. The results reveal that the level of transit equity for affordable housing units differs across housing programs and cities. In the third step, an example of a modification to a local bus route is evaluated for one affordable housing location with a high inequity index to demonstrate the applicability of the method. The substantial increase in accessible jobs after modification, from 135 to 6,400, highlights the potential effectiveness of implementing short-term transit service changes to improve the accessibility of existing affordable housing locations. This three-step method primarily relies on open datasets that are also available for other regions in the U.S.A
Data-driven timetable design and passenger flow control optimization in metro lines
No full textAs travel demands in metro systems continue to grow rapidly, the mismatch between passenger demand and metro capacity has become a critical challenge in metro operations. To address this issue, this paper investigates the collaborative optimization of train timetables and station-based passenger flow control under stochastic demand, which aims to minimize the total system cost while ensuring an adequate service level to each station. We formulate the research problem as a stochastic mixed-integer programming model with expected travel time cost constraints for each station and translate it into a multi-objective attainability problem by imposing a target on the objective value. We develop an efficient operation policy that determines the timetable and flow control decisions in response to each demand scenario, satisfying the objective and service level targets in the long term when feasible. We conduct extensive numerical experiments on both synthetic and real-world transit data to evaluate the performance of our approach. The results demonstrate that our approach outperforms the benchmark first-come-first-served policy in terms of efficiency and service fairness under both exogenous and endogenous demand distributions. The improvement achieved by our approach is attributed to the prioritization of short trips over long ones, effectively exploiting the reusable nature of train capacity
Does urban bus route assignment improve air quality?
No full textWorldwide, one of the most important causes of mortality is air pollution. To solve this problem, governments have implemented policies to reduce on-road and industrial emissions. In this regard, the Barcelona city council and Transports Metropolitans de Barcelona (TMB) started implementing the Nova Xarxa de Bus (NXB) to redefine the bus network following the criteria of connectivity, efficiency, and rationality. This policy was implemented in seven phases from 2012 to 2018. In this context, this paper analyses the impact of this policy on Barcelona’s air quality using a dataset from 2008 to 2016. Using a difference-in-difference approach, we show that implementing these new routes increased air quality in Barcelona. Additionally, we show that pollution decreased in each phase analysed, especially in the air quality stations near the main roads. From our results, we can infer that an optimal bus route design can improve air quality in urban areas
Mixed-fleet operation of battery electric bus and hydrogen bus: Considering limited depot size with flexible refueling processes
No full textElectrified transit is crucial for promoting zero-emission transportation in metropolitan cities. However, this initiative faces considerable challenges in Hong Kong due to limited space available for parking and refueling bus fleets. Despite the inexpensive operational costs of battery electric buses (BEBs), plenty of space is required to park and refuel BEBs. Hydrogen buses (HBs) can partially address the space issue with a longer driving range and shorter refueling time compared to the BEBs, whereas more operational costs must be spent. Therefore, a mixed fleet with BEB of HB tends to be a more cost-effective solution. In consideration of the distinctive characteristics of BEBs and HBs, this study develops an integrated vehicle scheduling and refueling of mixed fleets with multiple depots (IVSR-MFMD) restricted by the limited depot size (i.e., space provided for bus parking and bus refueling), where flexible refueling processes, allowing for uncertain refueling start times and refueling amounts, are endogenously incorporated into the operational cycle. The speed-up techniques are further used to reduce problem dimensions and reformulate the model. A two-route-two-depot example and a real-world case in Hong Kong are used to verify the model. The results demonstrate that adopting HB can efficiently reduce depot size and achieve lower operational costs when routes consume massive energy. Additionally, it is found that flexible refueling processes lead to lower operational costs, and the customized speed-up techniques can significantly improve computational efficiency
Path-choice-constrained bus bridging design under urban rail transit disruptions
No full textAlthough urban rail transit systems play a crucial role in urban mobility, they frequently suffer from unexpected disruptions due to power loss, severe weather, equipment failure, and other factors that cause significant disruptions in passenger travel and, in turn, socioeconomic losses. To alleviate the inconvenience of affected passengers, bus bridging services are often provided when rail service has been suspended. Prior research has yielded various methodologies for effective bus bridging services; however, they are mainly based on the strong assumption that passengers must follow predetermined bus bridging routes. Less attention is paid to passengers’ path choice behaviors, which could affect the performance of the bus bridging services deployed. In this paper, we specifically take passengers’ path choice behaviors into account and address the bus bridging optimization problem under urban rail transit disruptions. Incorporating a PS-logit model to estimate the probabilities of passenger path choices, we propose a mixed-integer nonlinear programming model to simultaneously determine the selection of bus bridging routes and vehicle deployment on selected bridging routes, with the objective of minimizing the cost associated with passenger travel time and unsatisfied demand. To solve this computationally challenging large-scale nonlinear model, we design a customized variable neighborhood search algorithm framework. A case study based on the Shanghai rail transit system is conducted to demonstrate the applicability and feasibility of the proposed approach. The results indicate that our approach can provide an effective bus bridging scheme that considers passenger path choice, which facilitates rapid response to rail disruptions. Our scheme substantially outperforms the current bridging designs that do not consider passenger path choice behaviors by significantly reducing the number of unserved passengers
Zero-emission bus economics study
No full textThis report details the process to develop a user-friendly Excel model – ‘the ZEB Cost Model’ – that allows the user to conduct a comprehensive evaluation of the different use-cases available to replace existing diesel buses with zero-emission buses (ZEB). The use-cases include options for replacing diesel buses at the end of their useful life, retiring diesel buses early, and retaining diesel buses to induce further mode shift. Thus, the ZEB Cost Model developed under this assignment and described in this report empowers public transport authorities to make informed decarbonisation investment decisions. Further, this report delivers several key findings revealed in the model design process. First, emissions savings from early retirement of diesel buses far outweigh emissions from earlier bus construction. Second, operations and maintenance costs – and, more specifically, energy costs (electricity, hydrogen or diesel) – are the key driver of total cost of ownership for different bus technologies. Third, battery electric buses, whether repowered diesel buses or new battery electric buses, are the least cost option with which to replace existing diesel buses. This is because of the high cost of hydrogen in New Zealand at the time of this research and the importance of fuel costs in overall total cost of ownership