Infrastructure Engineering - Research Publications
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ItemThe Impact of Flexible Platoon Formation Operations(Institute of Electrical and Electronics Engineers (IEEE), 2020-06)Vehicle platooning, a coordinated vehicle movement strategy, has been proposed to address a range of current transport challenges such as traffic congestion, road safety, energy consumption and pollution. While the current literature mainly focuses on platoon control strategies and intra-platoon communication, comparatively little work is done on how to form these platoons. Literature assumes platoon formation by tail merge which is sufficient only for planned formation on a ramp or at a ramp-highway junction. In this article we study the impact of three different merge operations, namely front, middle, and tail merge. The efficiency of these operations is analyzed under different scenarios, varying the vehicles speed adjustment strategy, traffic density, and the density of mergeable vehicles. The impact of the merge operations is represented in terms of merge time, merge distance, average traffic speed, and merge success rate. Our experiments show that in an ideal no traffic scenario, the middle merge is costlier in terms of merge time for the same merge distance whereas in the presence of traffic middle merge helps is quick platoon formation on an average in a higher traffic density in particular. This insight should provide a more flexible toolkit for planning a platoon formation.
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ItemRIM: a ray intersection model for the analysis of the between relationship of spatial objects in a 2D plane(Taylor & Francis, 2020-07-07)The term between is frequently used to describe spatial arrangements of objects where one described core object is positioned in the space bounded by two or more peripheral objects. As such, the relation between involves spatial configurations of at least three spatial objects. However, most of the existing qualitative spatial reasoning models focus only on binary spatial relations, and there is currently no single model that enables adequate reasoning about this ternary spatial relation. This paper proposes a novel model for expressing nuanced spatial relationships between three spatial objects, called the Ray Intersection Model (RIM). RIM evaluates rays cast between two peripheral spatial objects, and their topological relations with the core object to determine its position relative to the peripheral objects. RIM leaves the binary classification of the core object as between/not between to the user and application context. Although RIM supports all types of 2D spatial objects (i.e. points, lines, and polygons), its expressiveness is demonstrated in this paper by analyzing the total of 28 distinct configurations of triplets of polygon objects in a 2D plane. RIM has been computationally implemented and we demonstrate how RIM can be applied to analyze the arrangements of buildings at a university campus.
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ItemExtracting interrogative intents and concepts from geo-analytic questions(Copernicus GmbH, 2020)Understanding syntactic and semantic structure of geographic questions is a necessary step towards true geographic question-answering (GeoQA) machines. The empirical basis for the understanding of the capabilities expected from GeoQA systems are geographic question corpora. Available corpora in English have been mostly drawn from generic Web search logs or limited user studies, supporting the focus of GeoQA systems on retrieving factoids: factual knowledge about particular places and everyday processes. Yet, the majority of questions enquired about in the spatial sciences go beyond simple place facts, with more complex analytical intents informing the questions. In this paper, we introduce a new corpus of geo-analytic questions drawn from English textbooks and scientific articles. We analyse and compare this corpus with two general-purpose GeoQA corpora in terms of grammatical complexity and semantic concepts, using a new parsing method that allows us to differentiate and quantify patterns of a question’s intent.
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ItemService quality monitoring in confined spaces through mining Twitter data(UNIV MAINE, 2020-01-01)Promoting public transport depends on adapting effective tools for concurrent monitoring of perceived service quality. Social media feeds, in general, provide an opportunity to ubiquitously look for service quality events, but when applied to confined geographic area such as a transport node, the sparsity of concurrent social media data leads to two major challenges. Both the limited number of social media messages—leading to biased machine-learning—and the capturing of bursty events in the study period considerably reduce the effectiveness of general event detection methods. In contrast to previous work and to face these challenges, this paper presents a hybrid solution based on a novel finetuned BERT language model and aspect-based sentiment analysis. BERT enables extracting aspects from a limited context, where traditional methods such as topic modeling and word embedding fail. Moreover, leveraging aspect-based sentiment analysis improves the sensitivity of event detection. Finally, the efficacy of event detection is further improved by proposing a statistical approach to combine frequency-based and sentiment-based solutions. Experiments on a real-world case study demonstrate that the proposed solution improves the effectiveness of event detection compared to state-of-the-art approaches.
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ItemThe impact of urban road network morphology on pedestrian wayfinding behavior(University of Maine, 2020-01-01)During wayfinding pedestrians do not always choose the shortest available route. Instead, route choices are guided by several well-known wayfinding strategies or heuristics. These heuristics minimize cognitive effort and usually lead to satisfactory route choices. Our previous study evaluated the costs of four well-known pedestrian wayfinding heuristics and their variation across nine network morphologies. It was observed that the variation in the cost of these wayfinding heuristics increased with an increase in the irregularity of the network, indicating that people may opt for more diverse heuristics while walking through relatively regular networks, and may prefer specific heuristics in the relatively irregular ones. The study presented here aims to investigate this claim by comparing simulated routes with observed pedestrian trajectories in Beijing and Melbourne, two cities at opposite ends of the regularity spectrum. We found that the values of mean route length and mean Network Hausdorff Distance for walking trips made in Melbourne were consistently lesser than the corresponding values obtained in Beijing. Also, across both the cities, we found that while there was minimal variation in the popularity of heuristics overall, in cases where different heuristics produced dissimilar routes, the shortest leg first strategy and the least angle strategy were more popular.
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ItemUsing Georeferenced Twitter Data to Estimate Pedestrian Traffic in an Urban Road Network(Dagstuhl Publishing, 2020-09-01)Since existing methods to estimate the pedestrian activity in an urban area are data-intensive, we ask the question whether just georeferenced Twitter data can be a viable proxy for inferring pedestrian activity. Walking is often the mode of the last leg reaching an activity location, from where, presumably, the tweets originate. This study analyses this question in three steps. First, we use correlation analysis to assess whether georeferenced Twitter data can be used as a viable proxy for inferring pedestrian activity. Then we adopt standard regression analysis to estimate pedestrian traffic at existing pedestrian sensor locations using georeferenced tweets alone. Thirdly, exploiting the results above, we estimate the hourly pedestrian traffic counts at every segment of the study area network for every hour of every day of the week. Results show a fair correlation between tweets and pedestrian counts, in contrast to counts of other modes of travelling. Thus, this method contributes a non-data-intensive approach for estimating pedestrian activity. Since Twitter is an omnipresent, publicly available data source, this study transcends the boundaries of geographic transferability and scalability, unlike its more traditional counterparts.
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ItemA Multi-Camera Tracker for Monitoring Pedestrians in Enclosed Environments(IEEE, 2020)Multi-camera pedestrians tracking is a challenging computer vision task. We propose a multi-camera tracker for monitoring pedestrians in an enclosed shopping environment. We assess the performance of the multi-camera tracker in a case study, tracking customers in a food and speciality market hall. Our multi-camera tracker tracks customers' walking between the stalls in the market. The information is useful for market management, visitor safety, and other potential application areas.
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ItemToward identifying the critical mass in spatial two-sided markets(Sage Publications, 2020-11-01)Unlike their nonspatial counterparts, spatial multi-sided platforms are matchmaking platforms with an additional layer of complexity: their customers expect to meet in space, not only virtually. This additional challenge will be studied in this paper in the context of a two-sided ride-sharing platform, which serves drivers and passengers. As with any two-sided platform, there is an interdependence between both groups of customers: More drivers are more attractive for passengers, and vice versa. This interdependence creates the old chicken-and-egg problem, only that here drivers and passengers need to be matched not for a virtual transaction, but by their ability to meet physically and travel jointly. We argue, and illustrate by simulations, that in spatial multi-sided markets there is not a single critical mass frontier that needs to be reached in order to make the system self-sustained (as in nonspatial markets), and that this frontier is varying from one location to the next, depending on the density and distribution of the demand and supply over space and time. Identification of the critical mass frontier will allow for better evaluation of implementation policies and regulations.
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ItemWayfinding and navigation research for sustainable transport(University of Maine, 2020)Spatial information science contributes to the foundations of sustainable transport development. This article focuses especially on the role that research on human wayfinding and navigation plays when it comes to designing digital connectivity and autonomy in urban transport.
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ItemOrigin-Destination Flow Estimation from Link Count Data Only(MDPI, 2020-09)All established models in transportation engineering that estimate the numbers of trips between origins and destinations from vehicle counts use some form of a priori knowledge of the traffic. This paper, in contrast, presents a new origin-destination flow estimation model that uses only vehicle counts observed by traffic count sensors; it requires neither historical origin-destination trip data for the estimation nor any assumed distribution of flow. This approach utilises a method of statistical origin-destination flow estimation in computer networks, and transfers the principles to the domain of road traffic by applying transport-geographic constraints in order to keep traffic embedded in physical space. Being purely stochastic, our model overcomes the conceptual weaknesses of the existing models, and additionally estimates travel times of individual vehicles. The model has been implemented in a real-world road network in the city of Melbourne, Australia. The model was validated with simulated data and real-world observations from two different data sources. The validation results show that all the origin-destination flows were estimated with a good accuracy score using link count data only. Additionally, the estimated travel times by the model were close approximations to the observed travel times in the real world.