Investigation of Traffic-Information Quantity Measurement Based on Information Theory

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.