Monash University, Institute of Transport Studies: World Transit Research (WTR)
Not a member yet
11112 research outputs found
Sort by
Computer vision for transit travel time prediction: an end-to-end framework using roadside urban imagery
No full textAccurate travel time estimation is paramount for providing transit users with reliable schedules and dependable real-time information. This work is the first to utilize roadside urban imagery to aid transit agencies and practitioners in improving travel time prediction. We propose and evaluate an end-to-end framework integrating traditional transit data sources with a roadside camera for automated image data acquisition, labeling, and model training to predict transit travel times across a segment of interest. First, we show how the General Transit Feed Specification real-time data can be utilized as an efficient activation mechanism for a roadside camera unit monitoring a segment of interest. Second, automated vehicle location data is utilized to generate ground truth labels for the acquired images based on the observed transit travel time percentiles across the camera-monitored segment during the time of image acquisition. Finally, the generated labeled image dataset is used to train and thoroughly evaluate a Vision Transformer (ViT) model to predict a discrete transit travel time range (band). The results of this exploratory study illustrate that the ViT model is able to learn image features and contents that best help it deduce the expected travel time range with an average validation accuracy ranging between 80 and 85%. We assess the interpretability of the ViT model’s predictions and showcase how this discrete travel time band prediction can subsequently improve continuous transit travel time estimation. The workflow and results presented in this study provide an end-to-end, scalable, automated, and highly efficient approach for integrating traditional transit data sources and roadside imagery to improve the estimation of transit travel duration. This work also demonstrates the added value of incorporating real-time information from computer-vision sources, which are becoming increasingly accessible and can have major implications for improving transit operations and passenger real-time information
Combined Revealed- and Stated-Preference Survey to Understand the Impact of Multi-Source Real-Time Information on Travel Mode Choice
No full textThis study presents a combined revealed preference (RP) and stated preference (SP) survey to understand travelers’ mode choices under the influence of real-time information for different activity types and trip lengths. The D-efficient method is adopted to generate SP scenarios. The empirical data for this study came from a “Survey to understand the impact of ICT on transportation choices” (SUIT; ICT = information and communication technology), conducted in July 2023 in the Washington, DC metro area and the Charlotte metro area, North Carolina (NC), USA A combined RP–SP multinomial logit and mixed logit model (MxL) capturing the error components have been estimated based on the collected data. The model results reveal that daily parking costs significantly impact individuals’ mode choices and tend to discourage driving. Furthermore, real-time information such as the availability of parking spaces at workplaces and metro stations encourages people to prefer drive and park & ride modes. Conversely, information on flash flooding alerts, road closures, and road accidents discourages people from driving, riding as auto-passengers, or taking a transportation network company (TNC) (Uber/Lyft) for trip purposes. Lastly, information on reduced waiting time and disruption plays a significant role in selecting transit and park & ride modes. The results obtained from this study can be beneficial to policymakers when assessing or designing alternative sustainable modes in the presence of real-time information. As its policy finding, the study recommends that transit disruption should be handled carefully to retain loyal customers and achieve various sustainability goals. In the event of transit disruption, alternative sustainable transportation modes should be offered to transit riders
How Does the Introduction of Shared Ride-Sourcing Services Affect Demand for Existing Modes for Non-Commuting Trips? Evidence from a Joint RP-SP Study in Metro Vancouver
No full textThe introduction and subsequent growth of ride-sourcing services have been found to affect the use of existing modes of travel. Although prior studies have explored the impacts of these services as a whole, relatively little work has been done to explore the relationship between shared ride-sourcing and existing modes of travel. Given the potential for shared ride-sourcing to help mitigate the negative externalities associated with ride-sourcing, understanding the factors influencing the use of these services and their relationship with existing modes can inform efforts to help ensure that this potential is realized. This study uses data from a web-based survey of Metro Vancouver residents to estimate a joint revealed preference–stated preference (RP–SP) model of mode choices for non-commuting trips. The model is then applied to explore the potential impacts of shared ride-sourcing on the demand for existing modes. To the authors’ knowledge, this is the first study to use a joint RP–SP model to explore the potential impacts of shared ride-sourcing on the demand for existing modes. The results suggest these services can affect the demand for exclusive ride-sourcing and attract demand from more sustainable modes such as public transit and active modes. This information can be used to help inform policies that help ensure that the benefits of shared ride-sourcing are realized. Shared ride-sourcing use can be encouraged by increasing the difference between the cost of exclusive and shared services; however, limiting the impacts of these services on the demand for more sustainable modes is also important
How does shared mobility impact metro-based urban commercial travel accessibility and Equity?
No full textThe integration of shared mobility services, such as bike-sharing and ride-hailing services, with metro systems enhances the effectiveness and convenience of urban mobility. Various transportation modes significantly impact the accessibility and equity of commercial travel for the purpose of shopping, entertainment, tourism, and catering, due to the diversity of options, destinations, and origins. This study, based on the primary urban regions of Chengdu in 2023, employs the Gaussian two-step floating catchment area model, Gini Index, and Lorenz curve to examine the effects of shared mobility on the accessibility pattern and spatial equity of commercial services. It shows that the bike-sharing-metro travel mode enhances overall commercial accessibility, whereas the ride-hailing-metro travel mode has a substantial impact on accessibility distribution. Additionally, the commercial accessibility distribution pertains to the arrangement of commercial establishments in short-distance travel, whereas it exhibits a central hub and peripheral locations for long-distance travel. While the equity of commercial services improves effectively, metro transportation remains situated at the core of the transportation mode. The creation of the metro transit-oriented development should thoroughly assess the impact of shared mobility on the station area and prioritize the equilibrium between urban commercial and residential sectors
Sustainability in transit: Assessing the economic case for electric bus adoption in the UK
No full textThe decarbonisation of the transport sector is central to the UK\u27s net-zero strategy. This study evaluates the economic viability of depot-charged single-decker electric bus fleets by integrating vehicle, crew, and charging scheduling into a total cost of ownership analysis. Our results indicate that today\u27s electrified bus fleets are roughly cost comparable to their traditional diesel counterparts. However, the cost disparity varies depending on the timetabling scenario, such that smaller operations continue to require subsidisation. We conclude that further battery price reductions and a more targeted subsidy system are critical to bridging the cost gap between the two propulsion technologies in a way which maximises taxpayers\u27 value for money
The bus-ergonomics matrix for comprehensive evaluation of buses and bus drivers’ exposure
No full textNo Abstract Availabl
Understanding passenger route choice behavior under the influence of detailed route information based on smart card data
No full textMost previous studies explored the route choice behavior of metro passengers using stated preference (SP) survey data, but the SP data are inevitably subject to endogenous and selection bias. In contrast, automated fare collection (AFC) data record travel information for nearly all passengers at boarding and alighting stations. However, due to the seamless transfer in urban rail transit, it becomes challenging to track the actual routes of passengers accurately using AFC data. Fortunately, based on a data-driven method, the chosen route and detailed travel information (e.g., segmented travel time, train load status) can be inferred with AFC data. To fill the research gaps, this paper delves into the route choice mechanism by considering the effect of detailed route information, taking Nanjing Metro, China as a case study. A Conditional Multinomial Logit model is employed to examine the effect of determinants on route choice behavior for metro passengers. The results show that the route choice model considering dynamic segmented travel time and train load status has better fit performance than the benchmark models. The sensitivity of the walking time is found to be similar to that of in-vehicle time for metro passengers, but a stronger distaste for waiting time or queuing time is observed. Besides, the crowding-related attributes are negative for route choice, but Nanjing Metro passengers present a higher tolerance for crowding compared with passengers in developed countries. These findings provide an accurate and comprehensive insight into the route choice behavior of metro passengers
Joint optimization of fixed route bus networks and complementary paratransit service areas
No full textAn optimization-based approach is proposed for the joint design of fixed-route bus networks and the service areas of complementary paratransit services. Complementary paratransit systems provide transportation to people with disabilities within a service area (PSA) that is traditionally designed as a function of the spatial layout of a fixed-route bus network. The proposed problem accounts for effectiveness and equity objectives for the bus and paratransit services. A constraint on the minimum extension PSAs is considered, which is of practical interest given the coverage regulations faced by transit agencies in some jurisdictions. A two-step procedure is proposed to find solutions to the design problem. In the first step, bus route network designs are generated, along with their minimum PSAs. In the second step, a genetic algorithm improves upon the PSAs generated in the first step. Simulation tests were performed to illustrate the application of the proposed methodology
Exploring the determinants of demand-responsive transit acceptance in China
No full textDemand-responsive transit (DRT) is gaining prominence in urban public transportation research, especially in rapidly modernizing transit systems of developing countries such as China. Despite DRT\u27s advantages, challenges such as low market demand and utilization persist. To ensure DRT\u27s successful integration and promotion, understanding public acceptance and its determinants is vital. This study expands the technology acceptance model (TAM) by incorporating trust, personal innovativeness, subjective norms, service quality, and perceived risk as pivotal factors influencing DRT acceptance. An online survey was conducted where a total of 627 valid responses were collected via snowball sampling. Structural equation modeling and path analysis were employed to dissect the factors influencing DRT adoption intentions. The results reveal that the proposed extended model accounts for 78.1% of the variance in DRT usage intentions. Trust exerts the most substantial influence on the usage intention of DRT, directly shaping user intentions and indirectly influencing them through various associated constructs. Service quality indirectly impacts intentions through perceived usefulness and personal innovativeness. Personal innovativeness and subjective norms have both direct and indirect impacts, whereas perceived risk solely indirectly affects intentions negatively. The research highlights the critical role of trust and service quality in shaping public DRT intentions and the importance of personal innovativeness and subjective norms in driving adoption. It also emphasizes the necessity of addressing perceived risk for acceptance. Theoretical and practical implications guide policymakers and operators in enhancing DRT services in China\u27s evolving transit environment
Strategic sustainability assessment of rideshare and automated vehicles using the analytical hierarchy process (AHP)
No full textNew mobility concepts such as Mobility as a Service (MaaS) are emerging as potential solutions to move people more sustainably in an increasingly urbanized world. Planning for this multi-modal mobility requires a whole system approach (STEEP - social, technical, economic, environmental, and political) to evaluate alternative future scenarios and address varied stakeholder concerns. A strategic planning tool was selected that can model alternative scenarios for how urban mobility systems may evolve over time. A sustainable mobility scorecard was defined, comprised of individual metrics generated from the tool\u27s output. The Analytical Hierarchy Process (AHP) was selected and applied to generate stakeholder weightings from an online survey of U.S. transportation planning professionals. Those weightings were applied to the scorecard to demonstrate their influence on alternative planning outcomes. Results include the scorecard metrics assessed with the greatest relative importance to sustainability; increases in no car ownership, increases in the transit/walk/bike mode share especially in lower income populations, maintaining the average peak traffic speed (actual/posted), and reducing cars per capita. The resulting weighted scorecard, part of a strategic assessment methodology for mobility sustainability (SAMMS), is then used to evaluate four future planning scenarios with contrasting trends (socio-demographics, travel behavior, employment, land use, transport supply) for the greatest overall sustainable mobility outcome