Method for detecting density of passenger flow

Abstract

The invention relates to a method for detecting the density of a passenger flow. The method comprises the following steps of: detecting for obtaining passenger flow quantity data in a first time point and a second time point; measuring a passenger flow movement speed between the first time point and the second time point; and obtaining the density of the passenger flow according to the passenger flow data, the passenger flow movement width and the passenger flow movement speed. The method for detecting the density of the passenger flow, provided by the invention, realizes the purpose of accurately obtaining the density of the passenger flow through obtaining the passenger flow quantity data, the passenger flow movement speed and the passenger flow movement width in some time slot.

Description

technical field [0001] The invention relates to a method for detecting passenger flow density, in particular to a method for detecting passenger flow density by using a line scanning laser and a two-dimensional laser ranging sensor. Background technique [0002] With the rapid growth of population and rapid economic development, high-density crowd gathering has become the norm, such as subways, railway stations, comprehensive transportation hubs and other transportation occasions. Crowd gathering has brought huge potential safety hazards to these places, and also put forward higher management requirements for management departments at all levels. According to relevant regulations, when the number of people exceeds a certain limit, the management department needs to take contingency measures such as restricting the entry of the crowd and dispersing the crowd. [0003] Taking the subway as an example, the Beijing subway has more than 400 entrances and exits, 16 transfer stati...

AI Technical Summary

Problems solved by technology

[0004] The original density detection basically uses the passenger flow quantity divided by the environmental area to obtain the passenger flow density. The disadvantage of this method is that it is difficult to accurately correspond to the passenger flow quantity and the environmental area. Although the detected passenger flow quantity information and environmental area information are very accurate, the real-time calculation of the density When , some people in the detected passenger flow have already moved out of the detected environmental area

Therefore, the original algorithm can only simply estimate passenger flow density information, and cannot obtain accurate passenger flow density information

Images