Sun Zhaocong
ABSTRACT
With the development of automotive industry and transportation industry, intelligent information processing becomes a global issue. In the near future, unmanned vehicle will be widely used the driving data of which needs monitoring carefully. The data of vehicle speed is important for analyzing the driving conditions and predict the danger of traffic accidents. When the road construction department judges a section of road as accident-prone areas, monitoring device will be installed to monitor the driving conditions. The algorithm proposed in this paper is used to extract vehicle speed from video. Gray matching method is used to lock the target vehicle. Weather the shooting device is drone or the installed monitoring device, the vehicle could be extracted with the video and will be tracked. The computing unit stalled in the shooting device will calculate the speed of the target vehicle based on frame difference. According to vehicle dynamics, the obtained vehicle speed could be used to calculate the condition of both vehicle and driver. The rolling resistance coefficient and air resistance can be calculated with the change of the speed. In the future, this technology will be used to detect the condition of each smart car on a specific road section. This algorithm provides a new way to obtain the vehicle speed and continuously monitors the vehicle conditions in a section of road. With the progress of visual recognition technology, speed recognition accuracy will greatly improve. During our study, the shooting device is installed on the flyover to record the track of the vehicle. The video is framed and grayed to obtain the vehicle speed. Compared to the actual speed, the error of the vehicle speed calculated with this algorithm is below 11.2%.
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Index Terms
- Visual-Based Vehicle Speed Acquisition Algorithm
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