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Position Recognition for an Autonomous Vehicle Based on Vehicle-to-Led Infrastructure

机译:基于车对车基础设施的无人驾驶汽车位置识别

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Self-driving cars are needed to ensure the location of the cars in order by recognizing obstacles around the vehicles, and creating and following travel routes. GPS based location determination system includes a very large error range, which limits the use of the GPS in tunnels, parking lots and large cities where radio signals are not able to travel through the air efficiently. High precision location determination technologies allow the cars to interact the navigation systems of self-driving cars with Intelligent Transportation System or ITS. The development of recent LED technology is applied to various industries. However, the technology is broadly used in the lighting system which is highly important for railroad traffic system. White color LED which is widely used for the lighting of lamps in tunnels, and it has various color temperature, which has different chromaticity coordinates. In this context, this paper aims at the location determination of self driving cars by analyzing the coordinates of chromaticity point, while grouping LED streetlamps which have different color temperature and shining optical focus on lanes. In addition, the paper evaluates the lane locations of the vehicles through the interrelation between their location and chromaticity coordinates under the laboratory environment. As a result, the paper identified the possibility of the location determination in the limited space of GPS signals.
机译:需要无人驾驶汽车,以通过识别车辆周围的障碍物并创建和遵循行驶路线来确保汽车的位置有序。基于GPS的位置确定系统具有很大的误差范围,这限制了GPS在隧道,停车场和无线电信号无法有效传播的大城市中的使用。高精度的位置确定技术使汽车可以将自动驾驶汽车的导航系统与智能交通系统或ITS进行交互。最近的LED技术的发展被应用于各个行业。但是,该技术广泛用于照明系统,这对于铁路交通系统非常重要。白色LED广泛用于隧道灯的照明,它具有多种色温,具有不同的色度坐标。在这种情况下,本文旨在通过分析色度点的坐标来确定自动驾驶汽车的位置,同时将色温不同且光学聚焦在车道上的LED路灯分组。另外,本文通过在实验室环境下车辆的位置与色度坐标之间的相互关系来评估车辆的车道位置。结果,论文确定了在GPS信号的有限空间中确定位置的可能性。

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