智能导航系统自适应切换模式交通流编码算法

Coding Algorithm of Traffic Flow in Intelligence Guidance System Based on Adaptive Switching Mode

针对智能交通流数据量大、无固定模式、精度要求不同的特点,提出了一种根据具体数据格式自适应切换压缩模式的编码算法。对于可进行有损压缩的数据,将时间序列预测思想应用于编码算法中,进行Contourlet逐级分解,直至精度达到要求;在该层应用ARMA建模,传送时只传递其ARMA参数,译码时先以ARMA模型构造Contourlet系数,然后重构原始数据;对于需进行无损压缩的数据,先分析其数据特性,结合传统算法,设计了一种等长、变长编码相结合的压缩方法,在保证数据可完全译出的前提下,达到最佳压缩率。仿真结果表明：对于无损压缩,新算法压缩率可达0.329-0.62;对于有损压缩,压缩率可达0.055-0.29,相对误差为2.34%-4.32%。

According to the characteristics of traffic flow as follow： large amount of data,no fixed format and different accuracy requirements,a new coding algorithm with self-adaptive switching mode according to specific format of data was put forward.For data which were suitable to lossy compression,prediction thought of time series was used in the algorithm.Traffic flow was stepwise decomposed by Contourlet and the process was repeated till precision fitted the bill.Parameters of ARMA model which was used in this level were sent in data transmission.Reconstruction of raw data was used after Contourlet coefficients were constructed by ARMA when decoding.For data which were suitable to lossless compression,characteristic analysis was carried out before designing an compression algorithm combined with variable length coding and equal length code to obtain the optimal compression ratio under the premise that data were fully translated.The simulated results show that the compression ratio of the algorithm can reach 0.329 to 0.62 in the lossless compression and can reach 0.055 to 0.29 in the lossy compression.The relative error rate in the lossy compression is 2.34% to 4.32%.