Traffic sign classification method and device

Abstract

The invention provides a traffic sign classification method and device. The traffic sign classification method comprises the steps of obtaining the visual cognition understanding time data of multipleexperimenters on each block of traffic signs to be classified; categorizing the traffic signs to be classified based on the visual cognition understanding time data. The traffic sign classification device is used for executing the above method. The invention is advantageous in that the features of the traffic sign layout and the visual cognition understanding time of drivers to the traffic signsare comprehensively taken into consideration, and the traffic signs are reasonably classified; the accuracy of the research of the traffic sign information threshold can be enhanced; accurate theory base is provided for traffic signs in road setting.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of transportation, and in particular to a traffic sign classification method and device. Background technique [0002] With the development of science and technology, cars have increasingly become a necessity in people's lives, and more and more people use cars as a means of transportation. Correspondingly, more reasonable traffic rules and traffic signs are needed to guide people to drive correctly. [0003] The reasonable setting of traffic signs on the road can accurately guide the driver to exercise on the road and reduce the error rate of the driver's operation. In the setting of road traffic signs and the graphic design of traffic signs, it is necessary to conduct research on the information threshold of traffic signs. The information threshold is also called the information overload threshold, which refers to the maximum amount of information that the driver can obtain within...

AI Technical Summary

Problems solved by technology

This classification method mainly considers the characteristics of each type of traffic sign layout, but ignores the driver's influence on the visual recognition of traffic signs.

There are also some scholars who classify traffic signs based on the comprehension of traffic signs and the results of homogeneity tests within the group. This classification method does not effectively combine

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