Monash University, Institute of Transport Studies: World Transit Research (WTR)
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Evaluating Social and Spatial Equity in Public Transport: A Case Study
No full textThe present study aims to evaluate public transport access distribution based on a framework of vertical equity principles. In this method, traffic analysis zones (TAZs) are analyzed by comparing the estimated transit demand with the existing geographical distribution of the network\u27s benefits (e.g., accessibility and mobility). The framework deploys the concept of connectivity power to measure the distribution of a transit system\u27s supply. On the other hand, demand is measured by an exhaustive index, the weighted average of four social indicators, namely the number of low-income people, the population, the households without vehicles, and the disabled in the TAZs. These weights can differ from city to city depending on culture, politics, social behavior, and costs of effective parameters such as fuel, parking, and tickets in that particular city. The framework was applied to the comprehensive transit network of Tehran, Iran. Finally, diagonal and radical lines linking the city\u27s southwest to its northeast are proposed
Metro-line expansions and local air quality in Shenzhen: Focusing on network effects
No full textWe examine the air-quality effects of urban-rail development in Shenzhen, taking a difference-in-differences approach. This study is motivated by existing mixed evidence on the rail-pollution relationship, which we associate with the dynamic nature of the relationship itself. Our results demonstrate that the relationship varies by time, depending on network density and scale. New station openings had no significant impacts on local air quality or even worsened it until the 2010 metro-line extension, when Shenzhen’s metro network density was still low, with limited spatial service coverage. However, the 2016 extension significantly abated air pollution as the network grew denser and more comprehensive. The rail-driven anti-pollution effects tended to be further strengthened with externalities arising from improved network connectivity, spilling over the effects beyond newly opened stations to preexisting ones. Also, metro stations in proximity to neighborhoods that share key characteristics in transit-oriented development tended to generate a greater anti-pollution effect
Rethinking bus ridership dynamics: Examining nonlinear effects of determinants on bus ridership changes using city-level panel data from 2010 to 2019
No full textThe decline of bus ridership is increasingly prevalent in cities in both developed and emerging economies around the world. While researchers have made many efforts to explain why choice riders switch to other transportation modes in single-city cases, why cities vary in the performance of maintaining bus ridership is still largely unknown. This study examines the changes in bus ridership among 175 medium and small-sized cities without urban rail transit from 2010 to 2019 in China and links a few determining factors to such changes by deploying fixed effects panel models and piecewise regression models. Both heterogeneity and nonlinear relationships in the dynamics of bus ridership changes are confirmed. The results demonstrate that cities at different development stages perform diversely in maintaining bus ridership, due to the variations in travel demand and travel choice preferences in those contexts. Increased private car ownership and widening income inequity both contribute to bus ridership decline while an expansion of bus fleet sizes is associated with more bus patronage. These relationships are all displayed as nonlinear formats; the effects can diminish when influencing factors reach a certain level during the growth of cities. The research outcomes may inform policymakers that cities at different development stages need to adopt context-based strategies instead of simply copying from elsewhere. Policies such as controlling private car ownership might not work equally well in cities with diversified characteristics
Marked crosswalks, station area built environments, and transit ridership: Associations between changes in 877 US TOD stations, 2010–2018
No full textTransit ridership across the US has experienced a decline over the past decade. Researchers, policy-makers and advocates have suggested that transportation and land use policies be modified to encourage transit-friendly environments. Despite the importance of studying the relationship between built environment and transit use, previous research on this topic exhibits several limitations in terms of scope, resolution and robustness of research design, due to availability of built environment and ridership data. Using a historical marked crosswalk dataset generated from Google Street View along with longitudinal station-level ridership and built environment data, this paper examines the association between changes in percent of intersections with marked crosswalks, station area built environments, and ridership in 877 TOD stations in the US between 2010 and 2018. Although we confirm ridership is decreasing overall, we find that the addition of high-visibility crosswalks was positively associated with transit ridership changes. However, transit ridership decreased in areas where the proportion of low-income workers increased, whereas percent of zero-vehicle households decreased faster than the national average. The findings suggest that efforts by land use and transportation planners to modify station areas to support higher transit ridership are necessary but likely insufficient to achieve higher ridership. Planning and policy attention to auto ownership and use, and land use-transportation coordination such as providing more affordable housing in TOD station areas, is likely to have beneficial impacts on transit ridership
Strategic dispatch of electric buses for resilience enhancement of urban energy systems
No full textThe increasing frequency of the occurrence of high impact low probability (HILP) disruptive events has posed huge threats to the power system. Therefore, power system resilience improvement has drawn world-wide attention. Electric buses (EB) are equipped with a large capacity of batteries which could provide sufficient energy and capacity values to run islanded micro-grids (MG) for hours, with a particular focus on V2G, which will deliver system resilience during extreme operational conditions. In this paper, an innovative reciprocal transport-power system coordination scheme is proposed to simultaneously mitigate the adverse impacts on both systems. By using this economic incentive-free approach, EBs are endogenously motivated to provide resilience-oriented V2G service to the power system, while increasing the transport service survivability during HILP disruptive events. Additionally, a novel EB dispatch rescheduling method considering the trade-off of both the requirement of energy supply security and transport service fulfilment is proposed. By using this method, the essential load curtailment of local MGs can be further alleviated, while the impacts of reduced charging service on transport service can also be further mitigated. Through a series of case studies, we illustrate that EBs have significant potential to provide resilience enhancement to the urban energy system based on appropriate dispatch strategies. Meanwhile, the interests of the power system and the transport system can be well reconciled by using the proposed approach during HILP disruptive events
Rapid peak seismic response prediction of two-story and three-span subway stations using deep learning method
No full textA deep learning-based rapid peak seismic response prediction model for the most common two-story and three-span subway stations is proposed in this study. The established model predicts the peak seismic responses of subway stations with a data-driven fashion and using limited information. The prediction model extracts the features of ground motions using one-dimensional convolutional neural network (1D-CNN) and then integrates the information of subway stations (i.e., the seismic fortification intensity, buried depth, and shear wave velocity) through a fully connected neural network for regression, resulting in peak seismic responses, namely the peak floor acceleration (PFA) and maximum inter-story drift ratio (MIDR). The model is trained using 19,200 samples obtained from the nonlinear time-history analyses (NLTHAs) of the designed 48 typical subway station structures. Furthermore, the external model verification was performed on 960 additional samples. For the predictions of PFA and MIDR, the coefficient of determination (R2) values are 0.967 and 0.986, respectively, and the damage states of subway stations are further evaluated, achieving an accuracy of 95.0%. These indicates that the model has good predictive performance and generalization ability. Moreover, the prediction model demonstrates a significantly higher computational efficiency compared to numerical simulation methods
Scheduling method for pairing night-shift and morning-shift duties on metro lines with complex structure
No full textScheduling the night-shift and morning-shift duties pairing plan (NMDPP) is a common process in Chinese metro crew management. Since metro crews work in a special working environment, sufficient rest is essential for them. NMDPP will affect the rest time of crews on metro lines with multiple depots and handover points. To improve the rest time of crews, this paper proposes a binary programming model to optimise the NMDPP. Moreover, a hybrid algorithm combining General Variable Neighbourhood Search (GVNS) with an Assignment Algorithm is designed to find high-quality solutions for this problem. Finally, computational experiments with both artificial data and real-life data are conducted. The results indicate that the GVNS can obtain high-quality solutions efficiently for various NMDPPs. Besides, the proposed method can effectively increase the rest time of crews compared to the practical method used in metro companies
Adaptive scheduling of mixed bus services with flexible fleet size assignment under demand uncertainty
No full textThis paper presents an optimization framework for adaptive scheduling of mixed bus services with flexible fleet size assignment under demand uncertainty. The service scheduling plans are driven by prevailing stochastic passenger demand subject to operational constraints. The optimization problem is formulated as a Markov decision process which aims to minimize passengers’ in-vehicle and waiting times, as well as the operator’s cost via use of services with different routes, schedules, and fleet sizes. To address the computational challenges, the solutions to the problem are to be calculated with use of reinforcement learning techniques. The proposed framework is implemented and tested using real-world scenarios configured from actual bus service route in Hong Kong. Experiment results reveals the benefits of the proposed bus service scheduling framework with use of flexible routes and fleet sizes in saving passengers’ and operator’s costs. This study contributes to real time transit operational planning with advanced computing and optimization techniques
Transit-oriented development and bikeability: Classifying public transport station areas in Montreal, Canada
No full textTransit-oriented development (TOD), characterized by a high and mix development around public transport stations, is gaining traction as a sustainable way to support the use of public transport for regional trips and active transport for local trips. To support integrated land use and transport planning, several TOD typologies have been developed, with a focus on land use and transport characteristics, and more recently walkability. While TOD aims to motivate the use of active modes, including cycling, assessments of bikeability have been left out of TOD typologies. To fill this gap, this study seeks to develop a bicycle-oriented TOD typology that combines indicators related to the cycling environment with traditional land use and transport indicators. Using Montreal, Canada as a case study, 14 indicators are generated to develop a TOD typology oriented on bikeability and the 114 public station areas are grouped into seven distinct clusters. The results demonstrate that the addition of bikeability criteria to the TOD typology helps discriminate the different types of stations based on their current bikeability and bikeability potential. The proposed framework enables identifying and prioritizing targeted interventions to station development. This study is of relevance to planners and researchers aiming to integrate cycling in the development of TOD
Research and innovation paving the way for climate neutrality in urban transport: Analysis of 362 cities on their journey to zero emissions
No full textThe EU Mission on Climate Neutral and Smart Cities is an ambitious initiative aiming to involve a wide range of stakeholders and deliver 100 climate-neutral and smart cities by 2030. We analysed the information submitted in the expressions of interest by 362 candidate cities. The majority of the cities’ strategies for climate neutrality include urban transport as a main sector and combine the introduction of new technologies with the promotion of public transport and active mobility. We combined the information from the EU Mission candidate cities with data from the CORDIS and TRIMIS databases, and applied a clustering algorithm to measure proximity to foci of H2020 funding. Our results suggest that preparedness for the EU Mission is correlated with research and innovation activities on transport and mobility. Horizon 2020 activities specific to transport and mobility significantly increased the likelihood of a city to be a candidate. Among the various transport technology research pathways, smart mobility appears to have a major role in the development of solutions for climate neutrality