- Infrastructure Engineering - Research Publications
Infrastructure Engineering - Research Publications
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ItemAnalysis of an Ad-hoc Platoon Formation and Dissolution Strategy on a Multi-lane Highway.Maiti, S ; Winter, S ; Kulik, L ; Sarkar, S (University of Auckland, 2019-01-01)Vehicle platooning has become popular in the recent Intelligent Transportation System (ITS) research. The literature typically assumes a planned formation and dissolution of platoons, mostly at source and destination. In contrast, this research considers platoons that can be formed on the fly. We investigate a greedy type of platoon formation with no particular order of destinations of the platoon members. This greedy formation allows a quick formation of the platoon but imposes an overhead of platoon rebuild cost when platoon members leave. The question arises whether this greedy formation and dissolution of platoons can preserve the original fuel benefit of platooning. To investigate this question, this research implements such a strategy and provides a generic guideline for fuel-efficient ad-hoc platooning
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ItemModelling Uncertainty of Single Image Indoor Localisation Using a 3D Model and Deep LearningAcharya, D ; Singha Roy, S ; Khoshelham, K ; Winter, S (ISPRS, 2019-05-29)Many current indoor localisation approaches need an initial location at the beginning of localisation. The existing visual approaches to indoor localisation perform a 3D reconstruction of the indoor spaces beforehand, for determining this initial location, which is challenging for large indoor spaces. In this research, we present a visual approach for indoor localisation that is eliminating the requirement of any image-based reconstruction of indoor spaces by using a 3D model. A deep Bayesian convolutional neural network is fine-tuned with synthetic images generated from a 3D model to estimate the camera pose of real images. The uncertainty of the estimated camera poses is modelled by sampling the outputs of the Bayesian network fine-tuned with synthetic images. The results of the experiments indicate that a localisation accuracy of 2 metres can be achieved using the proposed approach.
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ItemInitial Analysis of Simple Where-Questions and Human-Generated AnswersHamzei, E ; Winter, S ; Tomko, M (LIPIcs, 2019)Geographic questions are among the most frequently asked questions in Web search and question answering systems. While currently responses to the questions are machine-generated by document/snippet retrieval, in the future these responses will need to become more similar to answers provided by humans. Here, we have analyzed human answering behavior as response to simple where questions (i.e., where questions formulated only with one toponym) in terms of type, scale, and prominence of the places referred to. We have used the largest available machine comprehension dataset, MS-MARCO v2.1. This study uses an automatic approach for extraction, encoding and analysis of the questions and answers. Here, the distribution analysis are used to describe the relation between questions and their answers. The results of this study can inform the design of automatic question answering systems for generating useful responses to where questions.
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ItemThe grass is greener on the other side: understanding the effects of green spaces on Twitter user sentimentsLim, KH ; Lee, K ; Kendal, D ; Rashidi, L ; Naghi Zadeh Kakhki, E ; Winter, S ; Vasardani, M (ACM Press, 2018)Green spaces are believed to improve the well-being of users in urban areas. While there are urban research exploring the emotional benefits of green spaces, these works are based on user surveys and case studies, which are typically small in scale, intrusive, time-intensive and costly. In contrast to earlier works, we utilize a non-intrusive methodology to understand green space effects at large-scale and in greater detail, via digital traces left by Twitter users. Using this methodology, we perform an empirical study on the effects of green spaces on user sentiments and emotions in Melbourne, Australia and our main findings are: (i) tweets in green spaces evoke more positive and less negative emotions, compared to those in urban areas; (ii) each season affects various emotion types differently; (iii) there are interesting changes in sentiments based on the hour, day and month that a tweet was posted; and (iv) negative sentiments are typically associated with large transport infrastructures such as train interchanges, major road junctions and railway tracks. The novelty of our study is the combination of psychological theory, alongside data collection and analysis techniques on a large-scale Twitter dataset, which overcomes the limitations of traditional methods in urban research.
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ItemActivity-based Mobility ProfilingGhosh, S ; Ghosh, SK ; Das, RD ; Winter, S (ACM Press, 2018)Several studies have shown that the spatio-temporal mobility traces of human movements can be used to identify an individual. However, this work presents a novel framework for activity-based mobility profiling of individuals using only the temporal information. The proposed framework is conducive to model individuals' activity patterns in temporal scale, and quantifies the uniqueness measures based on certain temporal features of the activity sequence.
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ItemStarting to talk about placeSTIRLING, LESLEY ; CAVEDON, LAWRENCE ; RICHTER, DANIELA ; Winter, Stephen ; KEALY, ALLISON ; DUCKHAM, MATT ; RAJABIFARD, ABBAS ; RICHTER, KAI-FLORIAN ; Baldwin, Tim ( 2011)
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ItemLocation-based mobile games for spatial knowledge acquisitionWinter, S ; Richter, KF ; Baldwin, T ; Cavedon, L ; Stirling, L ; Duckham, M ; Kealy, A ; Rajabifard, A (CEMob2011, 2011-01-01)