9 research outputs found

    Impact analysis of accidents on the traffic flow based on massive floating car data

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    The wide usage of GPS-equipped devices enables the mass recording of vehicle movement trajectories describing the movement behavior of the traffic participants. An important aspect of the road traffic is the impact of anomalies, like accidents, on traffic flow. Accidents are especially important as they contribute to the the aspects of safety and also influence travel time estimations. In this paper, the impact of accidents is determined based on a massive GPS trajectory and accident dataset. Due to the missing precise date of the accidents in the data set used, first, the date of the accident is estimated based on the speed profile at the accident time. Further, the temporal impact of the accident is estimated using the speed profile of the whole day. The approach is applied in an experiment on a one month subset of the datasets. The results show that more than 72% of the accident dates are identified and the impact on the temporal dimension is approximated. Moreover, it can be seen that accidents during the rush hours and on high frequency road types (e.g. motorways, trunks or primaries) have an increasing effect on the impact duration on the traffic flow

    Impact of statins based on high-risk plaque features on coronary plaque progression in mild stenosis lesions: results from the PARADIGM study

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    AimsTo investigate the impact of statins on plaque progression according to high-risk coronary atherosclerotic plaque (HRP) features and to identify predictive factors for rapid plaque progression in mild coronary artery disease (CAD) using serial coronary computed tomography angiography (CCTA).Methods and resultsWe analyzed mild stenosis (25–49%) CAD, totaling 1432 lesions from 613 patients (mean age, 62.2 years, 63.9% male) and who underwent serial CCTA at a ≥2 year inter-scan interval using the Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography Imaging (NCT02803411) registry. The median inter-scan period was 3.5 ± 1.4 years; plaques were quantitatively assessed for annualized percent atheroma volume (PAV) and compositional plaque volume changes according to HRP features, and the rapid plaque progression was defined by the ≥90th percentile annual PAV. In mild stenotic lesions with ≥2 HRPs, statin therapy showed a 37% reduction in annual PAV (0.97 ± 2.02 vs. 1.55 ± 2.22, P = 0.038) with decreased necrotic core volume and increased dense calcium volume compared to non-statin recipient mild lesions. The key factors for rapid plaque progression were ≥2 HRPs [hazard ratio (HR), 1.89; 95% confidence interval (CI), 1.02–3.49; P = 0.042], current smoking (HR, 1.69; 95% CI 1.09–2.57; P = 0.017), and diabetes (HR, 1.55; 95% CI, 1.07–2.22; P = 0.020).ConclusionIn mild CAD, statin treatment reduced plaque progression, particularly in lesions with a higher number of HRP features, which was also a strong predictor of rapid plaque progression. Therefore, aggressive statin therapy might be needed even in mild CAD with higher HRPs.Cardiolog

    Towards integration of LADM and CityGML for the cadastral system of Turkey

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    With the rapid urbanization and the dynamics in land transactions, Turkish cadastre, as in many other countries, is facing challenges in the daily recording of sales, donations, taxations, and mortgages on land. Especially with the modern constructions and complex interrelationships of rights, restrictions, and responsibilities (RRR), the third dimension should not be forgotten. In this context, the design of a new cadastre data model for Turkey is essential. Inspired by this need, with this study, we aim in proposing a new cadastre model based on international standards such as Land Administration Data Model (LADM) and CityGML. LADM represents the legal and administrative aspects of the cadastral objects but does not show the semantic and 3D geometrical representation of physical cadastral objects which are required for the process of 3D cadastre. Therefore, in the paper, we propose an Application Domain Extension (ADE) for the cadastral objects that expands the integration of LADM and CityGML data model with the legal and administrative concepts defined in the Turkish Law. The study presents a detailed overview of the Turkish legal cadastre system and a proposal for its physical realization based on international standards. In addition, the developed ADE is also valuable for cadastral services undertaken by the General Directorate of Land Registry and Cadastre (GDLRC). It could also be used as a basis of a 3D national data standard for cadastral information systems

    Urban 3D modelling methods: A state-of-the-art review

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    As urbanisation accelerates, the urban landscape reshapes at a fast pace. Consequently, the urban built environment continuously evolves horizontally as well as vertically. However, more attention in the field of spatial analysis is given to horizontal dynamics, despite the importance of geoinformation in the vertical dimension. 3D modelling methods have gained popularity due to their powerful capability of capturing and analysing geoinformation in the vertical dimension and visualising objects lifelike in the urban built environment. Various urban applications with diverse 3D modelling methods at different research scales and purposes have emerged. However, there is no systematic overview of these different modelling methods. Therefore, it is imperative to provide an up-to-date review of these advances. In this paper, we aim to review urban 3D modelling methods widely used in the prior 5-year period (2015–2020). Our analysis focuses on five attributes, i.e., basic characteristics, data requirements, technical requirements, users requirements and ethical considerations. The discussion presents the current status of 3D modelling methods – a wide range of applications yet with substantial development potential. This paper closes with insights for future work regarding the necessities of 3D data structure support as well as interdisciplinary research, specifically for big data management and integration

    Investigating standardized 3D input data for solar photovoltaic potentials in the Netherlands

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    This paper presents our contribution to the development of a standardized 3D input data model for solar photovoltaic potential estimation. Presently, different input data and processing steps influence the calculation for estimating the potential of solar energy in the Netherlands. The variety in characteristics of input data and issues with temporal accuracy extracted from the national registers and databases makes it challenging to obtain a consistent and reliable result. To address this issue, we created a point cloud dataset that integrated from LiDAR point cloud and dense image matching which is complete, recent and positionally accurate. Furthermore, we made a 3D building model from the integrated point cloud and identified the effect of finer resolution in the photovoltaic potential analysis

    Point cloud based 3D models for agent based simulations in social distancing and evacuation

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    Point clouds serve as the raw material for various models, such as Building Information Models (BIM). In this work, we investigate the reconstruction steps needed to create models that can be utilized directly for agent-based simulations. The input data for the reconstruction is captured with an indoor mobile mapping system. To show the prominence of this idea, we run social distancing and evacuation simulations on the reconstructed models. The simulations are run with multiple agents using a vision-based pedestrian model and A∗-based path finding algorithm. The limitations of this approach are discussed. The video of the simulation is shared with the audience. Link to the video: https://youtu.be/r2D3IxXt7L
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