Monash University, Institute of Transport Studies: World Transit Research (WTR)
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Impact of “light” bus rapid transit (BRT-light) on traffic and emissions in a travel corridor
No full textOur study compared observed traffic volumes in the Bus Rapid Transit (BRT-Light) corridor to those predicted using two different quasi-experimental methods. The first quasi-experimental design, referred to as interrupted time series, assumes the trends in traffic on BRT alignment from 2013 to 2017 continue through to 2019 after BRT-Light is in place. Making that assumption, traffic volume on the BRT alignment is 2514 vehicles per day lower (−7.38%) than one would expect based on the preexisting trend. The second quasi-experimental design is called a before-after design with a control group, which assumes that traffic volume on the BRT route would increase by the same percentage as traffic on parallel streets to the BRT line, that is 2.30 percent or 645 VPD between before and after. Also, BRT alignment\u27s traffic volume was reduced by 1249 VPD or 4.78 percent more rather than outside of BRT corridor, and 17,632 VPD or 9.33 percent considering trip generation. Meanwhile, transit ridership in the corridor increased by 8687 passengers per day (122.66%) more than expected with the introduction of BRT, which helps account for the effective reduction of vehicular traffic on the streets that comprise the BRT alignment. Through the section analysis, we found that dedicated right-of-way reduced traffic effectively. Our estimates suggest that BRT-Light will result in an annual reduction of 17,886,229 pounds of CO2 emissions and 914,614 gallons of gasoline consumption. Based on these results, we conclude that BRT-Light had a positive effect on easing vehicle traffic volume and emissions in the Provo-Orem metropolitan area
Addressing electric transit network design frequency setting problem with dynamic transit assignment
No full textElectric buses are projected to become the standard mode of transit systems in the foreseeable future for sustainable transportation. Realizing this transition necessitates a meticulously planned electricity infrastructure design which should be handled simultaneously with the traditional transit network planning to enhance the efficiency of electric transit networks. For this integrated problem referred to as the Electric Transit Network Design and Frequency Setting Problem, several studies have been conducted, with the absence of evaluating the energy state of each electric bus individually. The Multi-Objective Differential Evolution Algorithm (MODEA), developed to address the complex problem at hand, is tested on a hypothetical network by filling research gaps in previous studies. Energy states resulting from the individual evaluation of each bus in the best Pareto optimal solution considering dynamic aspects of the transit network are presented comprehensively. Furthermore, the impact of dynamic characteristics on the electric transit network design is demonstrated by comparing the findings obtained on the static network
Barriers Associated with the First/Last Mile Trip and Solutions to Bridge the Gap: A Scoping Literature Review
No full textA first/last mile (FLM) trip is defined as the distance a person travels before boarding a transit stop (first mile) or after disembarking (last mile). FLM trips could encourage or discourage people from riding transit systems, affecting their access to major services such as healthcare, education, employment, and transportation. When considering underserved communities specifically, where people rely heavily on public transportation, challenges to completing the FLM trip often negatively impact quality of life. This paper provides a comprehensive review of previous research efforts discussing the FLM trip. It begins by identifying the outcomes of challenges in completing the FLM trip and the contributing factors to those challenges and subsequently summarizes the various solutions transportation agencies and decision-makers have implemented to address the first and last legs for transit users. The most common solutions include shared mobility services, circulating shuttles, and built environment improvements. This research serves as a valuable reference for transportation professionals to enrich their understanding of the FLM barriers and the potential solutions to bridge this FLM gap
Resilience as a Service for Transportation Networks: Definition and Basic Concepts
No full textUrban transportation systems\u27 structure and functionality can be affected by unexpected disruptions for several reasons, such as natural hazards, intentional attacks, accidents, and so forth. The conventional definition of resilience is the capacity to withstand, assimilate, adjust, and expeditiously recuperate from various forms of perturbations such as shocks, disturbances, and deliberate attacks. Though multiple studies in the literature focus on resilience assessment and improving the resilience level of mobility services before disruption, few studies offer solutions for the operators of transportation systems during disruptions to alleviate their negative effects, such as reducing the recovery time. In this context, a new paradigm called ``resilience as a service\u27\u27 (RaaS) has emerged in the field of operations management. The idea of RaaS is to integrate the available resources of different service providers to manage disruptions and maintain the system\u27s resilience. This paper proposes a definition of RaaS dedicated to transportation systems. To provide a methodological example for the RaaS paradigm, we formulate a bi-level optimization problem to represent a solution example that RaaS providers can deliver. The upper-level model formulates the resource reallocation problem during disruption from the perspective of RaaS providers, while the lower-level model considers user perspectives. We provide a numerical example in a real test case of a French city to illustrate the benefits of implementing a RaaS solution. The results show that we can reduce the average travel delay of all users by 69%, including the delay results from the proposed RaaS strategy compared with the absence of RaaS
Conceptualising justice in transit-oriented development (TOD): towards an analytical framework
No full textOriginally conceived to create dense, diverse and mixed-used communities that are inclusive and sustainable communities, Transit-oriented Development (“TOD”) has come under increasing academic scrutiny on its negative implications on equity and justice. However, these injustices are often examined case-by-case individually, which revealed the lack of a comprehensive framework that is grounded in justice concepts and theories for analysing justice in TOD. In this paper, we aim to show the importance of, and suggest a framework for, analysing justice in TOD holistically. We begin by taking a brief overview of key theories and concepts in process and outcome justice. Then, through a thematic review of justice-related TOD literature, we synthesised three main justice issues currently existing in TOD: transit-induced gentrification; neglect of livelihood and well-being of disadvantaged groups; and poor inclusion and representation of different stakeholders. These issues revealed the interconnectedness and importance of both process and outcome justices in TOD. As such, we formulated an analytical framework by adopting the Institutional Analysis and Development (“IAD”) model (a tool for understanding institutional interactions in public policies) to examine process justice; and the 5Ds of the built environment (namely Density, Diversity, Design, Destination Accessibility, and Distance to Transit) to examine outcome justice. In brief, for process justice, our framework advocates open, accessible and equitable particiaption by all interested stakeholders to be able to give views, exercise their power, obtain and share information, and make decisions collectively, with dedicated efforts to facilitate participation of more disadvantaged groups. For outcome justice, our framework calls for providing suitable and equitable built environments (in terms of 5Ds) in different neighbourhoods in a TOD, with special attention towards the needs of disadvantaged groups. The framework serves as general guidance for researchers and planners to analyse the justice implications of TOD (both ex-ante and ex-post) in a holistic and conceptually-grounded manner, with a view to better positioning justice issues and directing efforts towards more just TODs
Discrete choice modeling with anonymized data
No full textThis paper presents an approach to estimate mode-choice models from spatially anonymized revealed preference travel survey data. We propose an algorithm to find a feasible sequence of activity locations for each individual that minimizes the maximum error of each trip’s Euclidean distance within the activity chain. The synthetic activity locations are then used to create unchosen alternatives within the choice set for each individual. This is followed by the mode-choice model estimation. We test our approach on three large-scale travel surveys conducted in Switzerland, Île-de-France, and São Paulo. We find that our methodological approach can reconstruct activity locations that accurately match trip Euclidean distances but with location errors that still provide location protection. The discrete mode-choice models estimated on the synthetic locations perform similarly, in terms of goodness of fit and prediction, to the ones obtained from the observed activity locations
Identifying critical transfer zones to coordinate transit with on-demand services using crowdsourced trajectory data
No full textThis study develops a data-driven approach for identifying critical transfer zones in the city to facilitate the coordination of transit and emerging on-demand services. First, the methods convert the trajectories into a 3 D grid with an optimal cube size. Built upon that, we zoom in and study the trajectory density of each mode in a cube and present the results by heatmaps. After that, we zoom out and aggregate those cube information fragments through the clustering algorithms to explore two critical patterns: the ridesharing swarm (RS) zones where many ridesharing trips go through, and the “sandwich pattern” zones where a transit trajectory dominant zone is sandwiched by two ridesharing trajectory dominant zones. Our numerical analysis confirms that these RS zones are well correlated to the promising areas/corridors for integrating transit and on-demand services; the “sandwich patterns” help discover first/last mile (FLM) zones. Last, we further develop a two-channel deep learning network to predict the variation of the FLM gaps so that adaptive services can be planned. A case study based on the field data of the second ring region of Chengdu, China confirms the effectiveness and capability of our analysis approach
Beyond fare evasion: the everyday moralities of non-payment and underpayment on public transport
No full textIn attempting to understand and prevent fare evasion, existing research and policy have often categorised fare evaders based on passenger ‘types’ or profiles. However, such categorisations of ‘malicious’ or ‘virtuous’ behaviours rely on underlying moral claims which often go unexamined. In this paper, we study how different actors construct such moral claims as part of everyday interactions. We demonstrate that the everyday moralities of not or under-paying are diverse, locally occasioned, and emotionally charged. Drawing on social media and video data from Chile and the UK, we examine interactions between passengers, by-standers, transport workers, and transport operators. We highlight the diverse resources that actors draw upon to construct moral claims around fare evasion, including the mobilisation of alternative moral categories; attempts to produce exceptions to formal rules; and the foregrounding of moral emotions. The paper engages with an interdisciplinary body of work which reassesses existing policies and societal responses to fare evasion, while also contributing to a nascent literature on everyday morality and mobilities
Planning a zero-emission mixed-fleet public bus system with minimal life cycle cost
No full textThe variety of available technology options for the operation of zero-emission bus systems gives rise to the problem of finding an optimal technology decision for bus operators. Among others, overnight charging, opportunity charging and hydrogen-based technology options are frequently pursued technological solutions. As their operating conditions are strongly influenced by the urban context, an optimal technology decision is far from trivial. In this paper, we propose an Integer Linear Programming (ILP) based optimization model that is built upon a broad input database, which allows a customized adaption to local circumstances. The ultimate goal is to determine an optimal technology decision for each bus line, considering its combined effects on charging and vehicle scheduling as well as infrastructural design. To this end, we develop technology-specific network representations for five distinct technologies. These networks can be viewed individually or as a multi-layered graph, which represents the input for the optimal technology mix. The proposed optimization framework is applied to a real-world instance with more than 4.000 timetabled trips. To study the sensitivity of solutions, parameter changes are tested in a comprehensive scenario design. The subsequent analysis produces valuable managerial insights for the bus operator and highlights the decisive role of certain planning assumptions. The results of our computations reveal that the deployment of a mixed fleet can indeed lead to financial benefits. The comparison of single technology system solutions provides a further basis for decision making and demonstrates relative superiorities between different technologies
