Infrastructure Engineering - Research Publications
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ItemSpatial and Spatiotemporal Matching Framework for Causal Inference(Schloss Dagstuhl, 2022-09-01)Matching is a procedure aimed at reducing the impact of observational data bias in causal analysis. Designing matching methods for spatial data reflecting static spatial or dynamic spatio-temporal processes is complex because of the effects of spatial dependence and spatial heterogeneity. Both may be compounded with temporal lag in the dependency effects on the study units. Current matching techniques based on similarity indexes and pairing strategies need to be extended with optimal spatial matching procedures. Here, we propose a decision framework to support analysts through the choice of existing matching methods and anticipate the development of specialized matching methods for spatial data. This framework thus enables to identify knowledge gaps.
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ItemIntegrating sustainability into higher education curricula(Engineers Australia, 2021)Education has been widely recognised as a key instrument to achieve sustainability. Integrating sustainability knowledge, skills and values are considered paramount to enable individuals to contribute to sustainable development. The paper presents a pilot study conducted at the University of Melbourne to investigate the links between the subjects offered by the University and sustainability. The pilot study is a part of the Sustainability in the Curriculum program, which addresses the Sustainability Plan Teaching and Learning Target 1, aimed to incorporate sustainability knowledge and values in the University's curricula. The 17 Sustainability Development Goals have been used as a framework to measure how well the curricula are linked to sustainability. A study first undertaken to establish the link between subjects and the Sustainability Development Goals is presented. The study involved data collection through published literature on Sustainable Development Goals and the University's subject handbook, followed by a survey involving the subject coordinators. The findings of the study show that the strength of linkages between subjects with sustainability varies, highlighting the challenge in some technical subjects in linking their contents with sustainability. Approaches adopted in the Faculty of Engineering and Information Technology in embedding sustainability in the curriculum are presented with some examples and discussions for the next steps.
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ItemForeword(The University of Melbourne, 2022-09-27)
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ItemNo Preview AvailableValue of Intersection Cross Box Data in Traffic Signal Control(ITS World Congress, 2021)
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ItemNo Preview AvailableInvestigating into public transport fare noninteractions using large-scale automatically collected data(Australasian Transport Research Forum, 2022)Fare card data provides an unprecedented opportunity to monitor day-to-day variability of travel demand and its responses to service disruptions and special events. However, when passengers take public transport without interacting with the fare system, demand is usually underestimated, which may cause problems for performance measurement and revenue collection. This research aims to investigate the fare noninteractions phenomena of the tram network in Melbourne, Australia. According to a prior evaluation, only 37% of boarding passengers validate tickets. This study utilizes large-scale automatically collated data to measure fare noninteractions, including data collected by Automatic Passenger Counting (APC) and Automated Fare Collection (AFC) systems. Compared to previous studies with small samples of on-board surveys, it contributes to the state of the art as these high coverage data enable the study of the impact of different types of explanatory variables, including time periods, routes, stop location, travel demand variability, presence of an inspector on-board, etc. Moreover, a free service zone is located in Melbourne central business district where passengers are not required to validate tickets. We specifically investigate passengers’ behavior at the boundary of a free service zone. Results show that fare noninteractions are lower for stops close to train stations, education facilities, stops that have been frequently inspected, and during the peak hours, but are higher for stops with large boarding flows, crowded services, evening periods and weekends. Importantly, conditioning on other variables, fare noninteractions at the boundary of the free service zone are higher in the morning peak but lower in the afternoon peak. The passenger flow diagram demonstrates the reason behind this may lie in the differences between purposes of trips. This investigation provides a starting point for proposing solutions to deal with the missing AFC data due to fare noninteractions.
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ItemNo Preview AvailableConsiderations for Expediting Road Safety Benefits with the Deployment of Vehicle Communication Technologies(Australasian Transport Research Forum, 2022)Communication technologies are enabling the introduction of connected vehicles and have the potential to improve road safety outcomes at a global scale. This paper aims to deliver a systematic understanding, classification, and evaluation of available communication technologies for road safety that considers the current challenges, mindsets, and future direction for C-ITS technology implementation. This is achieved by combining the results of three lines of research inquiry: 1) literature review of existing communication technologies and worldwide pilot experiments and trial implementations, 2) assessment of the potential for selected connected vehicle safety applications to address motor vehicle crashes across different geographies and road conditions, and 3) expert panel interviews to investigate the challenges and opportunities for technology implementation, specifically in the Australian context, with supporting evidence from global literature sources. These investigations found that C-ITS deployment concerns identified by stakeholders are in line with those identified in literature; however, there are significant safety benefits to be reaped from C-ITS deployment. Policymakers can leverage the potential of this positive outcome and target efforts at addressing the identified challenges when considering pathways to the uptake of connectivity technologies.
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ItemNo Preview AvailableData-driven evaluation model of safety risks at signalised intersection(Australasian Transport Research Forum, 2022)Near future safety risk evaluation is a critical step towards adaptive traffic safe operation at a smart intersection. This paper proposes a data-driven model that can quickly evaluate simulated safety risks for use in adaptive operational interventions. A traffic micro-simulation model was utilised to generate conflicts-based data for developing the machine learning model. Conflict indicators including time to collision, TTC, and post encroachment time, PET, were used to identify safety risk. Supervise learning models such as linear regression and machine learning models including random forest and extreme Gradient Boosting (XGBoost) were employed to evaluate risk indices for adaptive operations. In total, 9 models were trained, and XGBoost were found to outperform the other algorithms with 0.87 of the overall accuracy. The findings of this study contribute to the development of edge computing traffic operation system accounting safety.
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ItemNo Preview AvailableAbnormality Detection in Urban Traffic Data: A Review(Australasian Transport Research Forum, 2022)Anomalous data is called to a data sample or a sequence of data that significantly differs from the others. Accurately and on-time detection of anomalies (abnormalities) is crucial for system managers since it may convey important information to them. Anomaly detection is widely investigated in different research areas as well as transportation and traffic field. In this paper, we review the literature of anomaly detection in urban traffic networks to find the most recent state-of-the-art methodologies in this field. A search method is used in this paper to find the most relevant research papers, and they are studied and analyzed regarding anomaly type, data type, and methodology. Different types of anomalies, data collectors, spatiotemporal scopes, and detection methods in the literature are categorized and investigated in this work. Finally, a summary and conclusion section is provided in this work to show the possible future research directions. Based on the findings, accidents and city-wide events like festivals or concerts are mostly detected in previous works as anomalies using loop detector (LD), and trajectory data (GPS data). Moreover, supervised methods are mostly employed for accident detection aims, but papers using unsupervised approaches detect city-wide events with GPS data.
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ItemNo Preview AvailableThe impact of high-occupancy lanes on the uptake of on-demand ridesplitting services(Australasian Transport Research Forum, 2022)New mobility alternatives such as on-demand ridesplitting services can bring large benefits to cities by increasing automobile occupancy and reducing congestion, pollution, and space allocated to parking. However, the current adoption of on-demand ridesplitting services is still limited and transport demand management (TDM) strategies may be necessary to increase such uptake. This work uses the agent-based simulation tool MATSim to simulate 10% of the population in the Greater Melbourne Area and investigate the effectiveness of dedicated ridesplitting lanes (DRL) on the uptake of on-demand ridesplitting services and overall transport network efficiency. Results suggest that the tested DRL configurations are effective in increasing the uptake of such services. We observe a significant increase in vehicle occupancy and a reduction in vehicle kilometres travelled, which indicate that this is a promising policy. However, in regard to average travel time, DRL scenarios benefit people with trips within the on-demand ridesplitting service’s area while deteriorating average travel time for people whose trips’ origins and/or destinations are outside the service’s area. Future simulations should incorporate multi-modal travel and include transport hubs that facilitate inter-modal transfers to test whether the observed benefits can be expanded to the areas outside the ridesplitting service area.