{"id":33138,"date":"2026-02-25T13:49:47","date_gmt":"2026-02-25T05:49:47","guid":{"rendered":"https:\/\/aiportek.com\/?p=33138"},"modified":"2026-02-25T14:05:16","modified_gmt":"2026-02-25T06:05:16","slug":"simdata-aisim-high-fidelity-autonomous-driving-dataset","status":"publish","type":"post","link":"https:\/\/aiportek.com\/en\/simdata-aisim-high-fidelity-autonomous-driving-dataset\/","title":{"rendered":"HONGKE Solutions] SimData High-Fidelity Virtual Dataset - aiSim-based Multi-Sensor Sensing Data Solution for Autonomous Vehicles"},"content":{"rendered":"<div data-elementor-type=\"wp-post\" data-elementor-id=\"33138\" class=\"elementor elementor-33138\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-303a47ec elementor-section-stretched elementor-section-full_width elementor-section-height-min-height elementor-section-content-middle elementor-section-height-default elementor-section-items-middle\" data-id=\"303a47ec\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;,&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-27d5e225\" data-id=\"27d5e225\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-inner-section elementor-element elementor-element-4e369ae3 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"4e369ae3\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-inner-column elementor-element elementor-element-6555484e\" data-id=\"6555484e\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-397ef20e elementor-widget elementor-widget-heading\" data-id=\"397ef20e\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Hongke's latest articles<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<div class=\"elementor-element elementor-element-4b5c0d9b elementor-absolute elementor-widget elementor-widget-heading\" data-id=\"4b5c0d9b\" data-element_type=\"widget\" data-settings=\"{&quot;_position&quot;:&quot;absolute&quot;}\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">HongKe<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-6d18033c elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"6d18033c\" data-element_type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-1f96cecf\" data-id=\"1f96cecf\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-fd50b9b elementor-widget elementor-widget-text-editor\" data-id=\"fd50b9b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d303089 elementor-widget elementor-widget-text-editor\" data-id=\"d303089\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<section class=\"elementor-section elementor-inner-section elementor-element elementor-element-4b0e7b4e elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"4b0e7b4e\" data-element_type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-inner-column elementor-element elementor-element-7a4b7cfc\" data-id=\"7a4b7cfc\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-79a3214 elementor-widget elementor-widget-heading\" data-id=\"79a3214\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">HONGKE Solution\u3011Automatic Driving Sensory Data Costs Too Much? It's time to use high-fidelity virtual data.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-226f412 elementor-widget elementor-widget-post-info\" data-id=\"226f412\" data-element_type=\"widget\" data-widget_type=\"post-info.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ul class=\"elementor-inline-items elementor-icon-list-items elementor-post-info\">\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item elementor-repeater-item-2358f4d elementor-inline-item\" itemprop=\"author\">\n\t\t\t\t\t\t<a href=\"https:\/\/aiportek.com\/en\/author\/hongketechnology\/\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-far-user-circle\" viewbox=\"0 0 496 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M248 104c-53 0-96 43-96 96s43 96 96 96 96-43 96-96-43-96-96-96zm0 144c-26.5 0-48-21.5-48-48s21.5-48 48-48 48 21.5 48 48-21.5 48-48 48zm0-240C111 8 0 119 0 256s111 248 248 248 248-111 248-248S385 8 248 8zm0 448c-49.7 0-95.1-18.3-130.1-48.4 14.9-23 40.4-38.6 69.6-39.5 20.8 6.4 40.6 9.6 60.5 9.6s39.7-3.1 60.5-9.6c29.2 1 54.7 16.5 69.6 39.5-35 30.1-80.4 48.4-130.1 48.4zm162.7-84.1c-24.4-31.4-62.1-51.9-105.1-51.9-10.2 0-26 9.6-57.6 9.6-31.5 0-47.4-9.6-57.6-9.6-42.9 0-80.6 20.5-105.1 51.9C61.9 339.2 48 299.2 48 256c0-110.3 89.7-200 200-200s200 89.7 200 200c0 43.2-13.9 83.2-37.3 115.9z\"><\/path><\/svg>\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text elementor-post-info__item elementor-post-info__item--type-author\">\n\t\t\t\t\t\t\t\t\t\tHongKeTechnology\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t<\/li>\n\t\t\t\t<li class=\"elementor-icon-list-item elementor-repeater-item-a689c23 elementor-inline-item\" itemprop=\"datePublished\">\n\t\t\t\t\t\t<a href=\"https:\/\/aiportek.com\/en\/2026\/02\/25\/\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-calendar\" viewbox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M12 192h424c6.6 0 12 5.4 12 12v260c0 26.5-21.5 48-48 48H48c-26.5 0-48-21.5-48-48V204c0-6.6 5.4-12 12-12zm436-44v-36c0-26.5-21.5-48-48-48h-48V12c0-6.6-5.4-12-12-12h-40c-6.6 0-12 5.4-12 12v52H160V12c0-6.6-5.4-12-12-12h-40c-6.6 0-12 5.4-12 12v52H48C21.5 64 0 85.5 0 112v36c0 6.6 5.4 12 12 12h424c6.6 0 12-5.4 12-12z\"><\/path><\/svg>\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text elementor-post-info__item elementor-post-info__item--type-date\">\n\t\t\t\t\t\t\t\t\t\t<time>February 25, 2026<\/time>\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t<\/li>\n\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c027dd7 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"c027dd7\" data-element_type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9aba933 elementor-widget elementor-widget-heading\" data-id=\"9aba933\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-small\">01 Preamble<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d3381e7 elementor-widget elementor-widget-text-editor\" data-id=\"d3381e7\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p data-start=\"294\" data-end=\"421\">During the development of an automated driving perception system, the model performance is highly dependent on the<strong data-start=\"319\" data-end=\"336\">Large-scale, high-quality perceptual datasets<\/strong>The following are some of the public datasets widely used in the industry. Publicly available datasets that are currently widely used by the industry include <strong data-start=\"354\" data-end=\"391\">KITTI, nuScenes, Waymo Open Dataset<\/strong> These datasets lay an important foundation for the research and implementation of automatic driving algorithms.<\/p><p data-start=\"423\" data-end=\"506\">However, building real-world perceptual datasets is not an easy task - not only does it require a significant investment in manpower, resources, and time, but it also faces multiple challenges such as limited data acquisition, privacy and compliance requirements, time-consuming labeling, and difficulty in accessing extreme scenarios.<\/p><p data-start=\"508\" data-end=\"620\">In this context.<strong data-start=\"514\" data-end=\"526\">High fidelity virtual dataset<\/strong>It is gradually becoming an important development direction for the research of automatic driving perception algorithms. The virtual data generated by the simulation platform can not only rapidly expand the data scale, but also flexibly construct complex traffic scenes, adverse weather conditions and rare events, providing more comprehensive and diversified training samples for the model.<\/p><p data-start=\"622\" data-end=\"661\">With this in mind, HONGKE officially launches a new high fidelity virtual data set -- the <strong data-start=\"647\" data-end=\"658\">SimData<\/strong>The<\/p><p data-start=\"663\" data-end=\"767\">SimData relies on <strong data-start=\"674\" data-end=\"705\">Highly accurate physical modeling and realistic visual rendering capabilities of the aiSim simulation platform.<\/strong>It can generate multi-sensor synchronized data (including Camera, LiDAR, Radar, IMU, etc.) to achieve highly consistent multi-modal characteristics with real-world data.<\/p><p data-start=\"769\" data-end=\"865\">SimData's data structure strictly follows <strong data-start=\"787\" data-end=\"807\">nuScenes Data Set Format Specification<\/strong>You can directly use the official <strong data-start=\"816\" data-end=\"835\">nuscenes-devkit<\/strong> Tools are parsed and visualized, significantly reducing the threshold and integration costs for developers.<\/p><p data-start=\"867\" data-end=\"952\">In this article, we will introduce the core features and construction process of SimData, and demonstrate its application performance in a typical sensing task; the official version of SimData and the related comparison test report will be released in the near future, so please stay tuned to the latest news of Hongke.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0537c77 elementor-widget elementor-widget-heading\" data-id=\"0537c77\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-small\">02 SimData Organization Process<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d84da33 elementor-widget elementor-widget-heading\" data-id=\"d84da33\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-small\">Sensor Layout<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5a30996 elementor-widget elementor-widget-text-editor\" data-id=\"5a30996\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p data-start=\"990\" data-end=\"1054\">In the aiSim simulation platform, we strictly reproduce the sensor layout design of the nuScenes dataset to ensure a high degree of consistency in the data structure and multimode synchronization characteristics.<\/p><p data-start=\"1056\" data-end=\"1065\">The simulation vehicle is configured as follows:<\/p><ul><li data-start=\"1069\" data-end=\"1084\">6-way Surround View Camera (Camera)<\/li><li data-start=\"1087\" data-end=\"1099\">5 Radar<\/li><li data-start=\"1102\" data-end=\"1116\">1 x Laser Radar (LiDAR)<\/li><li data-start=\"1119\" data-end=\"1133\">1 Inertial Measurement Unit (IMU)<\/li><li data-start=\"1136\" data-end=\"1148\">1 Positioning System (GPS)<\/li><\/ul><p data-start=\"1150\" data-end=\"1215\">The sampling frequency of the camera and the radar are <strong data-start=\"1165\" data-end=\"1174\">40 Hz<\/strong>The sampling frequency of the laser radar is <strong data-start=\"1185\" data-end=\"1194\">80 Hz<\/strong>It is designed to meet the needs of synchronized multi-sensor acquisition with high time accuracy.<\/p><p data-start=\"1217\" data-end=\"1235\">The spatial layout and orientation of each sensor is shown below:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4b4394c elementor-widget elementor-widget-image\" data-id=\"4b4394c\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"687\" height=\"184\" src=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/\u5c4f\u5e55\u622a\u56fe-2026-02-25-135014.png\" class=\"attachment-large size-large wp-image-33142\" alt=\"\" srcset=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/\u5c4f\u5e55\u622a\u56fe-2026-02-25-135014.png 687w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/\u5c4f\u5e55\u622a\u56fe-2026-02-25-135014-300x80.png 300w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/\u5c4f\u5e55\u622a\u56fe-2026-02-25-135014-18x5.png 18w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/\u5c4f\u5e55\u622a\u56fe-2026-02-25-135014-600x161.png 600w\" sizes=\"(max-width: 687px) 100vw, 687px\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\">Overall view (left), front view (right)<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-77732a9 elementor-widget elementor-widget-image\" data-id=\"77732a9\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"672\" height=\"186\" src=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/\u5c4f\u5e55\u622a\u56fe-2026-02-25-135027.png\" class=\"attachment-large size-large wp-image-33143\" alt=\"\" srcset=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/\u5c4f\u5e55\u622a\u56fe-2026-02-25-135027.png 672w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/\u5c4f\u5e55\u622a\u56fe-2026-02-25-135027-300x83.png 300w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/\u5c4f\u5e55\u622a\u56fe-2026-02-25-135027-18x5.png 18w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/\u5c4f\u5e55\u622a\u56fe-2026-02-25-135027-600x166.png 600w\" sizes=\"(max-width: 672px) 100vw, 672px\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\">Left view (left), top view (right)<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-30f86b3 elementor-widget elementor-widget-heading\" data-id=\"30f86b3\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-small\">Coordinate system description<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c12e546 elementor-widget elementor-widget-text-editor\" data-id=\"c12e546\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p data-start=\"1316\" data-end=\"1436\">Unlike nuScenes, all sensors in SimData use the <strong data-start=\"1350\" data-end=\"1377\">FLU (Forward-Left-Up) Coordinate System<\/strong>and in the nuScenes dataset, the camera sensor uses the <strong data-start=\"1405\" data-end=\"1435\">RDF (Right-Down-Forward) Coordinate System<\/strong>The<\/p><p data-start=\"1438\" data-end=\"1495\">During the data construction process, all annotation files were subjected to rigorous coordinate conversion and alignment to ensure that the logical definitions were fully consistent with nuScenes.<\/p><p data-start=\"1497\" data-end=\"1557\">As a result, users do not need to deal with additional coordinate differences when applying SimData, and their data parsing process and development experience is consistent with nuScenes.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4f5c3d7 elementor-widget elementor-widget-image\" data-id=\"4f5c3d7\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"1024\" height=\"533\" src=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/640-1024x533.webp\" class=\"attachment-large size-large wp-image-33141\" alt=\"\" srcset=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/640-1024x533.webp 1024w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/640-300x156.webp 300w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/640-768x400.webp 768w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/640-18x9.webp 18w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/640-600x312.webp 600w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/640.webp 1080w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-23727c6 elementor-widget elementor-widget-heading\" data-id=\"23727c6\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-small\">Data Structure Design<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a0f440c elementor-widget elementor-widget-text-editor\" data-id=\"a0f440c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p data-start=\"1576\" data-end=\"1652\">The SimData dataset is fully aligned with nuScenes in terms of overall architecture. For developers who are already familiar with nuScenes, they can get started quickly without additional adaptation or learning costs.<\/p><p data-start=\"1654\" data-end=\"1682\">The overall directory structure is as follows (consistent with the nuScenes organization):<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4391f38 elementor-widget elementor-widget-image\" data-id=\"4391f38\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"375\" height=\"517\" src=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/640-1.webp\" class=\"attachment-large size-large wp-image-33139\" alt=\"\" srcset=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/640-1.webp 375w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/640-1-218x300.webp 218w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/640-1-9x12.webp 9w\" sizes=\"(max-width: 375px) 100vw, 375px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cd09043 elementor-widget elementor-widget-text-editor\" data-id=\"cd09043\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p data-start=\"1696\" data-end=\"1709\"><strong>maps folder<\/strong><\/p><p data-start=\"1711\" data-end=\"1749\">Holds all the high-resolution map image files used in the dataset, which are used to provide geolocation information and scene context references.<\/p><p data-start=\"1751\" data-end=\"1767\"><strong>samples folder<\/strong><\/p><p data-start=\"1769\" data-end=\"1786\">Stores critical frame data for all types of sensors, including:<\/p><ul><li data-start=\"1790\" data-end=\"1804\">6-way camera image (.jpg)<\/li><li data-start=\"1807\" data-end=\"1820\">5 Lutra Dot Cloud (.pcd)<\/li><li data-start=\"1823\" data-end=\"1838\">1-way laser radar point cloud (.bin)<\/li><\/ul><p data-start=\"1840\" data-end=\"1864\">\u6bcf <strong data-start=\"1842\" data-end=\"1851\">0.5 seconds<\/strong> Saves a frame as a keyframe.<\/p><p data-start=\"1866\" data-end=\"1881\"><strong>sweeps folder<\/strong><\/p><p data-start=\"1883\" data-end=\"1916\">Saves continuous sensor data except for key frames, which is used to construct timing information and multi-frame fusion tasks.<\/p><p data-start=\"1918\" data-end=\"1933\"><strong>v1.0-* Folder<\/strong><\/p><p data-start=\"1935\" data-end=\"1968\">Storage of sensor annotations and metadata information, all utilizing <code data-start=\"1954\" data-end=\"1961\">.json<\/code> Format, Coverage:<\/p><ul><li>Time Stamp<\/li><li>Attitude Parameters<\/li><li>Labeling<\/li><li>Scene Description<\/li><\/ul><p data-start=\"1998\" data-end=\"2025\">The JSON association structure is identical to that of nuScenes.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b96e12e elementor-widget elementor-widget-image\" data-id=\"b96e12e\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"980\" height=\"1024\" src=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/640-2-980x1024.webp\" class=\"attachment-large size-large wp-image-33140\" alt=\"\" srcset=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/640-2-980x1024.webp 980w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/640-2-287x300.webp 287w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/640-2-768x803.webp 768w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/640-2-11x12.webp 11w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/640-2-600x627.webp 600w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/640-2.webp 1080w\" sizes=\"(max-width: 980px) 100vw, 980px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f1928a3 elementor-widget elementor-widget-text-editor\" data-id=\"f1928a3\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p data-start=\"2053\" data-end=\"2137\">In SimData, each block of data and information is identified by a globally unique identifier. <strong data-start=\"2083\" data-end=\"2122\">UUID (Universally Unique Identifier)<\/strong> Marked as a token.<\/p><p data-start=\"2139\" data-end=\"2192\">These tokens form a bridge between different data. Users can access most of the tokenized and structured information through the following three core files:<\/p><ul><li data-start=\"2196\" data-end=\"2209\">sample.json<\/li><li data-start=\"2212\" data-end=\"2230\">sample_data.json<\/li><li data-start=\"2233\" data-end=\"2257\">sample_annotation.json<\/li><\/ul><p data-start=\"2264\" data-end=\"2279\"><strong>sample.json<\/strong><\/p><p data-start=\"2281\" data-end=\"2302\">Records the basic information of the Keyframe:<\/p><ul><li data-start=\"2306\" data-end=\"2328\">Each keyframe corresponds to a sample_token.<\/li><li data-start=\"2331\" data-end=\"2353\">Query the scene by scene_token.<\/li><li data-start=\"2356\" data-end=\"2386\">Provide prev \/ next token for constructing continuous frame relationship.<\/li><\/ul><p data-start=\"2393\" data-end=\"2413\"><strong>sample_data.json<\/strong><\/p><p data-start=\"2415\" data-end=\"2430\">Includes details of the multi-sensor data for the corresponding frame:<\/p><ul><li data-start=\"2434\" data-end=\"2472\">ego_pose_token: corresponds to the vehicle pose in ego_pose.json.<\/li><li data-start=\"2475\" data-end=\"2515\">calibrated_sensor_token: corresponds to the sensor calibration parameter (internal and external)<\/li><li data-start=\"2518\" data-end=\"2535\">filename: path of the original data file.<\/li><li data-start=\"2538\" data-end=\"2558\">height \/ width (if image)<\/li><li data-start=\"2561\" data-end=\"2574\">timestamp (microseconds)<\/li><li data-start=\"2577\" data-end=\"2594\">is_key_frame (boolean)<\/li><li data-start=\"2597\" data-end=\"2614\">next \/ prev (temporal association)<\/li><\/ul><p data-start=\"2621\" data-end=\"2647\"><strong>sample_annotation.json<\/strong><\/p><p data-start=\"2649\" data-end=\"2668\">Records information about the target object in each keyframe, including:<\/p><ul><li data-start=\"2672\" data-end=\"2694\">instance_token (unique token for the target)<\/li><li data-start=\"2697\" data-end=\"2717\">category_token (category information)<\/li><li data-start=\"2720\" data-end=\"2743\">visibility_token (visibility level)<\/li><li data-start=\"2746\" data-end=\"2754\">Geometry and posture information:<ul><li data-start=\"2759\" data-end=\"2775\">Translation (center point)<\/li><li data-start=\"2780\" data-end=\"2788\">size<\/li><li data-start=\"2793\" data-end=\"2817\">rotation (Quaternion)<\/li><\/ul><\/li><li data-start=\"2820\" data-end=\"2825\">Dot cloud statistics:<ul><li data-start=\"2830\" data-end=\"2843\">num_lidar_pts<\/li><li data-start=\"2848\" data-end=\"2861\">num_radar_pts<\/li><li data-start=\"2864\" data-end=\"2876\">Front and back frame token association<\/li><\/ul><\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-afdd1b6 elementor-widget elementor-widget-heading\" data-id=\"afdd1b6\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-small\">03 Examples of SimData and Perceptual Modeling Applications<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4665150 elementor-widget elementor-widget-text-editor\" data-id=\"4665150\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p data-start=\"2908\" data-end=\"2965\">SimData is available directly through <strong data-start=\"2922\" data-end=\"2941\">nuscenes-devkit<\/strong> parsing, which is used in exactly the same way as nuScenes:<\/p><div class=\"relative w-full my-4\"><div class=\"\"><div class=\"relative\"><div class=\"h-full min-h-0 min-w-0\"><div class=\"h-full min-h-0 min-w-0\"><div class=\"border corner-superellipse\/1.1 border-token-border-light bg-token-bg-elevated-secondary rounded-3xl\"><div class=\"corner-superellipse\/1.1 rounded-3xl bg-token-bg-elevated-secondary\"><div class=\"relative z-0 flex max-w-full\"><div id=\"code-block-viewer\" class=\"q9tKkq_viewer cm-editor z-10 light:cm-light dark:cm-light flex h-full w-full flex-col items-stretch \u037c5 \u037cj\" dir=\"ltr\"><div class=\"cm-scroller\"><div class=\"cm-content q9tKkq_readonly\"><span class=\"\u037c8\">from<\/span> <span class=\"\u037ce\">nuscenes<\/span><span class=\"\u037c8\">.<\/span><span class=\"\u037ce\">nuscenes<\/span> <span class=\"\u037c8\">import<\/span> <span class=\"\u037ce\">NuScenes<\/span><br \/><span class=\"\u037ce\">nusc<\/span> <span class=\"\u037c8\">=<\/span> <span class=\"\u037ce\">NuScenes<\/span>(<span class=\"\u037ce\">version<\/span><span class=\"\u037c8\">=<\/span><span class=\"\u037cc\">\u2018v1.0-custom\u2019<\/span>, <span class=\"\u037ce\">dataroot<\/span><span class=\"\u037c8\">=<\/span><span class=\"\u037ce\">data_path<\/span>, <span class=\"\u037ce\">verbose<\/span><span class=\"\u037c8\">=<\/span><span class=\"\u037cb\">True<\/span>)<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><div class=\"\"><div class=\"\">\u00a0<\/div><\/div><\/div><\/div><\/div><p data-start=\"3094\" data-end=\"3144\">Analysis and modeling can be done using official tools. Combine with cv2 or matplotlib for data visualization, including:<\/p><ul><li data-start=\"3148\" data-end=\"3160\">6-Camera GT Frame Output<\/li><li data-start=\"3163\" data-end=\"3174\">Synchronized LiDAR Dot Cloud<\/li><li data-start=\"3177\" data-end=\"3187\">BEV Viewing Angle Marker Display<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-04c7844 elementor-widget elementor-widget-image\" data-id=\"04c7844\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"696\" height=\"167\" src=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/\u5c4f\u5e55\u622a\u56fe-2026-02-25-135103.png\" class=\"attachment-large size-large wp-image-33144\" alt=\"\" srcset=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/\u5c4f\u5e55\u622a\u56fe-2026-02-25-135103.png 696w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/\u5c4f\u5e55\u622a\u56fe-2026-02-25-135103-300x72.png 300w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/\u5c4f\u5e55\u622a\u56fe-2026-02-25-135103-18x4.png 18w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/02\/\u5c4f\u5e55\u622a\u56fe-2026-02-25-135103-600x144.png 600w\" sizes=\"(max-width: 696px) 100vw, 696px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b980303 elementor-widget elementor-widget-heading\" data-id=\"b980303\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-small\">BEVFormer test results<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f578c1e elementor-widget elementor-widget-text-editor\" data-id=\"f578c1e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p data-start=\"3216\" data-end=\"3284\">Direct inference using BEVFormer-Tiny weights trained on nuScenes (not retrained on SimData) to verify data availability.<\/p><ul><li data-start=\"3288\" data-end=\"3356\">Official Formula Library<br data-start=\"3293\" data-end=\"3296\" \/><a class=\"decorated-link\" href=\"https:\/\/github.com\/fundamentalvision\/BEVFormer\/tree\/master\" target=\"_new\" rel=\"noopener\" data-start=\"3296\" data-end=\"3354\">https:\/\/github.com\/fundamentalvision\/BEVFormer\/tree\/master<\/a><\/li><li data-start=\"3360\" data-end=\"3401\">Links<br data-start=\"3364\" data-end=\"3367\" \/><a class=\"decorated-link\" href=\"https:\/\/arxiv.org\/pdf\/2203.17270\" target=\"_new\" rel=\"noopener\" data-start=\"3367\" data-end=\"3399\">https:\/\/arxiv.org\/pdf\/2203.17270<\/a><\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6215777 elementor-widget elementor-widget-heading\" data-id=\"6215777\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-small\">04 Conclusion<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-db23971 elementor-widget elementor-widget-text-editor\" data-id=\"db23971\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p data-start=\"3418\" data-end=\"3489\">This paper illustrates the importance of virtual datasets in the study of autonomous driving perception and presents a high-fidelity virtual perception dataset generated based on the aiSim simulation platform -- the <strong data-start=\"3477\" data-end=\"3488\">SimData<\/strong>The<\/p><p data-start=\"3491\" data-end=\"3545\">The article describes in detail the data structure and usage of SimData, and proves its usability and effectiveness by testing and validating it with an open-source perceptual model.<\/p><p data-start=\"3547\" data-end=\"3598\">In the future, the HONGKEI team will release more detailed test and comparison reports to further validate the high consistency between SimData and real datasets.<\/p><p data-start=\"3600\" data-end=\"3695\">Through this series of work, we have not only verified the high fidelity of the aiSim simulation environment, but also provided a set of high-quality, easy-to-use, and scalable virtual perceptual data resources for researchers and developers, which will continue to help the research and model training of automatic driving perception algorithms.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-45ed7c8 elementor-widget elementor-widget-button\" data-id=\"45ed7c8\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/aiportek.com\/adas-simulator-aisim\/\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Go to aiSim Product Page<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t<div class=\"elementor-element elementor-element-9049411 e-flex e-con-boxed e-con e-parent\" data-id=\"9049411\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-cfcf4de e-flex e-con-boxed e-con e-parent\" data-id=\"cfcf4de\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-dbc1b58 elementor-widget elementor-widget-heading\" data-id=\"dbc1b58\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-xl\">Other Articles<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-74adc8f elementor-posts--align-left elementor-grid-3 elementor-grid-tablet-2 elementor-grid-mobile-1 elementor-posts--thumbnail-top elementor-card-shadow-yes elementor-posts__hover-gradient elementor-widget elementor-widget-posts\" data-id=\"74adc8f\" data-element_type=\"widget\" data-settings=\"{&quot;cards_row_gap&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:100,&quot;sizes&quot;:[]},&quot;cards_columns&quot;:&quot;3&quot;,&quot;cards_columns_tablet&quot;:&quot;2&quot;,&quot;cards_columns_mobile&quot;:&quot;1&quot;,&quot;cards_row_gap_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;cards_row_gap_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]}}\" data-widget_type=\"posts.cards\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-posts-container elementor-posts elementor-posts--skin-cards elementor-grid\" role=\"list\">\n\t\t\t\t<article class=\"elementor-post elementor-grid-item post-36133 post type-post status-publish format-standard has-post-thumbnail hentry category-18 tag-knowbe4 tag-36\" role=\"listitem\">\n\t\t\t<div class=\"elementor-post__card\">\n\t\t\t\t<a class=\"elementor-post__thumbnail__link\" href=\"https:\/\/aiportek.com\/en\/hongke-knowbe4-australia-cloud-hosting-enterprise-case-study-reduce-insider-threat-build-proactive-cybersecurity-culture\/\" tabindex=\"-1\" target=\"_blank\"><div class=\"elementor-post__thumbnail\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"952\" src=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/07\/\u5b98\u7f51\u5c01\u9762.jpg\" class=\"attachment-full size-full wp-image-36139\" alt=\"\" srcset=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/07\/\u5b98\u7f51\u5c01\u9762.jpg 1024w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/07\/\u5b98\u7f51\u5c01\u9762-300x279.jpg 300w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/07\/\u5b98\u7f51\u5c01\u9762-768x714.jpg 768w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/07\/\u5b98\u7f51\u5c01\u9762-13x12.jpg 13w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/07\/\u5b98\u7f51\u5c01\u9762-600x558.jpg 600w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/div><\/a>\n\t\t\t\t<div class=\"elementor-post__badge\">Hongke Case<\/div>\n\t\t\t\t<div class=\"elementor-post__text\">\n\t\t\t\t<h3 class=\"elementor-post__title\">\n\t\t\t<a href=\"https:\/\/aiportek.com\/en\/hongke-knowbe4-australia-cloud-hosting-enterprise-case-study-reduce-insider-threat-build-proactive-cybersecurity-culture\/\" target=\"&quot;_blank&quot;\">\n\t\t\t\t[Hongke Case Study] Servers Australia Implements KnowBe4 to Achieve a 90% Training Completion Rate\t\t\t<\/a>\n\t\t<\/h3>\n\t\t\t\t<div class=\"elementor-post__excerpt\">\n\t\t\t<p>Servers Australia, an Australian cloud hosting provider, had previously been able to only reactively handle cybersecurity incidents, with high risks of internal threats and phishing attacks. After implementing the KnowBe4 cybersecurity awareness training platform, the company established a company-wide cybersecurity culture through simulated phishing tests, comprehensive training resources, and employee risk analysis. Training completion rates exceeded 90%, effectively reducing human-caused security vulnerabilities and shifting the team from reactive remediation to proactive defense against ransomware and social engineering threats.<\/p>\n\t\t<\/div>\n\t\t\n\t\t<a class=\"elementor-post__read-more\" href=\"https:\/\/aiportek.com\/en\/hongke-knowbe4-australia-cloud-hosting-enterprise-case-study-reduce-insider-threat-build-proactive-cybersecurity-culture\/\" aria-label=\"Read more about [Hongke Case Study] Servers Australia Implements KnowBe4 to Achieve a 90% Training Completion Rate\" tabindex=\"-1\" target=\"_blank\">\n\t\t\tRead more\t\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-post__meta-data\">\n\t\t\t\t\t<span class=\"elementor-post-author\">\n\t\t\tHongKeTechnology\t\t<\/span>\n\t\t\t\t<span class=\"elementor-post-date\">\n\t\t\tJuly 20, 2026\t\t<\/span>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/article>\n\t\t\t\t<article class=\"elementor-post elementor-grid-item post-36105 post type-post status-publish format-standard has-post-thumbnail hentry category-12 tag-gnss tag-67\" role=\"listitem\">\n\t\t\t<div class=\"elementor-post__card\">\n\t\t\t\t<a class=\"elementor-post__thumbnail__link\" href=\"https:\/\/aiportek.com\/en\/hongke-gnss-skydel-anechoic-ota-testing-evtol\/\" tabindex=\"-1\" target=\"_blank\"><div class=\"elementor-post__thumbnail\"><img loading=\"lazy\" decoding=\"async\" width=\"1080\" height=\"608\" src=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/07\/640-26.webp\" class=\"attachment-full size-full wp-image-36108\" alt=\"\" srcset=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/07\/640-26.webp 1080w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/07\/640-26-300x169.webp 300w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/07\/640-26-1024x576.webp 1024w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/07\/640-26-768x432.webp 768w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/07\/640-26-18x10.webp 18w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/07\/640-26-600x338.webp 600w\" sizes=\"(max-width: 1080px) 100vw, 1080px\" \/><\/div><\/a>\n\t\t\t\t<div class=\"elementor-post__badge\">Hongke Dry Goods<\/div>\n\t\t\t\t<div class=\"elementor-post__text\">\n\t\t\t\t<h3 class=\"elementor-post__title\">\n\t\t\t<a href=\"https:\/\/aiportek.com\/en\/hongke-gnss-skydel-anechoic-ota-testing-evtol\/\" target=\"&quot;_blank&quot;\">\n\t\t\t\t[Hongke Insights] From \u201cCables\u201d to \u201cStarry Sky\u201d: Hongke Skydel Anechoic Launches a New Paradigm for GNSS Spatial Radiation Testing\t\t\t<\/a>\n\t\t<\/h3>\n\t\t\t\t<div class=\"elementor-post__excerpt\">\n\t\t\t<p>To address the need for high-precision navigation in the low-altitude economy (UAV\/eVTOL) in Hong Kong and Southeast Asia, Hongke has launched the all-new Skydel Anechoic spatial physical field and phase angle simulation system. Breaking free from the limitations of traditional RF cables, this system perfectly replicates a three-dimensional sky environment within a microwave anechoic chamber (OTA), enabling precise verification of CRPA antenna interference resistance, antenna radome phase distortion, and spatial angle of arrival (AoA)!<\/p>\n\t\t<\/div>\n\t\t\n\t\t<a class=\"elementor-post__read-more\" href=\"https:\/\/aiportek.com\/en\/hongke-gnss-skydel-anechoic-ota-testing-evtol\/\" aria-label=\"Read more about [Hongke Insights] From \u201cCables\u201d to \u201cStarry Sky\u201d: Hongke Skydel Anechoic Launches a New Paradigm for GNSS Spatial Radiation Testing\" tabindex=\"-1\" target=\"_blank\">\n\t\t\tRead more\t\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-post__meta-data\">\n\t\t\t\t\t<span class=\"elementor-post-author\">\n\t\t\tHongKeTechnology\t\t<\/span>\n\t\t\t\t<span class=\"elementor-post-date\">\n\t\t\tJuly 15, 2026\t\t<\/span>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/article>\n\t\t\t\t<article class=\"elementor-post elementor-grid-item post-36019 post type-post status-publish format-standard has-post-thumbnail hentry category-18 tag-peak tag-38\" role=\"listitem\">\n\t\t\t<div class=\"elementor-post__card\">\n\t\t\t\t<a class=\"elementor-post__thumbnail__link\" href=\"https:\/\/aiportek.com\/en\/pcan-m2-interface-card-l4-autonomous-driving\/\" tabindex=\"-1\" target=\"_blank\"><div class=\"elementor-post__thumbnail\"><img loading=\"lazy\" decoding=\"async\" width=\"1080\" height=\"605\" src=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/07\/640-4-1.webp\" class=\"attachment-full size-full wp-image-36023\" alt=\"\" srcset=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/07\/640-4-1.webp 1080w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/07\/640-4-1-300x168.webp 300w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/07\/640-4-1-1024x574.webp 1024w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/07\/640-4-1-768x430.webp 768w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/07\/640-4-1-18x10.webp 18w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/07\/640-4-1-600x336.webp 600w\" sizes=\"(max-width: 1080px) 100vw, 1080px\" \/><\/div><\/a>\n\t\t\t\t<div class=\"elementor-post__badge\">Hongke Case<\/div>\n\t\t\t\t<div class=\"elementor-post__text\">\n\t\t\t\t<h3 class=\"elementor-post__title\">\n\t\t\t<a href=\"https:\/\/aiportek.com\/en\/pcan-m2-interface-card-l4-autonomous-driving\/\" target=\"&quot;_blank&quot;\">\n\t\t\t\t[Hongke Solutions] Hongke PCAN-M.2 Interface Card \u2013 Case Study: L4 Autonomous Vehicle On-Board Communication Solution\t\t\t<\/a>\n\t\t<\/h3>\n\t\t\t\t<div class=\"elementor-post__excerpt\">\n\t\t\t<p>This article explores how Hongke\u2019s PCAN-M.2 four-channel CAN FD interface card can be deeply integrated into ADLINK\u2019s autonomous driving ECU to create a high-bandwidth, low-latency, ISO automotive-grade, highly reliable in-vehicle communication solution for Level 4 autonomous shuttle buses. Click to read the full B2B technical case study and architecture analysis!<\/p>\n\t\t<\/div>\n\t\t\n\t\t<a class=\"elementor-post__read-more\" href=\"https:\/\/aiportek.com\/en\/pcan-m2-interface-card-l4-autonomous-driving\/\" aria-label=\"Read more about [Hongke Solutions] Hongke PCAN-M.2 Interface Card \u2013 L4 Autonomous Driving In-Vehicle Communication Solution Case Study\" tabindex=\"-1\" target=\"_blank\">\n\t\t\tRead more\t\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-post__meta-data\">\n\t\t\t\t\t<span class=\"elementor-post-author\">\n\t\t\tHongKeTechnology\t\t<\/span>\n\t\t\t\t<span class=\"elementor-post-date\">\n\t\t\tJuly 13, 2026\t\t<\/span>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/article>\n\t\t\t\t<\/div>\n\t\t\n\t\t\t\t<div class=\"e-load-more-anchor\" data-page=\"1\" data-max-page=\"39\" data-next-page=\"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/posts\/33138\/page\/2\/\"><\/div>\n\t\t\t\t<nav class=\"elementor-pagination\" aria-label=\"Pagination\">\n\t\t\t<span class=\"page-numbers prev\">\"<\/span>\n<span aria-current=\"page\" class=\"page-numbers current\"><span class=\"elementor-screen-only\">Page<\/span>1<\/span>\n<a class=\"page-numbers\" href=\"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/posts\/33138\/page\/2\/\"><span class=\"elementor-screen-only\">Page<\/span>2<\/a>\n<a class=\"page-numbers\" href=\"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/posts\/33138\/page\/3\/\"><span class=\"elementor-screen-only\">Page<\/span>3<\/a>\n<span class=\"page-numbers dots\">...<\/span>\n<a class=\"page-numbers\" href=\"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/posts\/33138\/page\/5\/\"><span class=\"elementor-screen-only\">Page<\/span>5<\/a>\n<a class=\"page-numbers next\" href=\"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/posts\/33138\/page\/2\/\">\"<\/a>\t\t<\/nav>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"<p>SimData is a high-fidelity virtual sensing dataset generated by aiSim simulation platform, which supports Camera, LiDAR, Radar, and IMU multi-sensor synchronization data, and the structure is fully aligned with nuScenes, which can be directly used for parsing and model training with nuscenes-devkit.<\/p>","protected":false},"author":1,"featured_media":33141,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[18],"tags":[65,64],"class_list":["post-33138","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-18","tag-aimotive","tag-64"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/posts\/33138","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/comments?post=33138"}],"version-history":[{"count":4,"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/posts\/33138\/revisions"}],"predecessor-version":[{"id":33148,"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/posts\/33138\/revisions\/33148"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/media\/33141"}],"wp:attachment":[{"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/media?parent=33138"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/categories?post=33138"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/tags?post=33138"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}