A vehicle early warning system and method based on roadside double flashing light recognition
A technology of double flashing lights and vehicles, applied in the field of traffic safety, can solve the problems of large-scale serial rear-end collision accidents of rear vehicles, vehicle rear-end collision accidents, etc., and achieve the effect of avoiding serial rear-end collision accidents
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Embodiment 1
[0028] refer to figure 2 , a vehicle early warning system based on roadside double flashing light recognition of the present invention, comprising: an integrated monitoring device, an early warning display, an early warning broadcaster and a control center; The millimeter-wave radar and camera are integrated on the road, and the millimeter-wave radar is used to obtain the speed and position information of each vehicle on the road, and transmit it to the control center; the camera is used to obtain the road condition information on the road, and its transmission to the control center;
[0029] The control center is used to identify whether the vehicle has turned on the double flashing lights according to the obtained road condition information, vehicle speed and position information, and determine the danger level of the current road condition. Corresponding warning information;
[0030] The early warning displays are arranged equidistantly on the roadside of the road, and a...
Embodiment 2
[0034] refer to figure 1 , a vehicle early warning method based on roadside double flashing light recognition, comprising the following steps:
[0035] Step 1, obtain the road condition information on the expressway in real time, extract the image of each vehicle; obtain the speed of each vehicle;
[0036] Among them, the road condition information and the speed of each vehicle are obtained through cameras and millimeter-wave radars set at intervals on the roadside of the expressway;
[0037] Step 2, using image grayscale analysis to select the candidate area in the image of each vehicle; using the maximum inter-class variance method to segment the candidate area, and then undergoing morphological transformation to obtain the candidate headlight area;
[0038] Specifically follow the steps below:
[0039] (2.1) Use the HSV color space to perform threshold filtering to obtain the corresponding candidate vehicle taillight area binary map;
[0040] Wherein, the threshold value...
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