scholarly journals Flow and Density Estimation in Grenoble Using Real Data

2021 ◽  
Vol 5 (1) ◽  
pp. 43
Author(s):  
Martin Rodriguez-Vega ◽  
Carlos Canudas-de-Wit ◽  
Hassen Fourati

This work deals with the Traffic State Estimation (TSE) problem for urban networks, using heterogeneous sources of data such as stationary flow sensors, Floating Car Data (FCD), and Automatic Vehicle Identifiers (AVI). A data-based flow and density estimation method is presented and tested using real traffic data. This work presents a study case applied to the downtown of the city of Grenoble in France, using the Grenoble Traffic Lab for urban networks (GTL-Ville), which is an experimental platform for real-time collection and analysis of traffic data.

2013 ◽  
Vol 748 ◽  
pp. 590-594
Author(s):  
Li Liao ◽  
Yong Gang Lu ◽  
Xu Rong Chen

We propose a novel density estimation method using both the k-nearest neighbor (KNN) graph and the potential field of the data points to capture the local and global data distribution information respectively. The clustering is performed based on the computed density values. A forest of trees is built using each data point as the tree node. And the clusters are formed according to the trees in the forest. The new clustering method is evaluated by comparing with three popular clustering methods, K-means++, Mean Shift and DBSCAN. Experiments on two synthetic data sets and one real data set show that our approach can effectively improve the clustering results.


2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Ying Zhuo ◽  
Lan Yan ◽  
Wenbo Zheng ◽  
Yutian Zhang ◽  
Chao Gou

Autonomous driving has become a prevalent research topic in recent years, arousing the attention of many academic universities and commercial companies. As human drivers rely on visual information to discern road conditions and make driving decisions, autonomous driving calls for vision systems such as vehicle detection models. These vision models require a large amount of labeled data while collecting and annotating the real traffic data are time-consuming and costly. Therefore, we present a novel vehicle detection framework based on the parallel vision to tackle the above issue, using the specially designed virtual data to help train the vehicle detection model. We also propose a method to construct large-scale artificial scenes and generate the virtual data for the vision-based autonomous driving schemes. Experimental results verify the effectiveness of our proposed framework, demonstrating that the combination of virtual and real data has better performance for training the vehicle detection model than the only use of real data.


2019 ◽  
Vol 9 (2) ◽  
pp. 1-10 ◽  
Author(s):  
Bharti Sharma ◽  
Sachin Kumar

Metropolitan road traffic mechanisms in developing countries are a critical problem due to fast motorization. The optimization of traffic control is one method to decrease this problem. In this study, a genetic algorithm was implemented to minimize delay at an intersection by finding red and green cycle intervals at an intersection. The objective function minimizes the delay at an intersection and increases progressive flows of traffic on roads. The study was done on real data collected from three t- intersections in the city of Hardwar, India. Traffic data for traffic flows, queue sizes, and traffic speed are collected using video detection systems in the study area. The digital images from the camera were analyzed in real time. The results show that the traffic control performance is improved up to 85% over existing algorithms proposed by the same author.


2012 ◽  
Vol 42 (2) ◽  
pp. 439-455 ◽  
Author(s):  
Saburo SAITO ◽  
Tran Ngoc HUY ◽  
Masakuni IWAMI ◽  
Takahiro SATO ◽  
Kosuke YAMASHIRO ◽  
...  

2021 ◽  
Vol 11 (11) ◽  
pp. 4757
Author(s):  
Aleksandra Bączkiewicz ◽  
Jarosław Wątróbski ◽  
Wojciech Sałabun ◽  
Joanna Kołodziejczyk

Artificial Neural Networks (ANNs) have proven to be a powerful tool for solving a wide variety of real-life problems. The possibility of using them for forecasting phenomena occurring in nature, especially weather indicators, has been widely discussed. However, the various areas of the world differ in terms of their difficulty and ability in preparing accurate weather forecasts. Poland lies in a zone with a moderate transition climate, which is characterized by seasonality and the inflow of many types of air masses from different directions, which, combined with the compound terrain, causes climate variability and makes it difficult to accurately predict the weather. For this reason, it is necessary to adapt the model to the prediction of weather conditions and verify its effectiveness on real data. The principal aim of this study is to present the use of a regressive model based on a unidirectional multilayer neural network, also called a Multilayer Perceptron (MLP), to predict selected weather indicators for the city of Szczecin in Poland. The forecast of the model we implemented was effective in determining the daily parameters at 96% compliance with the actual measurements for the prediction of the minimum and maximum temperature for the next day and 83.27% for the prediction of atmospheric pressure.


2020 ◽  
Vol 1651 ◽  
pp. 012060
Author(s):  
Fujian Feng ◽  
Shuang Liu ◽  
Yongzheng Pan ◽  
Xin He ◽  
Jiayin Wei ◽  
...  

2021 ◽  
Author(s):  
Masaki Uto

AbstractPerformance assessment, in which human raters assess examinee performance in a practical task, often involves the use of a scoring rubric consisting of multiple evaluation items to increase the objectivity of evaluation. However, even when using a rubric, assigned scores are known to depend on characteristics of the rubric’s evaluation items and the raters, thus decreasing ability measurement accuracy. To resolve this problem, item response theory (IRT) models that can estimate examinee ability while considering the effects of these characteristics have been proposed. These IRT models assume unidimensionality, meaning that a rubric measures one latent ability. In practice, however, this assumption might not be satisfied because a rubric’s evaluation items are often designed to measure multiple sub-abilities that constitute a targeted ability. To address this issue, this study proposes a multidimensional IRT model for rubric-based performance assessment. Specifically, the proposed model is formulated as a multidimensional extension of a generalized many-facet Rasch model. Moreover, a No-U-Turn variant of the Hamiltonian Markov chain Monte Carlo algorithm is adopted as a parameter estimation method for the proposed model. The proposed model is useful not only for improving the ability measurement accuracy, but also for detailed analysis of rubric quality and rubric construct validity. The study demonstrates the effectiveness of the proposed model through simulation experiments and application to real data.


2021 ◽  
Vol 3 (4) ◽  
pp. 295-311
Author(s):  
AbuRawi Mustafa ALMARKIYAH ◽  
Fouziya Alzarqani Ipraheem FADHLULLAH

Tripoli is a city of a Mediterranean Sea climate; this has contributed with some social and religious factors to affect the architectural and urban design, which all originally has come from the Islamic content. This study argues the climatic features of Tripoli in order to show the ways followed by the Libyan Muslim architect. In other words, these ways were used to adapt with the climate and create the demanding architectural treatments, which have served the building units. This is considered as a study case that can discuss the possibility of the climatic reflection on the walls. That is to say, the walls’ thickness, the type of the used substance in building, the substance’s properties, the type of roof used in covering the building units and the architectural design of the building as treatments achieved professionally by the architect in decreasing the heat in summer and increasing the heat in winter through the mass block. Additionally, the researchers have stated that Tripoli’s building design respected the privacy of the inhabitants and their isolation from the world outside their buildings. That is because they wanted to have their own cold spaces inside which were rich of light, air and shadow. As a result of the aforementioned considerations, the architectural buildings contained the uncovered space and the broken entrance to keep the privacy from the passengers and to protect the inhabitants from wind and sand. These were regarded as final solutions for the architectural and climatic problem. Further, this study illustrates the active role of using the planning including the architectural formations and the treatments of motion path. That is according to their width, their length, their form, their guidance and their direction change in order to make shadow and isolate the front of buildings. This also contributed to give the streets the northern wind which in turn helped to keep the air moving as long as possible to tone down the climatic influences. Moreover, the planning aimed to show its turn through analytical, architectural and documentary survey for realistic examples in the archeological registrar of the potential city treatments. These architectural elements were important in making the sustainable architecture in respect to the environment and human relaxation requirements. Finally, the researchers measured the following factors temperatures, wind, rain, and ratio humidity for variety of spaces in the city. That was followed by qualitative and quantitative statistical analysis supported by graphs


Author(s):  
M. А. Fursanov ◽  
A. A. Zalotoy

The issues of prospective operation of the city electric networks in the conditions of the MART GRID, which will be quite different as compared to the traditional understanding and approaches, are under consideration. This requires the selection and application of appropriate analytical criteria and approaches to assessment, analysis and control of the networks. With this regard the following criteria are recommended: in a particular case – the optimal (minimal) technological electric power consumption (losses), while in general – economically reasonable (minimal) cost value of electric power transmission. It should be also borne in mind that contemporary urban networks are actively saturated with distributed sources of small generation that have radically changed the structure of electrical networks; therefore, account for such sources is an absolutely necessary objective of management regimes of urban electric networks, both traditional and in associated with the SMART GRID. A case of the analysis and control of urban electric 10 kV networks with distributed small sources of generation has been developed and presented according to the theoretical criterion of minimum relative active power losses in the circuit as a control case. The conducted research makes it possible to determine the magnitude of the tolerance network mode from the point of the theoretical minimum. 


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