Monash University, Institute of Transport Studies: World Transit Research (WTR)
Not a member yet
11112 research outputs found
Sort by
Stochastic game-based cross-layer defense scheme for jamming-resistant virtual coupled train sets
No full textThe railway operation concept of Virtually Coupled Train Sets (VCTS) allows for shorter headways between units in a train convoy, enhancing the current capacity limit imposed by existing Communication-Based Train Control (CBTC) systems by enabling units to operate safely at shorter distances. However, due to the use of open Train-to-Train (T2T) wireless communication through Long-Terms Evolution for Metro (LTE-M), VCTS is vulnerable to various cyber-attacks, including jamming attacks, which have largely been overlooked. To address this issue, this paper proposes a Stochastic Game-Based Cross-Layer Defense (SGCD) scheme. This scheme aims to enhance the safety and stability of VCTS in both the physical and cyber layers, in the presence of uncertain communication failures caused by jamming attacks. This proposed scheme formulates the defense approach and the particularly jamming actions as a stochastic game. A cross-layer control approach is employed to mitigate the impact of jamming attacks on the train convoy. The performance of this cross-layer control is mapped to the frequency domain and quantified using the norm to ensure the stability and safety of the VCTS system. Extensive simulation results demonstrate that the SGCD scheme can effectively ensure the running stability and safety of a train convoy under random jamming attacks in the VCTS. The proposed defense mechanism can enhance the security and reliability of the VCTS system, thereby enabling safer and more efficient train operations with shorter headways
Passenger Route and Departure Time Guidance Under Disruptions in Oversaturated Urban Rail Transit Networks
No full textThe urban rail transit (URT) system attracts many commuters with its punctuality and convenience. However, it is vulnerable to disruptions caused by factors such as extreme weather and temporary equipment failures, which greatly affect passengers’ journeys and diminish the system’s service quality. In this study, we propose targeted travel guidance for passengers at different space–time locations by devising passenger rescheduling strategies during disruptions. This guidance not only offers insights into route changes but also provides practical recommendations for delaying departure times when required. We present a novel three-feature four-group passenger classification principle, integrating temporal, spatial, and spatiotemporal features to classify passengers in disrupted URT networks. This approach results in the creation of four distinct solution spaces based on passenger groups. A mixed integer programming model is built based on individual level considering the first-in-first-out rule in oversaturated networks. In addition, we present a two-stage solution approach for handling the complex issues in large-scale networks. Experimental results from both small-scale artificial networks and the real-world Beijing URT network validate the efficacy of our proposed passenger rescheduling strategies in mitigating disruptions. Specifically, when compared to scenarios with no travel guidance during disruptions, our strategies achieve a substantial reduction in total passenger travel times by 29.7% and 50.9%, respectively, underscoring the effectiveness in managing unexpected disruptions
Composite Accessibility Index: A Novel and Holistic Measure for Evaluating Transit Accessibility
No full textThe accessibility of public transport is a vital factor for the overall success of transit operations. It determines whether people choose to use and rely on public transport by assessing the ease of accessing opportunities. Accessibility, as a measure of the system’s performance, encompasses various travel segments and can be evaluated from different perspectives. Evaluating transit accessibility in data-constrained environments, particularly in developing countries, requires an optimal framework. The present study proposed a framework by modifying available accessibility measurement indices and trying to encompass all affecting variables in a single composite index. The integrated transit system comprising the bus rapid transit system and city bus in Surat city, India, is selected to demonstrate the proposed framework. The results of the ranked-based correlation coefficient test exhibit the comprehensive assessment capabilities of the proposed composite index in evaluating transit performance. Surat city’s transit network shows better coverage based on the gravity model theory, that is, moderate performance in local coverage offered capacity per population. However, it exhibits poor accessibility with respect to reaching destinations, resulting in below-average transit accessibility. Except for the city center and eastern part, 65% of the city area experiences inadequate accessibility of public transport. These findings align with the city’s low transit mode share of 2.5% and stagnant daily ridership of 0.25–0.28 million passengers in the last half decade. The composite index map serves as a planning tool for optimizing the utilization of available resources and guiding future policy implementations
Tourists vs. residents: Nested logit analysis of mode choices for environmental sustainability
No full textUrban short-distance transportation is crucial for environmental sustainability in metropolitan areas. Although mode choice behavioral differences between tourists and residents have been noted, a comprehensive investigation is lacking. This study addresses this gap using discrete choice modeling to compare mode preferences between tourists and residents. Results reveal that residents emphasize time-saving, while tourists prioritize service quality and convenience. Employed residents attach extra importance to in-vehicle time, and tourists have low tolerance for crowded conditions. Gender impacts only residents’ choices, whereas reduced transfers enhance public transport’s appeal to tourists. Income and environmental consciousness affect both groups, while trip-related factors such as travel purpose and stay duration shape tourists’ choices. These findings offer novel insights into group-specific determinants of mode choice and inform targeted strategies to promote low-carbon public transportation, including tailored pricing incentives, infrastructure improvements, and AI-powered real-time transport and parking applications, thereby facilitating sustainable development in transportation, tourism, and environment
Changes in mode use after residential relocation: Attitudes and the built environment
No full textAfter changes in the spatial environment induced by residential relocations, mode choice is prone to reconsideration. This study analyzes a panel dataset of 661 movers in Germany who were questioned before and after a move. We aim to determine the relationships between changes in the built environment, in travel attitudes, and in mode choice, accounting for possibly bi-directional relationships. Structural equation models are estimated for four different modes (car, bike, walking, and public transport). We observe that changes in the built environment impact mode choice: After relocating to more urban locations, active mode use increases while car and – unexpectedly – public transport use decrease. Travel attitudes do not directly influence residential location choice, only indirectly via search preferences. There is limited evidence for residential determination as attitudes towards most travel modes remain stable. We only observe changes in walking attitudes in response to changes in the built environment
Toward greener transit: Carbon-efficient density thresholds for public transit vs. private vehicles
No full textDespite its potential as a sustainable transportation mode, public transit in many low-density urban and suburban areas in the U.S often generates more CO2 emissions per passenger-mile than privately operated vehicles (POVs), primarily due to low ridership and passenger loads. Using Gradient Boosting Decision Trees (GBDT) and spline regression models, this study investigates the non-linear relationship between population density and the relative carbon efficiency of transit compared to POVs across the 136 largest U.S. urban areas. This study found that the minimum density required for public transit to be more carbon-efficient than driving, while controlling for other factors, is around the lowest 10th percentile of population-weighted density (PWD)—approximately 3.4 persons per acre. Further, a critical density threshold was identified at around the 80th percentile of PWD, about 8.6 persons per acre, beyond which the positive impact of population density on transit’s carbon efficiency significantly shifts up
Who Gets What? A user perspective on initial credit allocation in Tradable Mobility Credit Schemes
No full textIn Tradable Credit Schemes (TCS), policymakers might align the total quantity of credits in the system with specific climate, air pollution, or traffic reduction goals. To achieve these objectives, the total credits issued are typically set below actual travel demand, thereby encouraging a mode shift from private cars to more sustainable alternatives, as well as promoting trip avoidance or postponement. A central aspect of TCS is, therefore, determining how credits are allocated to individuals—and, specifically, whether all users should receive the same credit budget. However, the literature offers limited research on the strategies, central elements, and user preferences related to the initial credit allocation. In this paper, we review the building blocks of the initial credit allocation in Tradable Mobility Credit Schemes, namely: (a) the eligible receivers, (b) the credit measurement unit, (c) the validity period and transferability of credits, and (d) the allocation method itself. Additionally, we present empirical findings on public support for non-uniform credit allocation strategies and preferences regarding credit compensation for various individual attributes. Our survey results show that approximately 70% of respondents endorse the non-uniform allocation of credits. Support was particularly high among individuals with limited public transport accessibility, lower incomes, and women. Besides, respondents identified mobility impairment, care work responsibilities, and poor public transport accessibility as the most critical factors that should influence the credit budget an individual receives. This paper provides policymakers with an overview of initial credit allocation strategies and practical insights to enhance public acceptance of TCS designs
Parallel railways and urban sustainability: a comprehensive bayesian evaluation of infrastructure impacts and land use
No full textThis study primarily investigates the issues arising from the construction of new railways parallel to existing ones, focusing on the impact on urban spatial layout, coordinated development of urban land use, and the stability of railway infrastructure. It proposes the Bayesian sustainable intelligent framework for enhancing parallel railway reliability (BSIF-PRR), which integrates system reliability analysis, a two-dimensional finite element method (FEM), and a Bayesian neural network (BNN) surrogate model to assess the impact of new railway construction on existing infrastructure. A FEM model is developed for structures adjacent to the existing railway and simulated under various operational scenarios. The BNN model then predicts structural stability limit states, providing critical stability control indices. The BSIF-PRR has been implemented in two practical situations. One was in the design of a new railway, where the indices derived from the model were integrated into the alignment design. This guided a multi-objective optimization process, aiming to enhance system performance while focusing on optimizing land use, minimizing house demolition, and reducing construction costs. Another one was the application of two existing parallel railways to verify the practicality of its predictive indicators. Additionally, the study provides suggestions and strategies for the sustainable development of urban paralleled railways
Model for electrification of urban public transport lines with supercapacitor buses: A case study of Belgrade
No full textIn this paper, a cost-oriented model for implementing e-buses equipped with supercapacitors in urban public transport was developed and tested. This model simultaneously determines the optimal locations for fast charger installation, their power ratings, capacity of supercapacitors, e-bus charging schedules in operation, and the amount of electricity transmitted to e-buses by chargers. IGNITE simulation software was used for modeling and simulating e-bus operation. The model was tested and validated with actual data from four bus lines in Belgrade (Serbia), presently with diesel-powered standard buses in operation, resulting in cost efficient solutions. Comparative analysis of implementation costs of e-buses with supercapacitors and LFP batteries was conducted. A sensitivity analysis of solutions was performed using both actual energy consumption data (based on recorded speed data, terrain configuration, and auxiliaries consumption impact), and average energy consumption. The sensitivity analysis demonstrated that input data quality significantly affects obtained solutions, as well as the sustainability and functionality of the urban public transport system. The impact of maximum e-bus charging times at bus stops and termini on passenger comfort was also considered, along with the impact of energy savings on the total implementation costs of supercapacitor e-buses
Utilizing street view images to estimate solar energy potential for photovoltaic-powered buses
No full textPhotovoltaic-powered buses offer a promising solution for reducing fossil fuel dependency and alleviating pressure on power grids. This study evaluates the solar energy potential in downtown Beijing by utilizing street view images, meteorological data, and advanced analytical techniques, including deep learning and the radiative transfer model. The analysis incorporates spatial characteristics, seasonal variations, and the impact of weather conditions on solar energy availability. Key findings include: (1) downtown Beijing exhibits substantial solar energy potential, with seasonal and spatial variations. Solar energy levels are highest on east-west oriented streets during summer, reaching up to 15.0 MJ/m2/day, while winter levels can drop to as low as 6.0 MJ/m2/day in densely built areas; (2) photovoltaic-powered buses can generate up to 100 kWh per day, enabling annual travel of 88,500 km under clear skies and 64,300 km under cloudy conditions, while reducing carbon emissions by 88.4 tons and 64.3 tons, respectively; (3) integrating photovoltaic systems into public transportation offers significant economic and environmental benefits, enhancing energy security and promoting sustainability. These results demonstrate the feasibility and advantages of incorporating photovoltaic technology into urban public transit, contributing to the development of sustainable cities by reducing carbon emissions and improving energy efficiency