基于信息理论的交通信息量度量
Investigation of Traffic-Information Quantity Measurement Based on Information Theory

针对语音信息缺乏量化和指路标志信息度量未反应实际出行条件下路网规模的影响作用问题，引入信息理论，构建语音信息量度量模型和图像信息量度量模型.设计包含23组不同信息量的实验路网，测定不同信息量下的驾驶员反应时间.研究结果显示：交通信息总量为52.22、57.90 bit时，出现反应时间的区域峰值；信息总量在50.74～57.38 bit区间段时，利于驾驶员对交通信息的认知且不产生信息量过载的现象；标志信息量为45.1、49.7 bit时，语音信息量位于5.12～10.24 bit区间利于降低驾驶员反应时间；语音信息量为5.12 bit时，标志信息位于49.70～54.30 bit区间利于提高驾驶员对交通状况认知.
：In view of the lack of voice-information quantification and that road-sign information measures have no effect on the road network size under actual travel conditions, information theory was introduced to construct a voice-information volume measurement model and an image-information volume measurement model. An experimental road network, including 23 sets of different amounts of information, was designed to measure the driver reaction time under different information volumes. The results of the study demonstrate that when the total amount of traffic information is 52.22 bits and 57.90 bits, there is a regional response-time peak. When the total amount of information is in the 50.74 bit to 57.38 bit interval, it can help drivers recognize traffic information without generating information overload. When the information volume is 45.10 bits and 49.70 bits, the voice-information volume should be in the range of 5.12 bits to 10.24 bits to reduce the driver reaction time. When the voice-information volume is 5.12 bits, the mark information is in the range of 49.70 bits to 54.30 bits, and it can improve the driver awareness of traffic conditions