Monash University, Institute of Transport Studies: World Transit Research (WTR)
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Assessing the impact of the new Mexico cable car on air pollution
No full textThe impact of traffic on air quality has prompted many cities to implement policies such as driving and parking restrictions, congestion fees, or investing in public transport infrastructure. This paper focuses on the effects on pollution levels of a new cable car system in Mexico City, a very polluted megalopoly. This cable car system provides transportation to historically marginalized communities situated in a mountainous area at an altitude high enough to make metro connectivity impossible. The study uses official NO2 level data to estimate a Diff-in-Diff model. The results show a drop in NO2 levels of approximately 13 % not only in the stations closest to the Cablebus, but also in areas located further away. Our results suggest that the potential environmental benefits of new green transport infrastructures should be taken into account by policymakers when making decisions related to public transit systems
Investigating scheduling of minibus taxis in South Africa\u27s eventual electric paratransit
No full textThe predominant mode of public transport in South Africa originates from the informal sector, specifically “paratransit”. Vehicles carry up to 23 passengers and are still propelled by internal combustion engines. We investigate the feasibility of using electric vehicles without negating the loss of opportunities by drivers and owners. We propose that scheduling of the electric vehicles is one important cornerstone towards electrification. We developed a fast-executing heuristic scheduling algorithm that allows for multiple vehicle depots in the transport network; simultaneous electric and internal combustion engine vehicle deployment; determining the number of charging stations; partial charging; and scheduled charging with intermittent electricity supply. The scheduling algorithm achieves the minimum number of vehicles to execute the passenger demand in shorter total distances, outperforming current approaches. The algorithm demonstrated multi-objective optimisation by minimising the vehicles, the number of charging stations, and the average trip delays of a schedule
Assessment of urban rail transit network passenger-centered resilience under hazards: A dynamic resilience assessment framework
No full textUrban rail transit (URT) is vulnerable to cascading failures from disasters due to their complexity. In modern society, we should pay more attention to the experience of passengers and enhance the quality of service in URT. This paper develops a model using dynamic indicators to assess the disaster resilience of URT. It presents a novel passenger-centered resilience assessment method that reflects dynamic passenger flow demand indicators. A cascading failure model under Geometric Attack Model was established to simulate the route choice of passengers before and after cascading failure. This paper collected data on the Beijing subway, analyzed the features of dynamic passenger flow resilience indicators, and assessed the disaster resilience of the Beijing subway. Results show: (1) generalized travel time costs and transfer times for passengers increase after cascading failures, indicating reduced system resilience; and (2) two indicators are at moderately low resilience levels. This shows that passenger travel routes become more complicated after station failure, and the network’s ability to restore service and maintain service quality in the aftermath of unexpected events needs improvement. The paper suggests improving disaster resistance by adding redundant lines and other measures and also discusses adjusting assessment strategies based on the unique characteristics of different cities. A sensitivity analysis was conducted on the model, and based on this, guiding suggestions were made for optimization strategies
Operation estimation on multiple public transport timetables integrated with vehicle scheduling in practice
No full textEven-headway and even-load timetables have been in practice for the past 50 years. The former stipulates constant departures to cultivate users’ habits accordingly, whereas the latter is oriented from demand regulations aiming to further reduce waiting times. However, striking the balance between operation reliability (derived from even-headway timetabling) and an on-demand response to passenger fluctuation (referring to even-load timetabling) requires addressing major challenges presented by peak or alternatively off-peak demands. Our work addresses this imbalance by comparable estimation. The focused problem involves timetabling, vehicle scheduling, fleet size, and operation reliability based on an identical modeling framework simultaneously involving the three models. Nonetheless, their compatibility warrants a unified measure estimation. Hence, a mixed integer linear programming model is built. Finally, multiple timetabling performance comparisons are observed by the Auckland public transport system yielding sensitivity analysis
Public transport crowding valuation in a post-pandemic era
No full textIt is important to understand how public transport passengers value on-board crowding since the outbreak of the COVID-19 pandemic. The main contribution of this study is to derive the crowding valuation of public transport passengers in a post-pandemic era entirely based on observed, actual passenger route choices. We derive passengers’ crowding valuation for the London metro network based on a revealed preference discrete choice model using maximum likelihood estimation. We find that after the passenger load on-board the metro reaches the seat capacity, the in-vehicle time valuation increases by 0.42 for each increase in the average number of standing passengers per square metre upon boarding. When comparing this result to a variety of crowding valuation studies conducted before the pandemic in London and elsewhere, we can conclude that public transport passengers value crowding more negatively since the pandemic. Furthermore, we found a ratio between out-of-vehicle time and in-vehicle time of 1.94 pre-pandemic and of 1.92 post-pandemic, based on which we conclude that the relative waiting/walking time valuation did not significantly change since the COVID-19 pandemic. Our study results contribute to a better understanding on how on-board crowding in urban public transport is perceived in a European context since the outbreak of the COVID-19 pandemic
Immobility and COVID-19: comparing mobility reduction among socio-demographic groups in a large German city during the pandemic
No full textThe COVID-19 pandemic and the public health measures imposed to tackle the spread of the virus have changed the everyday life and severely reduced the mobility of many. In this paper, we investigate the relationship between changed transport behavior and complex socio-demographic groups. Drawing on a survey on mobility and transport use during the pandemic for the Hanover region (Germany), we find three distinct clusters in our data related to changed mobility behavior: (1) people with no change in transport behavior, (2) people heavily reducing public transport use in the inner city, and (3) people reducing public transport use for their commute. In a second step, we use logistic regression models to understand the socio demographic factors determining each of these change patterns. The results show that women and younger participants were more likely to experience an impact on their travel behavior as well as reducing the use of inner-city public transport, while the reduction of commuter transport seems to be mostly homogeneous once controlled for teleworking. We also find a complex interplay between gender and other socio-demographic factors, especially caring responsibilities for children and student status, to have shaped the reported extent of mobility reduction. We show that we need to think about socio-demographic variables in a more complex way instead of perceiving of them as stand-alone variables. Our analysis hence helps to uncover the complex reality of mobility reduction during the pandemic, providing deeper insights into the (im)mobile reality of people’s lives in times of COVID-19.Kindly check and confirm inserted city name are correctly identified.Yes, the city name is Hanover and thus corretly identifie
Would you like to get on the bus? An eye-tracking study based on the stimulus-organism-response framework
No full textTo encourage people to participate in bus travel, it is important to explore the factors that affect their willingness to ride. Previous studies have rarely considered both subjective and objective factors that affect passenger willingness. We designed a laboratory experiment based on the stimulus-organism-response framework using the waiting scene as the stimulus, perception of crowding (POC) and the emotion and eye-tracking indicators of waiting passengers as the organism, and willingness to ride as the behavioral response. A total of 64 participants were asked to look at 24 pictures of waiting scenes on an eye tracker and to complete a questionnaire. The results show that window permeability, number and distribution of passengers, and queuing mode significantly affect the POC, emotion, and gaze behavior of waiting passengers. The POC, emotion of waiting passengers, and their gaze at the waiting environment significantly affect the willingness to ride. Accordingly, we propose to promote the development of bus travel through measures such as providing more accurate travel information, installing queuing facilities, and modifying the bus card swiping machines. This study not only helps to improve the willingness of people to participate in bus travel, but also contributes to bus travel research and theory
The effect of ease of travel on travel behaviour and perceived accessibility: A focus on travel to university campus
No full textEase of Travel (EoT), referring to people’s travel skills and motivations, and available travel options and quality can influence how people travel and how easily they can reach out-of-home activities. In this study, we explore the new concept of EoT and analyse its underlying structures using a sample of 2,593 students and staff members of University College London (UK). Subsequently, the determinants of EoT elements are examined, while we also analyse how EoT affects travel to campus and the perceived accessibility of the campus. Results suggest that EoT is effectively composed of the four elements motivation, skills, options and quality. These EoT elements are mainly affected by the residential location, travel disabilities, and the proximity of public transport and shared (e-)bikes. Finally, we found that EoT significantly impacts travel mode choice, travel distance and duration when travelling to campus, while positively affecting the perceived accessibility of the campus. Improving EoT levels, and making it easier for people to travel around, can result in shorter and more active trips and can also increase accessibility to out-of-home activities (improving people’s well-being). This could be realised by creating more compact, mixed-use neighbourhoods with easy access to public transport and shared (e-)bikes
Hierarchical Nearest Neighbor Gaussian Process models for discrete choice: Mode choice in New York City
No full textStandard Discrete Choice Models (DCMs) assume that unobserved effects that influence decision-making are independently and identically distributed among individuals. When unobserved effects are spatially correlated, the independence assumption does not hold, leading to biased standard errors and potentially biased parameter estimates. This paper proposes an interpretable Hierarchical Nearest Neighbor Gaussian Process (HNNGP) model to account for spatially correlated unobservables in discrete choice analysis. Gaussian Processes (GPs) are often regarded as lacking interpretability due to their non-parametric nature. However, we demonstrate how to incorporate GPs directly into the latent utility specification to flexibly model spatially correlated unobserved effects without sacrificing structural economic interpretation. To empirically test our proposed HNNGP models, we analyze binary and multinomial mode choices for commuting to work in New York City. For the multinomial case, we formulate and estimate HNNGPs with and without independence from irrelevant alternatives (IIA). Building on the interpretability of our modeling strategy, we provide both point estimates and credible intervals for the value of travel time savings in NYC. Finally, we compare the results from all proposed specifications with those derived from a standard logit model and a probit model with spatially autocorrelated errors (SAE) to showcase how accounting for different sources of spatial correlation in discrete choice can significantly impact inference. We also show that the HNNGP models attain better out-of-sample prediction performance when compared to the logit and probit SAE models, especially in the multinomial case
The role of perceptions and expectations for public transport satisfaction in Korean metropolitan areas
No full textThis study investigated the determinants of passenger satisfaction. We conducted an online survey among public transport users in five Korean metropolitan areas and discuss differences between Seoul and other metropolitan areas. This survey examined satisfaction based on perception and expectation across five dimensions: Mobility, Accessibility, Reliability, Transfer, and Comfort. The study introduced the gap score, which represents the difference between perceived and expected satisfaction, to meaningfully explain overall passenger satisfaction. Using structural equation modeling to explore path coefficients, we found that “Accessibility gap” is a significant determinant of satisfaction regardless of metropolitan area size. “Mobility gap” in the capital region and “Comfort gap” in comparatively smaller metropolitan areas were also found to be significant determinants. This is despite overall mobility being rated higher and comfort being rated lower in the capital region. Our results suggest hence a “paradox” for public transport planning. If the service aspect is better, passengers develop higher expectations and deviations from the expected service quality raises disappointment which leads to overall reduced satisfaction