Monash University, Institute of Transport Studies: World Transit Research (WTR)
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Unlocking the gates: Pedestrian route choice in transforming metro station paid areas into mobile public spaces
No full textRecent discussions on public transport as public space are particularly relevant in transit-oriented cities, where urban design profoundly shapes connectivity and pedestrian flow. Strategies such as destination consolidation, node manipulation, and privatized infrastructure, including walkways and transit systems, significantly influence these patterns. Assimilating ideas from nudge and practice theories, this study examines pedestrians\u27 reactions to hypothetical scenarios of opening quasi-public paid areas in metro stations to the public. Using three pairs of interconnected metro stations in Hong Kong—two linked by private paid walkways (stated preference) and one by public unpaid walkways (revealed preference)—a questionnaire survey (N=419) and discrete choice modeling were conducted. Results show adverse weather, such as rain or extreme temperatures, is a primary driver for choosing weather-protected underground paths. However, proximity and distance do not consistently predict route choice, suggesting the influence of less visible factors. For example, retail shops along a route subtly encourages usage, even for individuals with limited interest in shopping, serving as markers of convenience or familiarity. Routes with proprietary underground exits also promote underground usages. These findings reveal how deliberate design, ingrained habits and symbolic meanings collectively shape pedestrian decisions. By uncovering the social-political dynamics of pedestrian movement, this study contributes to the politics of routes discourse and offers quantitative insights for integrating micro-scale flow management in public space with broader urban planning strategies for transport infrastructure. It underscores the need to design public spaces that consider the subtle power dynamics emerging from the interplay between everyday practices and the socio-material configuration of space
Investigating Indian Commuters’ Perceived Crime Risk on Autonomous Public Buses and Ride-Pooling Services
No full textAutonomous vehicle technologies are anticipated to transform road transportation systems, promising enhanced traffic safety and efficiency across different modes, including public buses (PB) and ride-pooling services (RPS). However, in India, there is a growing security concern/fear of crime concerning conventional PB and RPS because of the recent rise in crimes committed on them. Moreover, the introduction of driverless modes of PB and RPS may further heighten commuters’ crime concerns on such services because of the absence of a driver. Thus, this study investigates the acceptance of autonomous public buses (APB) and autonomous ride-pooling services (ARPS), as well as how commuters’ characteristics influence the perceived risks of crime and victimization and their willingness to use the modes. To achieve this, a stated preference survey was designed and conducted across India. The survey resulted in 732 complete responses. The results show that socioeconomic attributes, vehicle automation, and security-related measures significantly influence commuters’ perceived fear of crime and willingness to use APB and ARPS in India. More specifically, young commuters demonstrate higher willingness to use APB and ARPS, while females exhibit lower willingness to use APB and ARPS. In addition, the presence of a security officer on these modes decreases commuters’ concerns about crime. Moreover, travel distance is positively associated with commuters’ perceived level of crime and victimization, while it has a negative relationship with their unwillingness to use APB and ARPS. APB and ARPS are yet to be introduced in India, and Indian commuters have not experienced the security concerns associated with them; thus, the results of this study can serve as the base for guideline formulation for security concerns in India. Based on the results of this study, a set of policy implications, such as female-only transit units, enhancing security measures on the automated modes, and design framework and infrastructure, were proposed. These policy implications can be instrumental in increasing the acceptability of APB and ARPS in India and other countries with similar characteristics
Research on Safety Risk Assessment of Xi\u27an Metro Operation Based on Structural Equation Model (SEM)-Matter-Element Extension Model (MEA)
No full textTo ensure the safety of Xi\u27an Metro operation and improve the level of operational safety risk management, a comprehensive evaluation model of operational safety risk of Xi\u27an Metro based on structural equation model (SEM)-matter-element extension model (MEA) was established based on 4M theory. Firstly, by analyzing both domestic and international Metro accident cases and literature, four risk factor perspectives were identified as personnel, equipment, management, and environment. Secondly, to accurately assess the safety risk of Xi\u27an Metro operation, a risk evaluation index system consisting of four primary indicators, eleven secondary indicators and forty-four observation points was established. Finally, the index weights were determined using structural equation modeling, and a comprehensive evaluation utilizing the Matter-element extension model was conducted to obtain precise safety evaluation results. The model was applied to Xi\u27an Metro Line 2, and the results indicated that the operational safety level of Xi\u27an Metro Line 2 is relatively secure. According to the evaluation results above, the findings align with the current conditions. Xi\u27an Metro operating company can utilize these results as a point of reference to propose measures that correspond to varying risks. This will effectively reduce safety risks and ensure the safe operation of Xi\u27an Metro
Exploring the nuanced correlation between built environment and the integrated travel of dockless bike-sharing and metro at origin-route-destination level
No full textAs an essential mode of last-mile connectivity for public transit, dockless bike-sharing (DBS) has garnered increasing attention in the analysis of feeder trips. However, most previous studies have primarily focused on land use attributes around stations, neglecting the influence of factors at other stages such as trip origins and route environments. To address these gaps, this study employs XGBoost and SHAP to analyze the relationship between built environment attributes and DBS-metro integrated travel at origin-route-destination level based on multi-source geographic data such as DBS trajectory data, streetscape images, and POIs. The results indicate that route-built environment factors have a stronger influence on DBS-metro integration than traditional 5D attributes. Furthermore, the influence of built environment factors is nonlinear. When the green view index is between 0.15 and 0.25, residents are attracted to using DBS to reach the metro. Moreover, this study identifies interaction effects between cycling distance and other factors. The research findings provide scientific support for operators to allocate vehicles and transportation planners to undertake community regeneration and develop sustainable transportation systems
Traffic prediction and road space optimization for the integration of dockless bike-sharing and subway
No full textThe integration of dockless bike-sharing (DBS) and subway is an effective measure to promote sustainable urban transportation. However, inaccurate traffic prediction and unreasonable road space allocation have brought a severe imbalance between supply and demand, significantly restricting its application. To address these issues, this study first employs machine learning to establish a traffic prediction model at the origin–destination level. Then, we propose a road space optimization method based on multi-source geospatial big data, aiming to compress motorized lanes and increase cycling space. Results from the Beijing case indicate: (1) The XGBoost model achieves the best prediction accuracy, with an R2 of 0.68 ± 0.04. (2) The optimization method can accurately identify high-priority areas, and compressing each motorized lane only by 0–0.41 m can achieve reasonable allocation and still meet official standards. This study will assist policymakers in identifying demand and adjusting infrastructure within the DBS-subway integration scenario, ultimately achieving sustainable transportation systems
A methodological framework for Resilience as a Service (RaaS) in multimodal urban transportation networks
No full textPublic transportation systems are experiencing an increase in commuter traffic. This increase underscores the need for resilience strategies to manage unexpected service disruptions, ensuring rapid and effective responses that minimize adverse effects on stakeholders and enhance the system’s ability to maintain essential functions and recover quickly. This study aims to explore the management of public transport disruptions through resilience as a service (RaaS) strategies, developing an optimization model to effectively allocate resources and minimize the cost for operators and passengers. The proposed model includes multiple transportation options, such as buses, taxis, and automated vans, and evaluates them as bridging alternatives to rail-disrupted services based on factors such as their availability, capacity, speed, and proximity to the disrupted station. This ensures that the most suitable vehicles are deployed to maintain service continuity. Applied to a case study in the Ile de France region (Paris and its suburbs), complemented by a microscopic simulation, the model is compared to existing solutions such as bus bridging and reserve fleets. The results highlight the model’s performance in minimizing costs and enhancing stakeholder satisfaction, optimizing transport management during disruptions
A tradable carbon credit incentive scheme based on the public-private-partnership
No full textThis paper proposes a tradable carbon credit scheme under a public-private partnership (PTCS) to reduce congestion and carbon emissions in the network, considering two travel modes with the public transit and the private cars. The PTCS involves three key entities: the traveler, the enterprise, and the government. A three-layer non-linear model is developed to formulate this problem. At the upper level, the government determines the credit scheme and the optimal subsidy to the enterprise, aiming to reduce carbon emissions, travel time, and the monetary cost. In the middle level, the costs and benefits of the enterprise are taken into account. While travelers redeem the carbon credits from the enterprise by opting for public transport, the enterprise can also gain financial benefits from green-mode travelers, including the flow benefits and the unit subsidy from the government. At the lower level, travelers choose their routes and travel modes under the given credit scheme, following the rule of the user equilibrium. We analyzed how the PTCS affects emissions and travel time and validated our findings with two numerical studies using a single OD toy network and the Sioux Falls network. Additionally, with government subsidies, the profitability of the enterprise can be increased to a great extent, achieving a triple-win situation for the enterprise, government, and travelers. This research shed light on promoting low-carbon travel, reducing emissions, and increasing the utilization rate of public transportation
Understanding park-and-ride decisions: The influence of travel information, values, and attitudes
No full textMultimodal advanced traveler information systems (MATIS) are widely regarded as essential tools for promoting sustainable mobility and supporting traffic demand management strategies, such as park-and-ride (P + R) schemes. However, in many countries, MATIS has not been fully integrated into P + R route planning, potentially limiting the effectiveness of such policies. This study aims to explore how travel information provided via MATIS influences private car drivers’ decisions to choose P + R mode, with a particular focus on the role of personal values and attitudes. The study integrates information on three routes for both “Car and subway P + R” options through a MATIS interface schematic in the form of a smartphone app. This information includes travel time, cost, subway car comfort levels, and parking spaces availability at P + R facilities. A study surveyed 229 respondents in Shanghai, China, regarding their intentions to choose P + R and collected relevant data. Based on the framework of the value-attitude-behavior (VAB) theory, an integrated choice and latent variable (ICLV) model is developed to examine the psychological and informational determinants of P + R choice, treating travel time as a random parameter to capture individual heterogeneity. The results indicate that power and security values are positively linked to comfort and pro-car attitudes, while hedonism values are negatively associated with pro-car attitudes; drivers who prioritize comfort tend to prefer driving on surface streets over elevated freeways or P + R mode, whereas individuals with stronger pro-car attitudes are more likely to choose either P + R or driving on surface streets; significant individual heterogeneity is observed in sensitivity to P + R travel time; the integration of car and P + R travel information through MATIS, particularly information on subway seat availability and parking spaces availability, appears to increase the likelihood of choosing P + R
Modelling sidewalk safety perceptions of pedestrians accessing bus stops and uncovering its role in shaping bus ridership: An empirical investigation
No full textMeasuring personal safety perception is a complex task, as it encompasses a multi-faceted array of factors. This study explores the factors influencing the perceived safety of pedestrians while accessing bus stops via sidewalks and develops a comprehensive measurement model for sidewalk safety perception. Additionally, the study investigates potential links between sidewalk safety perceptions and bus ridership by applying Structural Equation Modelling (SEM). Data were collected from 568 personal interviews conducted across various Indian cities, focusing on pedestrians’ perceptions of safety while accessing bus stops. Perceived safety was conceptualized as a latent construct, with second-order confirmatory factor analysis identifying three primary dimensions: “Safety from Sidewalk Infrastructure”, “Safety from Other User Behavior” and “Safety from Sidewalk Maintenance and Management”. These three latent constructs collectively represent the overall safety perception of sidewalks in the context of bus stop access. Further analysis found that most bus users prefer a minimum sidewalk width of 1.5–2 m and an increased minimum width of 2–4 m near bus stops. The findings offer valuable insights into the intricate factors shaping pedestrian safety perceptions and provide a robust framework for enhancing sidewalk conditions to promote safer and more accessible public transit usage
Rail-based public transportation service quality and customer satisfaction: a decade of insights and advances
No full textOver the past decade, there has been a notable increase in interest among researchers, managers, and other stakeholders in the public transportation sector regarding service quality (SQ) and customer satisfaction (CS) in the domain of railway transportation. Like for all other sectors and industries, quality of service is also of great importance to rail transportation organizations, as it influences customers’ satisfaction, passengers’ demand, investment decisions, and revenues. Given the complexity of railway SQ and its effects on CS and ridership, it is crucial to have a thorough grasp of the underlying causes, analysis methods, and improvement strategies. Therefore, this literature review provides a comprehensive overview of the current state of research on rail-based public transportation SQ, identifies the important factors influencing the SQ from articles published between 2012 and 2022, and then classifies the articles within the review period based on regional context, year of publication, sample size, the studied type of rail transport, and empirical findings. Additionally, the progress of technology and the accessibility of computer software packages have streamlined the extraction of valuable insights from passengers’ perceptions obtained through CS surveys and other data mining methods. Therefore, this review also provides insights and advances into the methodological approaches and modeling techniques adopted to analyze and evaluate SQ and CS