Abstract
Because of the continuous progress of vehicle hardware, the condition where the vehicle cannot load a complex algorithm no longer exists. At the same time, with the progress of vehicle hardware, the number of texts shows exponential growth in actual operation. In order to optimize the efficiency of mass data transmission in actual operation, this paper presented the text information (including position information) of the maximum entropy principle of a neural network probability prediction model combined with the optimized Huffman encoding algorithm, optimization from the exchange of data to data compression, transmission, and decompression of the whole process. The test results show that the text type vehicle information based on compressed algorithm to optimize the algorithm of data compression and transmission can effectively realize data compression. It can also achieve a higher compression rate and data transmission integrity, and after decompression it can basically guarantee no distortion. The method proposed in this paper is of great significance for improving the transmission efficiency of vehicle text information, improving the interpretability and integrity of text information, realizing vehicle monitoring, and grasping real-time traffic conditions.
Highlights
With the popularity of mobile Internet in traffic, the application of mobile Internet operating mode and the growing number of operating vehicles have resulted in a large amount of data in the actual operation
In order to optimize the efficiency of mass data transmission in actual operation, this paper presented the text information of the maximum entropy principle of a neural network probability prediction model combined with the optimized Huffman encoding algorithm, optimization from the exchange of data to data compression, transmission, and decompression of the whole process
Due to the unbalanced distribution of urban mobile communication base stations, the urban communication environment is quite different, the data transmission capacity is quite different in different parts of the city, and some areas even appear as communication blind areas
Summary
With the popularity of mobile Internet in traffic, the application of mobile Internet operating mode and the growing number of operating vehicles have resulted in a large amount of data in the actual operation. Text information transmission after compression is key to solving this problem This method can be accepted because it can meet the data transmission delay and data quality indicators formulated by user units in a complex urban communication environment. In order to improve the quality and efficiency of wireless data transmission, researchers have proposed a variety of text data compression and transmission algorithms. In urban areas where communication base station coverage is uneven and the communication environment varies, how to optimize the compression and transmission of text and other information is a major problem for practical applications. Optimization of the data transmission method after vehicle information collection is of great significance for improving the transmission efficiency of vehicle text information, improving the interpretability and integrity of text information, realizing vehicle monitoring, and grasping real-time traffic conditions
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