交通拥堵形态的聚类判别实现
The Clustering and Discrimination of Traffic Congestion Form Is Realized

城市道路中司机对路况全貌不了解，极有可能驶入拥堵路段耽误行程，预知实时路况可以避开拥堵路段尽快到达目的地。驾驶过程需要观察前方，因此语音播报成为必须，但逐条路段播报不利于司机掌握全貌且播报不及时，本文通过聚类分析方法，对路网中的拥堵分布给予高度归纳概括、准确的信息表达，从而使得机器自动识别并在有限时间内语言推送表达信息，避免对司机形成信息干扰。有利于司机有限时段内掌握前方路况全貌。
Drivers don’t know the full picture of road conditions in the urban road network, so it is very likely to delay the journey when driving into the congested road sections. Predicting the real-time road conditions can avoid the congested road sections and reach the destination as soon as possible. In the driving process, it is necessary to observe the front, so voice broadcast is necessary, but it is not conducive to the driver’s grasp of the whole picture and the broadcast is not timely enough. In this paper, through clustering analysis method, the congestion distribution in the road network is highly summarized and accurately expressed, so that the machine can automatically recognize and push the expression information in a limited time, avoiding the formation of information for the driver Interference. It is beneficial for the driver to master the full view of the road ahead in a limited period of time.