ViCAL : Virtual Cities and Autonomous Learning

ViCAL：虚拟城市和自主学习

• 批准号: 10042169
• 金额: $ 44.6万
• 依托单位: CGA SIMULATION LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10042169
• 关键词: ViCAL; Virtual; Cities; Autonomous; Learning

Created by CGA Simulation and PINTEL, ViCAL integrates simulated data for training the deep learning algorithms behind the AI that analyses video and other sensor data from traffic control systems.Korean based company, PINTEL, has an existing product called Precise Video Analytics Experience (PreVAX), already in use in Korea. PreVAX is an intelligent traffic system that collects real-time data by applying an artificial intelligence-based algorithm to video from traffic control systems. CGA Simulation has developed ALEAD, a simulation platform, previously optimised for training Connected and Autonomous Vehicles (CAVs), planning installation of 5G infrastructure and transport infrastructure planning.ALEAD uses agent based modelling (ABM), which generates 'patterns-of-life' created via the interaction of digital agents (simulated vehicles), which travel from home, to work, to leisure, to retail, in manners informed by real life. This is better for predicting reactions to unprecedented dilemmas, like the introduction of new modes of travel or a pandemic.ViCAL will add the simulation techniques developed by CGA to the AI video platform developed by PINTEL. This newly enhanced product will be a substantial revenue earner for both companies as this innovation adds unique features that distinguish them in the Smart City, V2X, traffic management and CAV marketsCGA provides synthetic data that can be combined with PINTEL's technology to predict edge cases. Using CGA's complex simulated environment, PINTEL will generate synthetic camera feeds. The simulation will visualise and remove an accessibility barrier to scenes that in real life would be dangerous or difficult to generate.CGA can create a broad range of simulated environments. During ViCAL we will label simulated data for easier use and transference across platforms, localities, and technologies. Our created cases can then be applied to multiple scenarios and variables. One example would be a car pulling out unexpectedly, but with a range of delays, from very close, to collision, to further away. Ease of access and clear data visualisation means ViCAL can be used by anyone, not just specialists, and shared easily with wider teams and stakeholders. CGA's hazard editor allows users to easily create and share specific driving situations for either pass/fail test of AI or equally to create a range of edge cases, with a customisable capability.

ViCAL由CGA Simulation和PINTEL共同创建，它集成了模拟数据，用于训练人工智能背后的深度学习算法，分析来自交通控制系统的视频和其他传感器数据。韩国公司PINTEL现有的产品名为Precise Video Analytics Experience（PreVAX），已在韩国使用。PreVAX是一种智能交通系统，通过将基于人工智能的算法应用于交通控制系统的视频来收集实时数据。CGA Simulation已经开发了ALEAD，这是一个仿真平台，之前曾针对培训互联和自动驾驶汽车（CAV）、规划5G基础设施的安装和交通基础设施规划进行过优化。ALEAD使用基于智能体的建模（ABM），通过数字智能体的交互生成“生活模式”（模拟车辆），其以真实的生活方式从家、工作、休闲、零售地行驶。这对于预测对前所未有的困境的反应是更好的，例如引入新的旅行模式或流行病。ViCAL将把CGA开发的模拟技术添加到PINTEL开发的AI视频平台中。这款新增强的产品将为两家公司带来可观的收入，因为这一创新增加了独特的功能，使它们在智能城市、V2X、交通管理和CAV市场中脱颖而出CGA提供的合成数据可以与PINTEL的技术相结合，以预测边缘情况。使用CGA的复杂模拟环境，PINTEL将生成合成摄像头馈送。模拟将可视化并消除真实的生活中危险或难以生成的场景的可访问性障碍。CGA可以创建广泛的模拟环境。在ViCAL期间，我们将标记模拟数据，以便于跨平台，地点和技术的使用和传输。我们创建的案例可以应用于多个场景和变量。一个例子是一辆汽车意外地退出，但有一系列的延迟，从非常接近，碰撞，到更远。ViCAL易于访问和清晰的数据可视化意味着任何人都可以使用，而不仅仅是专家，并且可以与更广泛的团队和利益相关者轻松共享。CGA的危险编辑器允许用户轻松创建和共享特定的驾驶情况，用于AI的通过/失败测试，或者同样创建一系列具有可定制功能的边缘案例。