首页> 外文会议>International Conference on Electrical, Electronics, Signals, Communication and Optimization >Intelligent traffic with connected vehicles: intelligent and connected traffic systems
【24h】

Intelligent traffic with connected vehicles: intelligent and connected traffic systems

机译:互联车辆的智能交通:智能互联交通系统

获取原文

摘要

This paper describes the structured approach involved in the development of an Intelligent Autonomous (self-driving, unmanned, driverless or robotic) Vehicles. In which autopilot with artificial intelligence are critical subsystems whose development requires multidisciplinary approach along with concurrent engineering to create a better, safer and reliable future. We have studied and implemented a miniature scale model with outcome of satisfactory results of supporting realistic vehicular mobility simulation using concepts of swarm technology discussed in this paper. Our Model must be equipped with a variety of instrumentation and controls depending upon the mission of the target vehicle. Mechatronics, Systems Engineering (SE), Control Systems (CS), Swarm Technology, Artificial Intelligence, Image Processing Cloud Computing, Virtualization with caching, Fuzzy Logic and Neural Networks has a potential scope of design for the prototype needed to be developed that will navigate to a desired location with obstacle avoidance. In this design of autonomous vehicles have access to information about their surroundings gathered from its several sensors such as Radar, GPS including a very important component of this system Infrastructure Unit which is connected virtually with Vehicle's Operating System, mapping and direction system is discussed broadly. Here, Infrastructure Unit plays a major role in routing the traffic to maintain free flow and accident avoidance, by provides information such as Routes, Traffic, Time, Directions to Vehicles and maintain constant speed for all vehicles to achieve an efficient autonomous transportation reducing accidents to zero. To improve the response time and storage of V2I Communication a new approach of caching and virtualization are encapsulated with a better and faster hardware such as Solid State Technology. This study has various applications in Space Science, Oceanography, and Automation in Traffic control which can effortlessly mee- the necessity, scalability of future Generation.
机译:本文描述了智能自动驾驶(无人驾驶,无人驾驶,无人驾驶或机器人)车辆的开发所涉及的结构化方法。其中具有人工智能的自动驾驶仪是关键子系统,其开发需要多学科的方法以及并行工程来创建更好,更安全和可靠的未来。我们已经研究并实现了一个微型模型,该模型使用本文讨论的群体技术概念,可以支持现实的车辆机动性仿真,并取得令人满意的结果。根据目标车辆的任务,我们的模型必须配备各种仪器和控件。机电一体化,系统工程(SE),控制系统(CS),Swarm技术,人工智能,图像处理云计算,带缓存的虚拟化,模糊逻辑和神经网络具有潜在的设计范围,可以开发需要导航的原型避开障碍物到期望的位置。在这种无人驾驶汽车的设计中,可以访问从其多个传感器(如雷达,GPS)收集的有关其周围环境的信息,其中包括该系统的一个非常重要的组件基础架构单元,该单元实际上与车辆的操作系统,地图和方向系统相连。在这里,基础设施部门通过提供诸如路线,交通,时间,车辆方向以及保持所有车辆的恒定速度等信息以实现有效的自主运输,从而减少交通事故,从而在安排交通路线以保持自由流动和避免事故方面发挥着重要作用。零。为了缩短V2I通信的响应时间和存储,一种新的缓存和虚拟化方法被封装在更好,更快的硬件中,例如固态技术。这项研究在空间科学,海洋学和交通控制自动化中有多种应用,可以毫不费力地满足下一代的必要性和可扩展性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号