Monash University, Institute of Transport Studies: World Transit Research (WTR)
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“I saw a fox in Melbourne CBD”: Urban travel behaviour changes during COVID-19 and beyond
No full textAn unexpected outcome of the COVID-19 pandemic were the dramatic travel behaviour changes experienced in cities worldwide, which, could result in more sustainable transport systems. Consequently, there is a need for longer-term post-pandemic travel behaviour change research. This study aimed to investigate city-level travel behaviour changes during and post-pandemic. To our knowledge, this is the first qualitative study exploring the permanency of COVID-19 travel behaviour changes. This study involved a literature review of 41 studies and in-depth interviews with 19 transport stakeholders in metropolitan Melbourne, Australia. Melbourne is a valuable study area, given that it was the most locked-down city globally. Overall, the results of this study suggest that post-pandemic travel behaviour will be different to pre-pandemic, with working from home (WFH) an integral influence on travel behaviour. In addition, several overarching travel behaviour changes were identified: WFH significantly increased during the pandemic and is anticipated to continue post-pandemic. Both public transport and private motor vehicle (PMV) trips decreased during lockdowns; while PMV rebounded quickly, public transport remained low, and a long recovery is expected. Active transport (cycling and walking) increased during the pandemic and appear likely to endure. Finally, while shared travel modes have received less attention, modal variance is expected in the future. This study has made several key contributions. It consolidated our understanding of the wide range of urban travel behaviour changes experienced during and anticipated post-COVID-19. Secondly, it synthesised current knowledge of recent post-COVID-19 travel behaviour change research. Thirdly, this study demonstrated that complementary qualitative studies strengthen transport research by unearthing new insight into the reasons underpinning travel behaviours, which could be vital for developing solutions. Furthermore, this study identified critical future research topics. Given that most countries are learning to live with the virus, it is an opportune time to investigate whether these intended travel behaviours have endured
Is it the behavior and actions of people that determine sustainable urban communities?
No full textThis study aims to provide an analytical understanding of the primary evidence for making urban centers sustainable through channelizing people\u27s preferences, behaviors, and actions toward sustainable urban communities. The structured questionnaire is used, which includes all possible dimensions to get the response from 361 households from Islamabad, the capital city of Pakistan. The Ordered Logistic Regression model is applied to analyze people\u27s preferences, behaviors, and actions for sustainable urban communities. The results indicate that people\u27s preferences, behavior, and actions toward water, energy conservation, and using recyclable products are likely to have a significant impact in determining urban sustainability communities. In comparison, food-related behaviors and actions are surprisingly weak in influencing urban sustainability communities. Thus, this study recommends implementing water metering, maximizing daylight use, a culture of energy-efficient buildings, and a smart public transportation system for sustainable urban communities besides awareness campaigns to influence people\u27s preferences and behaviors
Acceptability of transportation demand management policy packages considering interactions and socio-economic heterogeneity
No full textThe Transportation Demand Management (TDM) policies will not be authorized if they have not enough public acceptability. In this study, policy packing is proposed as a way to alleviate the unacceptability of coercive (push) TDM policies that have considerable effectiveness (e.g., cordon and parking pricing) by using some non-coercive (pull) TDM policies (e.g., transit development). Furthermore, in addition to the main effects, the interaction effects of TDM policies on the acceptability of two policy packages are addressed. Policy package (I) includes cordon pricing and reduction of transit access time, and Policy package (II) contains parking pricing and reduction of transit access time. A Random Parameter Ordered Logit (RPOL) model is developed based on a choice experiment designed for car commuters of Tehran, Iran. Results confirm that while reducing transit access time have a significant interaction effect with cordon pricing on the acceptability of Package (I) it has not a significant interaction effect with parking pricing on the acceptability of Package (II). Furthermore, the heterogeneity of respondents\u27 cars value and the presence of free parking at the workplace can significantly affect the acceptability of Package (II). This study also addresses the effect of respondents’ trip and socio-economic characteristics on the acceptability
Attitudes towards public transport under extended disruptions and massive-scale transit dysfunction: A Hong Kong case study
No full textDisruptions to transport systems often significantly change travel behaviour. This is especially true when the disruption lasts over an extended period and is accompanied by the massive-scale dysfunction of transit operations. In addition, although attitude is critical for predicting travel behaviour, there is little documentation of changes in attitudes towards transit modes and the factors influencing such changes during a transit system disruption. Furthermore, few studies have investigated how social movements can exert a pronounced disrupting effect on a transit system. To fill these research gaps and provide policy recommendations for a more responsive contingency plan in response to future transit system disruptions, our study aims to investigate this issue based on the case of Hong Kong during the 2019 social movement. We collected a questionnaire survey representing the period from late June to early July 2020, a few months after the end of the protests. Using structural equation models, we have examined how people\u27s attitudes towards different transit modes changed during the social movement. Our findings highlight that people\u27s perception of the city\u27s urban rail system – the Mass Transit Railway, which the government has a significant stake in and control over – worsened significantly during the transit disruption, but the effects were less pronounced for bus and mini-bus. In addition, attitudes towards the social movement were found to vary significantly across social groups, a finding linked to people\u27s attitudes towards different transit modes. Importantly, our study reveals that people\u27s views of social movements can significantly determine how they evaluate impacted and alternative transport modes during transit disruptions. These newly revealed attitudinal dimensions should be fully considered in predicting behavioural change and adjusting transit services under similar conditions
Transit Safety System Evaluation and Hotspot Identification Empowered by Edge Computing Transit Event Logging System
No full textThis paper discusses the importance of near-crash events and associated metadata as valuable sources for smart transit applications, such as surrogate safety measures for transit safety research. The STAR Lab at the University of Washington, sponsored by the Federal Transit Administration, has developed an edge computing system that processes onboard videos for near-crash detection. This paper builds on previous work by addressing two research questions: first, how to leverage the near-crash detection system to synthesize rich data sources on transit vehicles, and second, how to use the smart data hub to support transit operation and safety studies. The proposed procedures for event-based transit data collection, evaluation of commercial collision avoidance warning systems (CAWS) technologies, and transit safety hotspot identification are detailed. CAWS’ performance was benchmarked on four transit buses that were operated for almost a year in Pierce County, WA, U.S. Furthermore, the meta-information of near-crash events enables hotspot analysis and the identification of several exemplar clusters that can be explained by driver behavior and roadway geometries. The results of the experiments demonstrate the system’s promising performance and its applicability to addressing various transit operation questions
Employee intentions and employer expectations: a mixed-methods systematic review of “post-COVID” intentions to work from home
No full textThe COVID-19 pandemic accelerated cultural and organisational acceptance of remote working. For a portion of the commuting workforce, working from home (WFH) is now possible. Of great interest is whether increased WFH will diminish actual mobility, and thereby reduce the transport task of cities. To understand this possibility, we must know how much WFH will be sustained into the future. Using a bespoke approach combining scholarly and grey literature, this review develops a tangible record of employee desires and intentions to WFH, in the context of the expectations of employers. Its contribution is a novel and rigorous appraisal of recent practices and sentiments. Results confirm that there is a strong underlying demand to WFH. Many studies, however, estimate unrealistically high rates of WFH which cannot be projected onto the wider working population. Further, we find there is a conflict between employee preferences and their expectations to WFH, with estimations of preferences far greater than estimates of expectations. This finding is confirmed by the analysis of employer sentiments. Employers broadly realise that accommodating WFH reflects a best-practice approach, yet favour predictable routines where specific days of on-site attendance are mandated. We conclude with reflections on the impact of our findings on the transport system. We propose that the impact of WFH on commuter decision-making depends on the degree to which employers mandate on-site attendance. Finally, we emphasise the need to acknowledge the wider political, economic and social milieu in which work is performed as shaping future WFH practice
Two-stage control for transfer synchronisation and regularity of subsequent bus line service
No full textTransfer synchronisation aims at reducing the waiting time of transferring passengers to achieve a seamless transfer. Taking control at the operation level is widely regarded as an effective method to make real-time response to transfer synchronisation. However, the irregularity of bus line service after transfer may be caused due to the real-time control before the transfer behaviour. In this paper, we propose a two-stage speed control strategy to improve the transfer efficiency and the regularity of bus service after transfer simultaneously. The influence of speed control is estimated by constructing dynamic rolling horizon. Considering the service performances of both the transfer node and the next stop, we develop a multi-objective optimisation model. Experimental results show that compared with the one-stage control, the two-stage control can significantly reduce the deviation of headway after transfer while reducing the transfer time
Subjective vs. objective assessment of the economic impacts of light rail transit: The case of G:Link in Gold Coast, Australia
No full textWhile the current discourse surrounding the economic impacts of light rail transit (LRT) predominantly leans on objective metrics, emerging signs point to a possible disparity between subjective perceptions and these objective evaluations. This study endeavours to fill this void by scrutinizing the impacts of the G:Link in Gold Coast, Australia on local businesses, prompted by anecdotal commentary of adverse effects. Conducting 23 interviews with businesses in Surfers Paradise, located within the G:Link\u27s influential zone, helped identify thematic economic effects. Subsequently, Difference-in-Difference and time-series regression models were estimated to objectively validate four of the identified thematic effects: changes in travel behaviour, business performance, customer base, and tourism activity. While businesses perceived the G:Link as ineffective in promoting public transport and blamed it for their economic downturns, objective data countered these perceptions. It revealed that the G:Link contributed to a 3.6% rise in public transport usage to Surfers Paradise. The economic downturn experienced by businesses cannot be linked to the LRT; rather, it mirrors a broader citywide temporal effect. Furthermore, in contrast to prevailing beliefs, there was a notable increase in both customer volumes and their dwell times. The findings offer nuanced insights into LRT\u27s effects on individual businesses and aggregated impacts, highlighting prevalent misperceptions that could undermine public support, investment opportunities, and sustainable transport choices. Addressing these misunderstandings necessitates robust education and communication strategies
The impacts of extreme hot weather on metro ridership: A case study of Shenzhen, China
No full textUnder climate change, cities around the world would be faced with increasingly frequent, intense, and prolonged heatwave events. Currently, not enough research has looked into the temperature-metro ridership relationship in the scenario of extreme hot weather. Moreover, a geographical perspective, particularly on the characteristics of the built environment surrounding the metro stations, is still lacking in existing studies. To fill these research gaps, this study uses one year of hourly metro ridership and temperature records to examine the general relation between temperature and metro ridership. It also further investigates the metro ridership change during a week-long heatwave event in Shenzhen in 2016. Multivariate regressions were built for the overall scenario and separately for the weekday, weekend, peak hours, and off-peak scenarios. The results provide evidence for the non-linear relationship between the rise in temperature and the increase in metro ridership. The findings also suggest a general decline in metro ridership both on weekdays and the weekend during the heatwave, with more remarkable change observed on the weekend and off-peak hours on weekdays. Urban environment characteristics around metro stations, such as the number of companies, population density, amount of tree canopy, as well as the betweenness-centrality of stations, are found to be associated with the magnitude of change in metro ridership during the heatwave. The findings of this study offer some implications for the planning, design, and operation of metro systems in the future
A data-driven conceptual framework for understanding the nature of hazards in railway accidents
No full textHazards threaten railway safety by their potential to trigger railway accidents, resulting in significant costs and impacting the public\u27s willingness to use railways. Whilst many prior works investigate railway hazards, few offer a holistic view of hazards across jurisdictions and time because the large number of primary sources make synthesising such learnings time consuming and potentially incomplete. The conceptual framework HazardMap is developed to overcome this gap, employing open-sourced Natural Language Processing topic modelling for the automated analysis of textual data from Rail Accident Investigation Branch (RAIB), Australian Transport Safety Bureau (ATSB), National Transportation Safety Board (NTSB) and Transportation Safety Board of Canada (TSB) railway accident reports. The topic modelling depicts the relationships between hazards, railway accidents and investigator recommendations and is further extended and integrated with the existing risk theory and epidemiological accident models. The results allow the different aspects of each hazard to be listed along with the potential combinations of hazards that could trigger railway accidents. Better understanding of the aspects of individual hazards and the relationships between hazards and previous accidents can inform more effective hazard mitigation policies including technical or regulatory interventions. A case study of the risk at level crossings is provided to illustrate how HazardMap works with real-world data. This demonstrates a high degree of coverage within the existing risk management system, indicating the capability to better inform policymaking for managing risks. The primary contributions of the framework proposed are to enable a large amount of knowledge accumulated to be summarised for an intuitive policymaking process, and to allow other railway investigators to leverage lessons learnt across jurisdictions and time with limited human intervention. Future research could apply the technique to road, aviation or maritime accidents