Monash University, Institute of Transport Studies: World Transit Research (WTR)
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Views of emerging sustainability leaders on the future of Transport: A Q study in a Taiwan tertiary education program
No full textAs we approach critical milestones such as the year 2050, by which time the global community aims to achieve zero carbon emissions, the decisions we make today concerning transportation infrastructure become increasingly influential. This research seeks to broaden the dialogue beyond the traditional domain of current policymakers and transport planners by incorporating the perspectives of the generation that will inherit and live with the long-term impacts of today’s decisions. This study investigates the perspectives of learners in a unique sustainability-focused undergraduate program in Taiwan regarding transportation’s future in a world impacted by anthropogenic climate change. Considering their potential as future sustainability professionals and leaders, understanding their views can offer insights for both educational and transportation policy. Using Q methodology, this research captures a range of viewpoints. The five distinct perspectives include the advocates of collective responsibility and tech-optimists, who hold positive views towards collective action and technological advancements respectively. The pragmatic solitaries and private transport advocates, who prioritize personal comfort and express skepticism about environmental targets. The public transport advocates, meanwhile, favor shared forms of transport and see a crucial role for the government in carbon reduction efforts. The study’s significance lies in its emphasis on a previously underexplored demographic within the unique context of Taiwan, revealing their perspectives on a transportation future shaped by climate change by using Q methodology, and its implications for policy derived from the findings
Analysis of the relationships among infrastructure, operation, safety, and environment aspects that influence public transport users: Case study of university small and medium sized cities in Brazil
No full textUniversity cities record large numbers of daily trips to campuses, resulting in significant impacts on urban traffic. Public transport services are crucial for meeting this demand, especially for students, who form the most abundant group and are typically captive users of this mode. However, various factors including infrastructure, operation, safety, and environment influence the perception of public transport users regarding their daily trips. Therefore, this case study of a Brazilian university examines the relationships among these factors, using a structural equation modeling approach with multiple indicators and multiple causes (SEM-MIMIC), based on perception data from public transport users within the academic community. The results indicate the importance of incorporating safety perception into travel satisfaction models and considering the interaction between infrastructure and public transport operation attributes. It is also crucial to account for the attributes of the environment in which university students travel. Furthermore, the findings show that user perceptions are influenced by factors such as gender, vehicle availability, total travel time, and the adequacy of the service to cope with specific needs. Based on these findings, urban mobility and university managers can plan measures to effectively enhance the attractiveness of public transport and encourage its usage among members of the academic community
Introducing electric buses in urban areas: Effects on welfare, pricing, frequency, and public subsidies
No full textWe study optimal degree of bus system electrification for Stockholm’s longest high-frequency bus line. We evaluate the welfare effects of opportunity and depot charging fleet configurations with batteries charged during dwell times at terminal stations or during the operating pause in the bus depot, respectively. Electric buses (e-buses) significantly reduce carbon and health damaging emissions of transit services. However, e-buses are presently not welfare improving, because their lower external costs do not offset the higher supply costs (e.g., capital cost of charging infrastructures and batteries). Instead, we find that optimising bus fares and frequencies and road pricing is more effective in improving social welfare and carbon emissions. E-buses significantly reduce surplus of bus operators, which thus are reluctant to adopt these technologies without direct public support. Sensitivity analysis shows that: (i) technological developments to substantially reduce capital costs can make e-buses perform well from a social welfare perspective; (ii) efficiency gains obtained in the operation of the service, e.g., by optimizing on-board conditioning systems, but also bus routing and driving style, can have a greater impact on the cost performance of e-bus fleet configurations than simply reducing capital costs. An argument for e-buses is the efforts in coordinating a transition to electrified vehicles, aiming at reducing the risk of futile investments in charging infrastructure
Navigating the transit network: Understanding riders’ information seeking behavior using trip planning data
No full textRelevant and timely provision of transit information advises travelers of the route options available to them, allows riders to plan the timing of their trips, and helps mitigate the adverse impacts of unexpected disruptions. This in turn can improve the experience and retention of current riders and help attract new ones. While previous studies have relied primarily on data collected from surveys to understand people’s use of transit information services, this paper uses backend data from Transit, a multimodal trip planner smartphone application (app), to analyze usage patterns in Calgary over the span of six months. A clustering analysis was initially performed to gain an understanding of trip search characteristics. The results show that most searches were made for short distanced trips. Additionally, panel data models were estimated to investigate the relationship between search frequency and transit service characteristics, temporal factors, built environment, weather and sociodemographic attributes. The model results reveal that people seek out transit information the most during times of uncertainty, as poor reliability and service disruptions were shown to increase itinerary searches markedly. Furthermore, there was found to be a significant increase in searches after the network was restructured and three bus rapid transit (BRT) lines were introduced. These findings can help agencies determine the best way to deliver information to people and gain insights into travel behavior
Synergizing shared micromobility and public transit towards an equitable multimodal transportation network
No full textThis paper assesses the equity impacts of shared micromobility and investigates regulatory policies that improve transport equity and promote synergy between public transit and shared micromobility. We consider a multimodal transportation network, where a micromobility platform deploys docking stations and operates a fleet of micromobility vehicles to provide shared micromobility services and a public transit agency offers transit services over a transportation network. A market equilibrium model is developed to capture the intimate interactions among access and egress times of shared micromobility services, waiting times of transit services, the spatial distribution of docking stations, passenger demand, platform pricing and fleet sizing, vehicle repositioning and the micromobility platform profit. The platform decision problem is cast as a high-dimensional non-convex program. A solution method is proposed to efficiently compute the solution through problem reformulation and dimensionality reduction. Based on the proposed framework, we evaluate spatial equity in transport accessibility using the Gini index, and find that although shared micromobility improves overall transport accessibility, the benefits are not fairly distributed across different geographic zones, which leads to enlarged spatial inequity gaps after introducing shared micromobility. To promote transport equity, we investigate three policy directions: (a) to impose a vehicle density floor on shared micromobility; (b) to offer a subsidy on shared micromobility rides for first/last-mile connections; and (c) to promote collaboration between public transit and shared micromobility. We show that different regulatory policies have advantages and limitations. The minimum vehicle density requirement can simultaneously improve spatial equity and passengers’ surplus, but has limited equity improvements. In contrast, the subsidy on bundled services could significantly mitigate spatial inequity, but it hurts passengers and the platform profit. Compared to the other two policies, the transit-micromobility collaboration can lead to higher equity improvement, higher passenger surplus, while offering a guarantee on the platform profit, which turns out to be the most cost-effective approach. These insights are validated through realistic numerical studies for San Francisco
Understanding travel mode choice through the lens of COVID-19: a systematic review of pandemic commuters
No full textThe COVID-19 pandemic disrupted travel behaviours for very large numbers of people including those who shifted to teleworking and those without the option to work from home. While there is much valuable transport research that has examined the former category, it is still unknown how certain people such as health sector employees and delivery drivers changed their physical commuting in transport contexts that were radically different from those existing normally in urban areas. Based on a systematic review of 36 scientific publications on commuting during pandemic, this study pursues a dual objective. First, by examining the interrelated institutional, physical, and socio-psychological processes that supported or hindered low-carbon transport the study revealed that (A) public transport (PT) reduced service levels and concerns related to COVID were positively associated with substantial shifts away from PT towards car and active travel; (B) this positive association was found to be even stronger in the existence of pre-pandemic habit of car use for commute and strong negative emotions like fear triggered by environmental changes and health risks. Second, by synthesising the key findings from the literature, this study provides significant implications for how mode choice is modelled through the Theory of Planned Behavior and Norm Activation Model. By questioning whether the pandemic commuters had a “normal” set of travel mode alternatives to choose from, the study draws attention to the nuances of mode “choice” versus mode “use” and moves beyond the assumption that commuting always results from individuals making choices. It also argues that the role of (negative) emotions along with the importance of proximity to, or separation from, other bodies on how people commute should be considered in future research. Finally, the crucial role of COVID-19 in changing travel-related norms and the resulting long-term implications for policy interventions require further investigation by future research
Train stations and house prices: a local perspective
No full textOpening a new train station is considered a way to generate amenity in a neighborhood. However, as train lines extend from a central city to suburbs and remote places, train stations may generate disamenity depending on the local context. This study examines the externality of stations from a house valuation perspective. A mixed-effects model is employed to capture the varying relationship between house prices and distance to a nearby station. The results show that this relationship significantly varies by county, which leads to a house price premium in some counties and price discount in others. This study attributes the price discount (disamenity) to low ridership, seasonality of ridership, passenger traits, and long distance from a central city. The study results are expected to provide policymakers with balanced insights on establishing a new station so that train stations can serve as a local amenity, not a harmful facility in the neighborhood
Smartphone mobility assistants. A lever to guide route choice preferences in mass transit?
No full textThe regulation of passenger congestion in mass transit is a persistent issue that requires ingenious and cost-effective solutions to ensure that related operations run at optimum capacity. Mass transit operators may implement Public Transport Demand Management (PTDM) strategies like cognitive levers to tackle this issue by targeting passengers’ behaviour during the route planning that precedes travel in mass transit. In this regard, multiple experimental studies in cognitive psychology and sciences have shown that transit maps can be used to guide passengers’ route choice preferences in mass transit.
A route choice experiment was conducted to examine the potential of smartphone mobility assistants as a tool to guide mass transit users’ away from the fastest options that tend to be predominantly preferred. 582 participants took part in an online study where they engaged in a route selection task by indicating their route choices in the Île-de-France mass transit system. We measured how participants’ preferences for the fastest route varied depending on the visual format in which routes were presented (on a transit map, on a timeline or listed briefly as per current trends), the presence of conflicting visuo-spatial information on the transit map (fastest choice = shortest vs. longest choice) and the level of comfort (availability of simple transfers and/or less congested routes).
The main results suggest the existence of two levers than can be implemented in smartphone mobility assistants to manage passenger congestion in mass transit: (1) a perceptive heuristic whereby passengers presented with a transit map manifest a preference for the route presented as the shortest on the map and (2) the possibility to sway a proportion of passengers away from the choice of the fastest route by presenting information about the comfort levels of alternative options
Predicting land use change around railway stations: An enhanced CA-Markov model
No full textPredicting land use change around railway stations is crucial for facilitating the coordinated development of transport and land use. Previous studies have seldom focused on simulating and predicting small-scale land use changes at a railway station. Therefore, this study employs an enhanced Cellular Automata-Markov (CA-Markov) model, aiming to achieve simulations and predictions with heightened precision. Firstly, two additional driving factors, namely accessibility to railway stations and the kernel density of points of interest (POIs), are incorporated into the CA-Markov model. Secondly, the validation of the enhanced model is achieved through simulating land use changes around Dujiangyan Station. Finally, this model is applied to predict land use around Mianzhu South Station in 2026, and optimization strategies for railway station areas are proposed. The results indicate an 83.43-hectare reduction in farmland area, accompanied by a moderate increase in 35.8 hectares of forest land and 41.52 hectares of residential land. This enhanced model provides valuable technical support for strategic planning in railway station areas
Exploring the relationship between public transport use and COVID-19 infection: A survey data analysis in Madrid Region
No full textThe COVID-19 pandemic has changed people\u27s mobility patterns, increasing the preference for private modes and reducing the public transportation demand. Most scientific contributions have studied the role of mobility levels in the spread of the virus and the influence of public transport on COVID-19 infections, but ignoring the importance of individual-level variables potentially affecting COVID-19 infection, such as daily habits. This paper analyses the relationship between the probability of being infected by COVID-19 and using public transport through a survey data analysis, taking Madrid (Spain) as the case study. This research uses a survey campaign with more than 15,000 responses, capturing socio-demographic aspects, COVID-19 infections, daily habits, and mobility patterns with high risk of COVID-19 infection. Through a multilevel probit model, this paper explores the extent to which a higher use of public transport is related to a greater likelihood of COVID-19 infection. The results suggest a relationship, although not very strong, between the probability of infection and the conjunction of higher frequency of use of metro services and level of crowding during the trip, whereas the use of bus services and travel time within the vehicle do not appear to affect