Pedestrian motion intention identification method adaptive to a human self-mixing environment

Abstract

The invention provides a pedestrian motion intention identification method adaptive to a human self-mixing environment. The method comprises the following steps: 1, carrying out pretreatment; The method comprises the steps of S1, obtaining state parameters of a target pedestrian, state parameters of traffic entities in an environment designated area where the target pedestrian is located and a division rule of the interest sensing area are obtained, the state parameters of the traffic entities in each interest sensing subarea are obtained, and the state parameters represented by the traffic entities in each interest sensing subarea are obtained according to the traffic entity representation obtaining rule in the subarea; and S2, analyzing and processing the state parameters of the target pedestrian, the traffic entity representations in all interest sensing subareas of the target pedestrian and the state parameters represented by the traffic entity representations according to a pedestrian motion intention identification model constructed based on a phase field theory and a fuzzy logic method, and obtaining a motion intention identification result of the target pedestrian. Pedestrian motion actions can be recognized in time, the current pedestrian motion intention can be judged, and technical support can be provided for pedestrian active safety early warning.

Description

technical field [0001] The invention relates to the technical field of pedestrian traffic and active safety, in particular to a pedestrian movement intention identification method adapting to a mixed environment of people and self. Background technique [0002] Pedestrians are an important factor affecting traffic safety and traffic capacity in the mixed environment of road sections. Accurately identifying the movement intentions of pedestrians in the mixed environment and predicting dangers, timely implementation of safety warnings, is conducive to improving the safety and efficiency of pedestrians and bicycles. Comfort is very important. [0003] Pedestrians and bicycles are low-speed and vulnerable groups in the traffic system, and the conflict between the two will rarely cause fatal injuries, and it is limited to the difficulty and complexity of real-time acquisition of the physiological, psychological, and physical parameters of pedestrians and cyclists. Insufficient a...

AI Technical Summary

Problems solved by technology

[0003] Pedestrians and bicycles are low-speed and vulnerable groups in the traffic system, and their conflicts rarely cause fatal injuries, and are limited to the difficulty and complexity of real-time acquisition of physiological, psychological, and physical parameters of pedestrians and bicycle riders. Insufficient attention has been paid to the safety of pedestrians and bicycles in the self-mixed traffic environment, and there are few studies on the movement characteristics of traffic entities and the interaction mechanism between traffic entities in the self-mixed traffic environment

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