Monash University, Institute of Transport Studies: World Transit Research (WTR)
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Assessing the Impact of Public Transportation, Bicycle Infrastructure, and Land Use Parameters on a Small-Scale Bike-Sharing System: A Case Study of Izmir, Türkiye
No full textMany cities in the world have deployed bike-sharing systems (BSS) to promote the use of bicycles. Previous studies analyzed the factors affecting the BSS usage, but these studies were predominantly conducted in cities that already possess well-established bike-sharing systems. However, there is a lack of comprehensive studies focusing on the factors influencing bike usage in cities where 1) bicycle culture is evolving and small-scale BSS is present, and 2) bicycles are not primarily considered as a transportation mode. This study aims to investigate the trip purposes and trip patterns of a small-scale docked BSS operating in Izmir, Türkiye. A two-step process was employed to determine the trip purposes, as cycling for leisure and cycling for transport. Later, ordinary least squares (OLS) and partial least squares regression (PLS) models were generated. The results showed that while the influence of public parks, residential areas and educational areas varied based on trip purpose, public transportation systems, particularly rail transit stations, and car parks appeared to have a more significant impact on transportation-oriented trips. Recommendations will be provided for the development of environmentally more sustainable BSS by accurately placing stations in the future to promote its usage for leisure or transportation purposes
Crowding multipliers on shared transportation in New York City: The effects of COVID-19 and implications for a sustainable future
No full textThe COVID-19 pandemic has added to the challenge of decarbonizing the transportation sector, as shared modes were perceived as more dangerous during the health emergency. If these behaviors persist, drawing riders to more sustainable modes may be more difficult. This study investigates measures how crowding multipliers in New York City for the subway, ridehailing, and microtransit changed during and after the pandemic. We used Bayesian techniques to estimate two mixed logit models based on stated preference data. Results show that post-pandemic crowding multipliers are either similar or lower than during the pandemic, depending on the transportation mode and masking compliance. Additionally, vaccination requirements did not significantly affect respondents’ choices, but respondents were willing to pay to reduce their transportation mode’s carbon footprint. The study suggests that commuters’ aversion to crowding will gradually decrease, but whether crowding multipliers will return to pre-pandemic levels or a post-pandemic ”new normal” remains uncertain
Assessing mode-specific transport affordability in a car-centric city
No full textHousing and transport are the two highest costs in household budgets and can significantly impact affordability and quality of life. These costs also impact decisions and require households to make a trade-off between the ease of accessing desired opportunities and the size of their home. Yet studies that have aimed to gain insights into the factors that influence housing and transport affordability to develop policy interventions rely on aggregate or incomplete measures of these associated household costs, potentially obfuscating the trends. This paper aims to enrich understanding of the relationship between housing and transport affordability using data collected from University of Alberta (Canada) students, faculty and staff. It relies on the reported monetary cost of household spending on housing and transport, and estimated travel time cost, as well as information on the transport mode and home location in an effort to confirm the relationship between housing and transport costs and identify policies that can lower generalized costs for households. Based on the analysis, we establish the importance of accounting for the travel time associated with different transport modes in quantifying the generalized cost burden of a household. We also confirm that housing and transport costs change in opposite directions with the increase in distance from the city core. Lastly, policy interventions that lower transport costs via improvements in transit service and land use are identified
An adaptive route choice model for integrated fixed and flexible transit systems
No full textOver the past decade, there has been a surge of interest in the application of agent-based simulation models to evaluate flexible transit solutions characterized by different degrees of short-term flexibility in routing and scheduling. A central modelling decision in the development is how one chooses to represent the mode- and route-choices of travellers. The real-time adaptive behaviour of travellers is important to model in the presence of a flexible transit service, where the routing and scheduling of vehicles is highly dependent on supply-demand dynamics at a near real-time temporal resolution. We propose a utility-based transit route-choice model with representation of within-day adaptive travel behaviour and between-day learning where station-based fixed-transit, flexible-transit, and active-mode alternatives may be dynamically combined in a single path. To enable experimentation, this route-choice model is implemented within an agent-based dynamic public transit simulation framework. We first explore model properties in a choice between fixed- and flexible-transit modes for a toy network. The adaptive route choice framework is then applied to a case study based on a real-life branched transit service in Stockholm, Sweden. This case study illustrates level-of-service trade-offs, in terms of waiting times and in-vehicle times, between passenger groups and analyzes traveller mode choices within a mixed fixed- and flexible transit system. Results show that the proposed framework is capable of capturing dynamic route choices in mixed flexible and fixed transit systems and that the day-to-day learning model leads to stable fixed-flexible mode choices
Post-COVID-19 campus commuting patterns and influential factors: evidence from a developing country
No full textThis research investigates factors influencing students’ commuting choices to university campuses, focusing on the post-COVID-19 era, attitudes, and socio-economic variables. The study includes original data collected from a total of 785 participants who were surveyed at Shiraz University, located in Iran. The study results indicate that while public transportation and university shuttle buses continue to be widely used for transportation, a considerable proportion of students prefer personal cars, mostly driven by favourable impressions. The closeness to the campus is a crucial factor in this regard, as the students residing within a distance of 3 km exhibit a preference for walking. Moreover, the significance of bio-security factors such as cleanliness and the effective control of crowds for modal choice in the post-COVID-19 era. The study\u27s findings give valuable insights for service providers and university administrators in the development of sustainable commuting programmes that align with the university\u27s environmental goals
A pattern-based timetabling strategy for a short-turning metro line
No full textThe planning of metro lines is typically done through a strictly hierarchical approach, which is effective but somewhat inflexible. In this paper, we propose a flexible semiperiodic timetabling strategy using short-turning; thus, allowing trains to turn before reaching the terminal station of a line. Our strategy produces timetables that are periodic with respect to a group of short-turning destinations. This is denoted by the term service pattern. We introduce the service pattern timetabling problem (SPTP). Given a service pattern, the SPTP optimizes the train timetable considering capacity restrictions. The SPTP is modeled as a constraint program. We develop a framework for producing a large set of diverse and high-quality timetables for a metro line. This is achieved by repeatedly solving the SPTP with different patterns. Then we select a restricted list of non-dominated solutions with respect to three objectives: (1) the average passenger waiting time, (2) the maximum load factor achieved by the trains, and (3) the number of transfers induced by short-turning. We evaluate the proposed framework on a number of test instances. Through our computational experiments, we demonstrate the effectiveness of the developed strategy
Air–rail timetable synchronisation: Improving passenger connections in Europe within and across transportation modes
No full textThis study addresses the integration of the railway and airline scheduling problems, in order to offer passengers smooth transfers between rail and air. This paper focuses on optimising the air and rail timetables at 18 major European airports including three hubs and their associated train stations. A multimodal passenger demand simulation, using constraint programming and based on real data, is proposed. A typical week, from Monday to Saturday, of December 2019 is analysed. Ten passenger demand simulations are run for each day, resulting in 60 test instances that are publicly released. The air–rail timetable synchronisation is applied to these 60 instances. Three scenarios are tested in which each operator agrees to change its schedule or not. Results show that changing the schedule of only 13% of European flights by 11 min, and half of trains scheduled to stop at the three hubs of 17 min, on average, could increase the number of suitable connections for passengers by 60%. In addition, if both airlines and railway operators adapt their schedules, passenger comfort is improved and operator costs are reduced, even more so than with unilateral changes
From “Big Small Town” to “Small Big City”: Resident Experiences of Gentrification along Waterloo Region’s LRT Corridor
No full textMost studies of transit-induced gentrification rely on statistical analysis that measures the extent to which gentrification is occurring. To extend and enhance our knowledge of its impact, we conducted sixty-five interviews with residents living along the light rail transit (LRT) corridor in Waterloo Region, Ontario, Canada, shortly before the system opened. There was already strong evidence of gentrification, with more than $3 billion (Canadian dollars) worth of investment, largely in condominiums, before a single passenger was carried. In line with contemporary critical conceptualizations of gentrification, our interviews identified new and complex psychological, phenomenological, and experiential aspects of gentrification, in addition to economic- or class-based changes
Analysing the impacts of individual-level factors on public transport usage during the COVID-19 pandemic: a comprehensive literature review and meta-analysis
No full textPublic transport (PT) usage was severely impacted during the COVID-19 pandemic, resulting in up to a 90% reduction in many cities in 2020. Numerous studies have been conducted since then to determine the relationship between individual-level factors (such as gender, attitudes, etc.) and the decrease in PT usage during the pandemic. Despite the evidence provided, findings are dispersed, and for several factors contradictory, making it challenging to reach any generalised conclusion. Furthermore, a comprehensive comparison of the effect sizes among travellers’ factors affecting PT use during this period is yet to be compiled. This paper aims to address these gaps by systematically reviewing the existing evidence and synthesising the effect sizes of travellers’ factors through a meta-analysis. We first identified 36 studies that statistically assessed the contribution of 15 individual-level factors on PT usage during the COVID-19 pandemic. By merging the empirical evidence of those studies, the direction of the association between those factors and PT usage was analysed. Then, after selecting comparable studies, meta-analyses were conducted for each factor to estimate the corresponding pooled effect sizes. The meta-analysis established that car availability, teleworking opportunities and high educational level contributed the most to reducing PT use during the pandemic. These factors increased the odds of reducing PT usage compared with the pre-pandemic by about three times. Factors such as COVID-19 risk perception, gender, high income and health had a moderate effect on the decision to stop using PT. PT habits, travel distance and physical accessibility also influenced PT use during the pandemic. Geographical location and the pandemic period explained part of the heterogeneity found. The findings provided in this study can help policy-makers understand the impacts of travellers’ factors on the decision to reduce PT usage during future pandemics/epidemics and guide public policies accordingly
Co-designing urban transport solutions with Southeast Asian young adults
No full textThe region of Southeast Asia is home to some of the most congested cities. In Malaysia the densely populated area of Kuala Lumpur and its surrounding Klang Valley face the congestion and pollution problems common to cities across Southeast Asia. This study uses the bottom-up approach of concept mapping to explore potential solutions to the transportation problems associated with rapid urbanisation. A sample of young adult Malaysian participants brainstormed ideas and generated 91 proposals for action, which they grouped into the six clusters of Legislation, Infrastructure, Public Transport, Culture & Practices, Education, and Policies. Each proposal was rated for Importance, Feasibility, and Improvement to Traffic Congestion. The study yielded a series of priorities for action by policy-makers including extending existing transport routes to close the ‘last mile gap’, providing safe facilities for non-motorised forms of transport, fair enforcement of existing regulations, and appointing properly qualified professionals to improve infrastructure