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HDTLR: A CNN based Hierarchical Detector for Traffic Lights

机译:HDTLR:一种基于CNN的交通信号灯分层检测器

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Reliable traffic light detection is one crucial key component for autonomous driving in urban areas. This includes the extraction of direction arrows contained within the traffic lights as an autonomous car will need this information for selecting the traffic light corresponding to its current lane. Current state of the art traffic light detection systems are not able to provide such information. Within this work we present a hierarchical traffic light detection algorithm, which is able to detect traffic lights and determine their state and contained direction information within one CNN forward pass. This Hierarchical DeepTLR (HDTLR) outperforms current state of the art traffic light detection algorithms in state aware detection and can detect traffic lights with direction information down to a size of 4 pixel in width at a frequency of 12 frames per second.
机译:可靠的交通信号灯检测是城市自动驾驶的关键关键组成部分。这包括提取交通信号灯中包含的方向箭头,因为自动驾驶汽车将需要此信息来选择与其当前车道相对应的交通信号灯。当前最先进的交通信号灯检测系统不能提供这种信息。在这项工作中,我们提出了一种分层的交通信号灯检测算法,该算法能够检测交通信号灯并确定其状态并在一个CNN前向通行证中包含方向信息。此分层DeepTLR(HDTLR)在状态感知检测中胜过当前最新的交通信号灯检测算法,并且可以以每秒12帧的频率检测方向信息到宽度为4像素的交通信号灯。

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