Monash University, Institute of Transport Studies: World Transit Research (WTR)
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Effect of beliefs and attitudes on public transport users’ choices. The moderating role of perceived intermodal connectivity
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The impact of heterogeneous accessibility to metro stations on land use changes in a bike-sharing context
No full textThe integration of urban rail transit and land use has been adopted as a crucial approach to fostering compact development in cities. Proximity to rail transit stations can increase the probability of land use changes, while few studies have analyzed the spatial heterogeneity of the impact of rail transit on land use changes. This study proposes a distance-decay function to delineate the spatial heterogeneity of metro station accessibility using bike-sharing data and examines the impact of metro stations accessibility on land use changes. Jiading New Town in Shanghai, China, is selected as our study case. By utilizing a non-linear distance-decay function to delineate metro station accessibility as a driving factor for training neural networks in a vector-based cellular automata model, an improvement in simulation accuracy is achieved compared to the model using a linear distance-decay function. This study could help establish more efficient strategies for promoting integrated development of rail transit and land use. The significance of this study lies in the generality of the optimized land use vector-based cellular automata model considering the spatial heterogeneity of metro station accessibility, which could also be applied to other situations, such as considering the accessibility to bus stops and road networks
Bayesian multivariate spatiotemporal statistical modeling of bus and taxi ridership
No full textStatistical modeling of ridership over both space and time provides valuable insights on transportation planning and policies. Existing spatiotemporal studies, however, predominantly focus on analyzing a single type rather than multiple types of ridership, thus cannot leverage the correlation between different types of ridership. This study proposes a Bayesian multivariate spatiotemporal statistical model to jointly analyze multiple ridership over time. Specifically, the model accounts for correlation between multiple ridership based on different assumptions of space-time interactions (i.e., departures from the main spatial and temporal patterns) between different types of ridership as well as if covariates are included in the model. Using hourly bus and taxi ridership in the city of Wuhu, China as an example, the case study indicates that accounting for the correlation between the space-time interactions of each ridership, beyond the correlation between the main spatial patterns of the two ridership, further improves the statistical inferences of ridership modeling. In addition, the proposed approach enables the detection of spatial and spatiotemporal hotspots of each ridership as well as bus-taxi ratio hotspots using posterior probabilities. It also supports visual inspections regarding how the inclusion of covariates explains these hotspots. The proposed approach not only advances multivariate spatiotemporal statistical modeling of ridership, but can also provide useful insights on space- and time-specific transport policies at a granular resolution
Agent-Based Modeling for Sustainable Urban Passenger Vehicle Mobility: A Case of Tehran
No full textIn response to escalating congestion and deteriorating air quality in urban centers worldwide, exacerbated by overburdened transportation systems, there is an urgent need for accurate traffic forecasting and effective sustainable urban development strategies. This study employs agent-based modeling through four distinctive scenarios for Tehran, I. R. Iran. A synthetic population is meticulously crafted using simulated annealing, enabling the emulation of daily commuting patterns. Results show that by bolstering cycling infrastructure and enhancing public transportation services, reliance on private cars is reduced up to 46%. The introduction of flexible working hours reduces the traffic volumes during peak traffic hours by 47% and significantly altering the daily distances traveled by personal cars, as evidenced by a 1:6 ratio in car volume increase between scenarios emphasizing flexible working hours and those with more conventional traffic patterns. The results provide powerful insights for decisionmakers to manage the traffic especially in high polluted air conditions
Transmuting battery-powered buses: State-of-charge scheduling cooperative with battery and charger capacity optimization
No full textTransitioning toward non-polluted public transportation systems is crucial for sustainability. Although declining battery costs have led to a greater utilization of battery-powered electric buses (BEBs), challenges persist owing to the high cost of chargers and battery energy limitations, which require efficient solutions. Therefore, this study proposed a novel offline state-of-charge scheduling method that focuses on optimizing battery and charger capacities. To make this study applicable to any city, a precise bus dynamic model was developed, and all evaluations were conducted using data commonly available in the cities. To validate the optimization, a sensitivity analysis was conducted to represent the effects of the factors involved. Moreover, to investigate the differences between the utility service and depot owner perspectives, the city’s and synthetic electricity tariffs were employed for scheduling, which differ in covering the city’s daily load profile valleys. This measure is crucial when the BEB demand is not considered in generation
Inclusive mobility hubs: An in-depth exploration of the requirements of disadvantaged groups
No full textMobility hubs are becoming increasingly relevant in urban transport systems because they have the potential to enhance sustainability and decrease transport disadvantages. However, the literature has not yet identified the use that disadvantaged groups make of mobility hubs, nor has it thoroughly revealed their requirements for using them without difficulties. As a means to fill this knowledge gap, this qualitative study applied the Capabilities Approach to thoroughly investigate the requirements of disadvantaged groups concerning the use of mobility hubs. The data was obtained through 45 semi-structured interviews and four focus groups with local experts and potential or current users of mobility hubs in four European regions: Brussels, Munich, Rotterdam-The Hague and Vienna. As a result, eight main categories of requirements and their prevalence among disadvantaged groups were identified. The findings contain several recommendations to support decision-makers and practitioners in developing inclusive mobility hubs
Reducing automobile commuting in inner-city and suburban: Integrating land-use and management intervention
No full textFew studies have examined how demand-side management measures, alone or in conjunction with built environment interventions, affect car owners’ automobile commuting choices in developing cities. Additionally, most studies overlook the difference between inner-cities and suburbs. Applying extreme gradient boosting decision trees and shapley method to the 2020 Wuhan travel survey data, this study addresses these gaps. Transportation management measures and the built environment individually exert a significant impact on car commuting, while jointly exhibiting synergistic effects on car commuting. Meanwhile, most of these effects are nonlinear and exhibit different properties in the inner-city and suburbs. In the inner-city, proximity to central development and population densification can reduce automobile commuting. Parking fees and transit allowances enhance these benefits. For suburbs, job densification and mixed development are more effective, but have limited impact on the inner city. This study demonstrated that integrating built environment interventions with management measures enhances policy effectiveness
In-Depth Appraisal of Bus Transport Services for Sustainability Performance: A Cost–Benefit Analysis Approach
No full textPublic transport is arguably considered the backbone of today’s urban mobility ecosystem and is generally regarded as an important element of the sustainable mobility paradigm. As systems, they comprise vast societal investment owing to the infrastructures and operations required to provide the designated service. As projects, public transport systems have financial, societal, and environmental impacts that ought to be assessed through the scope of sustainability. Through sustainability, future generations’ financial, societal, and environmental needs are not compromised to meet the present generation’s needs. Thus, sustainability assessments can assist decision makers in perceiving the impacts and implications of an existing or under-consideration system on society and deciding on corrective actions. For the case of public transport systems, such assessments can assist in evaluating the expenditure distribution of the system and suggest actions that could maximize welfare gains under financial, social, and environmental criteria. Within this scope, the current paper proposes a methodological framework for unraveling transport systems’ sustainability to reveal their spatiotemporal dependencies. The study proposes a cost–benefit analysis framework where a public transport system is segmented and assessed into three levels: stops, lines, and administrative areas. Stop and line levels incorporate essential characteristics allowing their independent evaluation. The assessment of administrative areas aggregates characteristics from previous levels, spatially distributing the public transport system’s evaluation. By incorporating additional sociodemographic data, the administrative area level’s assessment links the evaluated transport system to societal characteristics, enhancing the decision maker’s perspective. The framework is showcased with Nicosia’s public bus transport system
Distributed virtual formation control for railway trains with nonlinear dynamics and collision avoidance constraints
No full textTo improve the model accuracy and control efficiency for the movements of a virtual formation, this paper investigates distributed optimal control for the virtual formation control system in railways. Adopting the relative distance braking mode, a coupled optimal control problem with nonlinear train dynamics and constraints regarding collision avoidance and jerk is formulated for the virtual formation. To handle the non-convex constrained problem efficiently, a distributed augmented Lagrangian based alternating direction inexact newton (ALADIN) method under the model predictive control (MPC) framework is developed. For the execution of the distributed computational process, the copied variables are introduced to reformulate the original coupled problem in an objective separable form. By exploiting the problem separability, the ALADIN method decomposes the reformulation into a coordinated quadratic programming problem of small-scale and several local nonlinear programming problems that can be calculated in parallel, thereby facilitating real-time control and relieving communication burden. Numerical experiments on a metro line are carried out to verify the effectiveness of the proposed model and method. Experimental results demonstrate that high-performance tracking control for virtually coupled train units can be achieved in real time
Public transportation-based crowd-shipping initiatives: Are users willing to participate? Why not?
No full textAn emerging stream of Crowd-Shipping (CS) solutions focuses on existing momentum in Public Transportation (PT) to ship viable delivery packages by PT passengers. Few studies have explored the package delivery acceptance behavior of passengers engaged in PT-based CS initiatives while passengers’ behavioral intention to participate (i.e., engage) is not studied. It is requisite that newly introduced CS platforms explore their potential crowdshippers’ behavior on intention to participate and set efficient marketing strategies. Given survey data collected from 2208 PT passengers in Sydney metropolitan area, this study explores the intention of PT passengers as crowd-shippers to participate in PT-based CS initiatives, as well as prohibiting factors in way of participation. Accordingly, a binominal logit model is developed whereby the variables impacting the intention to participate are identified. Then, using an inductive thematic analysis, 917 reasons (text responses) for not participating are scrutinized, and the prohibiting factors are identified and categorized. Considering demographic and socio-economic characteristics of the respondents, the study reveals to what degree passengers with different characteristics are sensitive to prohibiting factors. This research provides several practical insights that can assist in successfully defining, launching, and advertising a new PT-based CS initiative. As a key finding, it is observed that women, full-time employees, elderly, retirees, and low-income PT passengers hardly participate, while the youth, individuals with a positive attitude towards sustainable freight initiatives, and those who experienced working with parcel lockers would participate with a higher probability. Moreover, it is observed that factors relating to time availability/flexibility and physical health condition/importance of passengers are much more important than the compensation level for passengers to accept to participate in PT-based CS initiatives