Transportation
This is a map-matching dataset, likely used for geospatial analysis and route mapping applications. The dataset is organized into multiple numbered segments, each potentially containing different routes, map regions, or tracking data.
Based on the name "map-matching-dataset" and the file structure, this dataset is probably used for developing or testing algorithms that match trajectory traces to road networks. Such datasets typically contain trajectory points, road network data, and ground truth matches for evaluation purposes.
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The UQTR dataset consists of 7838 real and synthetic images of the Université du Québec à Trois-Rivières (UQTR) campus road under normal and snow conditions. The image resolution is 1280×720. It includes lane labels in .txt files, where each row stores the set of points of a lane. The points are stored as x1 y1 x2 y2, as in the tutorial by Ruijin Liu, Zejian Yuan, Tie Liu, Zhiliang Xiong: Train and Test Your Custom Data.
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The TUROS-TS encompasses 5,357 Google Street View images with 8,775 traffic sign instances covering 9 categories and 28 classes. Three subsets of the dataset were created: test (10%-1050 images 579), validation (20% -1050 images), and training (70% - 3728 images). It is available upon request. If you want to train and test the data set. Please send an email to afef.zwidi@regim.usf.tn
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The Dash Cam Video Dataset is a comprehensive collection of real-world road footage captured across various Indian roads, focusing on lane conditions and traffic dynamics. Indian roads are often characterized by inconsistent lane markings, unstructured traffic flow, and frequent obstructions, making lane detection and traffic identification a challenging task for autonomous vehicle systems.
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The ADS-B track data, downloaded from the open Internet, contains four aircraft targets, namely B737, C17-1, C17-2, E35L, each target contains 110 complete tracks, totaling more than 100,000 track points. The data sets of 4 aircraft targets were randomly divided into training sets, verification sets and test sets according to the ratio of 8:1:1.
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Vehicle-to-everything (V2X) collaborative perception has emerged as a promising solution to address the limitations of single-vehicle perception systems.
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An In-depth Analysis of Thermal Management Systems for Wireless Charging in Electric Vehicles
1. Introduction
Wireless charging technology is revolutionizing electric vehicles (EVs) by offering a convenient alternative to traditional charging. This technology enhances user experience and supports the growth of autonomous EV fleets. As electrification of transportation accelerates, effective thermal management becomes crucial to address heat generation during inductive power transfer, ensuring system reliability and longevity.
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Self-Aligning IPT Pads for Efficient High-Power Wireless Charging for EV
Introduction
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The project focuses on the development and evaluation of an innovative magnetic coupler designed for in-wheel wireless charging systems in electric vehicles (EVs). This technology aims to enhance the efficiency and convenience of EV charging by integrating the charging mechanism directly into the vehicle's wheels. The magnetic coupler utilizes principles of wireless power transfer (WPT) through magnetic induction and resonance, allowing for effective energy transfer even with misalignment and varying distances between the transmitter and receiver coils.
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This paper introduces an innovative inductive power transfer (IPT) system tailored for electric vehicle (EV) charging, emphasizing dynamic IPT implementations that utilize electrified roadways with integrated couplers. To tackle the challenges of complexity and reliability associated with current systems, we propose a Push-Pull Driven Coupler Array (PPCA) architecture. This design employs only N+1 switches to independently energize N primary couplers, enabling simultaneous activation of multiple couplers while mitigating current stress on the switches.
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