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Improvement of Driver Visibility at Night by Ego Vehicle Headlight Control

机译:EGO车型夜灯控制驾驶员可见性的提高

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For drivers it is significant to have an appropriate intensity level of light for proper visibility of the road. But, driving a vehicle at night is very difficult task due to the direct headlights from vehicles which drives in opposite directions and uncontrollable light sources from outside. Moreover, when the headlights are dim, the intensity level of the light is not sufficient for the drivers which causes to increase the accidents rate rapidly specially in urban areas. This is mainly due to manual lightening systems. Therefore this research is focus on developing an efficient image processing based algorithm to ensure the sufficient intensity level of the lights to the ego-vehicle driver while providing the least intensity level for the opposite drivers automatically. A pixel-based image segmentation method was used to implement the proposal. Testing the algorithm was done in a simulated environment to verify the accuracy of the algorithm.
机译:对于驾驶员来说,对于正确的可视性,具有适当的强度光线。但是,由于车辆的直线灯和来自外部的相反方向和无法控制的光源的车辆的直接头灯,在夜间驾驶车辆是非常困难的。此外,当前灯为暗淡时,光的强度水平对于驱动器来说是不够的,这导致在城市地区迅速增加事故速率。这主要是由于手动闪电系统。因此,该研究专注于开发基于高效的图像处理的算法,以确保为自动车辆驱动器的灯的充分强度水平,同时自动为相对的驱动器提供最小的强度水平。使用基于像素的图像分割方法来实现该提议。测试算法在模拟环境中完成,以验证算法的准确性。

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