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Vehicle Trajectory Optimization Based on Limiting Average Algorithm
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DOI：10.1109/ACCESS.2020.3047386.png)
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摘要
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Due to multipath effects and other complex environments, GPS data received by the server contains noise. This paper introduces a solution to reduce the interference of the noise. First, a limiting filtering algorithm helps to overcome the accidental noise of received GPS data. Next, the received GPS data filtered with a moving average algorithm to inhibit periodic noise. Finally, the Douglas-Peucker algorithm thins out the data while ensuring the trajectory curve remains unchanged. In this way, we can not only make the trajectory curve smoother but also save memory consumptions. The experimental results show that the proposed method effectively removes noise and redundant data, and the effect of trajectory optimization is obvious.
Keyword:
Trajectory optimization
limiting filtering
moving average
Douglas-Peucker
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期刊
IF:
3.6
论文数:
9.8W
被引数:
30.9W
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