Monash University, Institute of Transport Studies: World Transit Research (WTR)
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Optimal public transport timetabling with autonomous-vehicle units using coupling and decoupling tactics
No full textFluctuating demand for public transport (PT) is one of the main reasons for unreliable PT service, and subsequent passenger frustration at being left behind at PT stops. A novel way to solve this situation is to optimally use autonomous PT vehicles with coupling and decoupling (C&D) of vehicle units to accommodate the fluctuating PT demand and reliability issues. In this way, vehicle size is added as a variable of the problem. This work proposes a new class of C&D tactics in the process of solving the problems of PT route timetabling subject to passenger demand. Resolving the optimisation problem involves determining the C&D arrangement at stops/stations to accommodate the C&D options and departure times. The validation of the model is performed by a small example and a real case study with a bilevel heuristic algorithm that manages to completely (100%) eliminate left-behind passengers using practical, even-headway, and even-load timetables
How bikesharing changed destination distance for its users: A case study of Chicago Metropolitan Area
No full textShared bike use has been growing, especially post-pandemic, because it improves personal mobility and provides an alternative to walking while increasing connectivity to transit services. Existing research has examined the impact of these services on mode share and vehicle ownership. However, these services also hold the potential to influence the distance people travel to reach destinations. In this study, we examine the impact of Divvy shared bike services in the Chicago metropolitan region on the average trip distance of its users across all trips between 2008, when the service was not operational in the city, and 2018. We use repeated cross-sectional household travel datasets from 2008 and 2018 for analysis. We perform difference-in-difference regression to calculate the change in average trip distance for the shared bike user group. As there is no way to track people in repeated cross-sectional datasets, unlike a panel dataset, we use propensity score matching to match users between the two datasets. The results indicate that the average trip distance is reduced by 0.841 km (miles) for the shared bike user group with the presence of shared bike services. Shared bike users are more likely to live in urban areas where destinations are in proximity and use multi-modal travel, which could be a reason for this group’s reduced average trip distance. Given our findings, we recommend planning for shared bike services integrated with transit in urban areas and promoting mixed land use so that users can choose proximate destinations in dense urban areas
Outdoor information panels to convey real-time travel information for transit ridership recovery
No full textTransit agencies in the United States have seen a drastic ridership decline since COVID-19. The research team collaborated with Massachusetts Bay Transportation Authority (MBTA) to utilize Outdoor Information Panels (OIPs) along major highways to deliver real-time travel information (RTTI) to encourage increased transit use. An online interview and a household survey were conducted in sequence to gather Great Boston Area (GBA) travelers’ travel experience, preferred RTTI contents, OIP graphic designs, and their stated mode shift in response to OIPs. The top three information items found to encourage transit use are real-time total travel time, next two train arrivals, and real-time parking availability. Additionally, travel cost is more influential for commuter rail (vs. subway) trips and major event (vs. generic) trips. 79% of transit user participants agree that OIPs would improve their travel experience. Trips with more flexible schedules and/or less requirement on carrying passengers and goods, such as social/recreational and major-event trips, are more influenced by RTTI than work, family, and shopping trips. Transit nonusers show a lower tendency to increase their transit use compared to transit users, with their potential increases varying more by trip purpose. A 2.1% emission reduction from work trips is estimated using a regional travel demand model for the GBA. Frequent transit users and nonusers (car users) contribute significantly to emission reductions. Frequent transit users contribute due to their substantial increase in transit use per person, despite being a smaller proportion of the traveling population, while nonusers contribute due to their large proportion, despite a smaller per-person increase in transit use
Beyond the bus: Unraveling DRT\u27s potential - An ex ante WTP evaluation for replacing ineffective fixed route regional lines
No full textThis study investigates the acceptance and willingness to pay (WTP) for Demand Responsive Transportation (DRT) services in the Košice Self-governing region in Slovakia as an alternative to fixed-route bus public transport. A total of seven settlements were selected for the study, where the existing fixed route bus service is economically unsustainable and could be potentially replaced by a DRT system. The findings reveal that 62 % of respondents are open to accepting DRT as an alternative to current bus transport, with an average WTP for these respondents of €0.36 per kilometer. Individual factors affecting the willingness to pay of respondents were identified, in particular age, household size, utilization and perceived quality of the existing bus system and access to other modes of travel, forming a base for identifying the target group for the DRT system. Main perceived shortcomings of the current bus system were also identified, that can form the basis for designing a specific DRT applicable in the studied region
Behavioural loyalty analysis of bus passengers using multi-source data fusion
No full textBus priority has been one of the most essential measures in achieving carbon peaking and carbon neutrality. However, in some cities, while the bus system is improving, the bus passenger volume is either growing slowly or declining. This opposite trend suggests that the behavioural loyalty of bus passengers has not been ensured despite improved bus facilities. This paper aims to enhance bus travel intention by addressing varied behavioural loyalty through a combination of survey and smart card data. The travel characteristics of bus passengers are clustered into behavioural loyalty and disloyalty using the K-means++ algorithm, and the factors influencing travel intention for these two types are analyzed using the Multiple Indicators and Multiple Causes (MIMIC) model. The findings regarding travel characteristics indicate that travel frequency for all passenger types decreases gradually as travel distance increases. Notably, long travel distances have negative effects on passenger loyalty. In terms of departure time distribution, loyal passengers exhibit more pronounced morning and evening peak periods, while disloyal passengers show less distinct evening peaks. Additionally, a significant proportion of loyal passengers engage in activities lasting 8–12 h on both weekdays and weekends. Meanwhile, the MIMIC model results indicate that both punctuality and attitude have significant positive impacts on both loyal and disloyal passengers. Loyal passengers prefer efficient and comfortable bus service, while bus travel speed, metro availability, and perceived behavioural control have positive impacts on disloyal passengers. Specific strategies are proposed based on the results of travel characteristics and the MIMIC model. These results can inform special strategies for improving bus travel intention and loyalty
Do I really like to shift to rail? Influence of rail modernisation on passenger preferences
No full textThe emphasis on environmentally friendly solutions is steadily increasing in the transport sector. The topic of this article is a discussion of the long-term European initiative shift to rail. This initiative is confronted with historical facts, using the rail connection between Prague and Pilsen in Czechia. Numerous modernisation activities have been carried out on this line and have led to a qualitative change in transport, albeit on a conventional railway line and not high-speed rail (HSR). The paper evaluates whether a significant rail infrastructure upgrade leads to a change in transport and residential behaviour. The evaluation relies on identifying relevant upgrade projects and assessing the costs of upgrading this conventional railway. According to the results showing a significant increase in ridership, passengers consider changes, frequency, and travel time to be the crucial factors of the fundamental change in service quality caused by the modernisation of the line. These changes are confirmed and emphasised by 29 in-depth interviews with new or more frequent rail passengers using the train connection between Prague and Pilsen, identifying individual preferences and motives for changing travel behaviour. The results show that an upgrade of a conventional rail line (comparable in cost to the construction of HSR in Spain) lead to significant savings in travel time of 17 % and motivated operators to increase frequency by almost 50 %, increasing ridership to more than double. Passengers\u27 interviews revealed more topics, such as services, comfort, and the difficult parking situation in Prague possible determinants for relocation and daily commuting
Unveiling inequalities: The intersection of gender and income in accessibility in Curitiba, Brazil
No full textThis research investigates accessibility inequalities in Curitiba, Brazil, employing an intersectional analysis of gender and income groups within the urban context. We utilized an Agent-based model (AxS model) to generate artificial trajectories from the Origin-Destination (OD) survey aggregated dataset and calculate individual accessibility metrics. The findings reveal that, overall, men have greater accessibility to opportunities than women in Curitiba. The exception is in income class A (the highest), where women tend to travel shorter, more central routes and use cars more frequently, leading to higher accessibility. However, women in other income groups (lower income) face lower accessibility than their male counterparts, largely due to living in peripheral areas with fewer local opportunities and being more dependent on slower transport modes such as public transportation and walking to access these opportunities. The gender accessibility gap widens notably as income decreases, showing the significance of intersectionality of income and gender factors. Counterfactual simulations revealed that the choice of transport modes has a greater impact on women\u27s individual accessibility than the distances traveled. The discussion emphasizes the need for mixed land use in peripheral areas and improvements on public transportation to ensure extensive coverage and reduce travel times to mitigate the effects of gender and income inequalities. This research contributes to studies on gender-sensitive urban planning, providing insights for policymakers and urban researchers seeking to foster inclusivity and equality in transportation systems and spatial development
How do built environment characteristics influence metro-bus transfer patterns across metro station types in Shanghai?
No full textUnravelling the complex relationship between metro-bus transfer behavior and the built environment is crucial for the construction of a sustainable urban public transportation system. The current research prominently emphasizes modeling station-level metro-bus transfer ridership in relation to the built environment that surrounds with transit stations, few has specially focused on exploring and comparing this relationship among various transit station types. Based on the case study of Shanghai central city, this research clustered metro stations according to the time-series similarity of metro-bus transfer ridership pattern by combining Derivative Dynamic Time Warping and K-medoids. Then, for each metro station group, the spatiotemporal heterogeneity and nonlinearity of built environment effects on transfer ridership pattern were examined simultaneously by applying an adapted GTWR-RF method that integrates Geographically and Temporally Weighted Regression (GTWR) and Random Forest (RF). Our empirical analysis confirmed the importance of key built environment determinants and their associations with transfer ridership vary significantly among different metro station types. Furthermore, this research highlighted the proposed GTWR-RF model, which considers both spatiotemporal heterogeneity and nonlinearity effects of the built environment on the transfer ridership, can significantly improve the prediction ability. These findings provide a comprehensive perspective for policymakers, enabling them to formulate transportation policies with consideration of station type specification and to bolster the overall public transportation usage in cities
The impacts of public transportation development on gentrification and poverty in Hong Kong neighbourhoods (2006–2021)
No full textThis study examines gentrification situation and changes in the number of poor households in Hong Kong from 2006 to 2021 with data from three census time points. It examines key neighbourhood characteristics and the impacts of recent public transportation development, focusing on both lower-income neighbourhoods and the whole territory. The findings reveal that lower-income Tertiary Planning Units (TPUs) with lower tenant proportions and new Mass Transit Railway (MTR) stations were more vulnerable to gentrification. There was a negative correlation between household income and the likelihood of losing poor households.
At the territory level, the impact of new MTR stations on gentrification was less significant, indicating greater resilience of the households. Additionally, TPUs with larger proportions of older adults had higher likelihood to experience a loss of poor households. Using difference-in-differences (DiD) approach, improved accessibility from MTR extensions is found to be positively correlated with changes in the proportions of poor households in the TPUs. The results provide valuable insights for designing targeted social welfare, housing and community policies
Unveiling the population heterogeneity in time-money trade-offs: Insights from Beijing’s subway commuters
No full textDeveloping sustainable and inclusive strategies for cities requires moving beyond universal solutions to address the diverse preferences of urban dwellers. However, the challenge lies in the invisible nature of these preferences. Here, we reveal residents’ preferences for time versus money by investigating the relationship between commuting time and housing prices. Using a multivariate linear regression model to analyze data from 219,000 Beijing subway commuters (153,000 from subway smartcard data and 66,000 from mobile phone signaling data), we find that: 1) Commuting time is negatively related to housing prices, indicating a trade-off between time and money. Specifically, for every ten thousand yuan per square meter change in housing prices, commuting time changes by 3 to 7 min. 2) The exchange rate of this trade-off reveals heterogeneity among residents. Measured by housing price changes, the willingness to pay for every minute of reduced commuting time in high-priced areas is three times that of low-priced areas. Long-distance commuters (those with a daily commute of over 90 min) require five times the compensation for an additional minute of increased commuting time compared to non-long-distance commuters. These findings highlight the need for urban policies that respond to residents’ diverse preferences, enhancing sustainability in urban planning