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根据提出的一种交通量生成模型所产生的仿真数据 ,对城市交通中路况信息数据流的信源编码进行了研究 .压缩数据的方法是对初始信源等效变换 ,使变换后等效信源的概率分布比原信源更加有序 ,熵值更小 ,从而压缩率更高 .传输时还要对等效信源使用霍夫曼 (Huffman)算法编出即时可译码 ,使该变长码的平均码长接近熵值 .给出的编码方案可用于智能交通系统 (ITS)的车辆导航中对路况信息的传输 .
According to the simulation data generated by a traffic generation model proposed, the source coding of traffic information flow in urban traffic is studied.The method of data compression is to transform the original source information equivalently and transform the equivalent information The probability distribution of the source is more orderly than the original source, the entropy is smaller, so the compression rate is higher.While transmitting the equivalent source, Huffman algorithm can be used to make real-time decoding, The average code length of the long code is close to the entropy value.The proposed coding scheme can be used to transmit the traffic information in the vehicle navigation system of Intelligent Transportation System (ITS).