Research on coding of road information in intelligent transport system

The code of road information was analyzed, based on the data provided by a model of the traffic volume. The method to compress data is equivalent conversion of the initial source, so the probability distribution of the equivalent conversed source becomes more sequential with less entropy value and greater compression ratio than that of initial one. When being transmitted, the instantaneously decodable code could be coded via Huffman-algorithm in order that the average length of variable length prefix code is close to the entropy value of the source. The result shows that the correlation of traffic volume at a cross is more than that in a street as well as that in a city. Its achievements can be applied in ITS (intelligent transport system) to communicate the road information.