Street-crossing pedestrian trajectory prediction method and system based on social force model, and medium

Abstract

The invention provides a street-crossing pedestrian trajectory prediction method and system based on a social force model, and a medium. The method comprises the following steps: a basic data acquisition step: selecting a pedestrian-vehicle mixed zebra crossing area for early investigation, shooting a pedestrian walking video of the area, and performing video processing and image processing on thepedestrian walking video to obtain pedestrian walking feature data and pedestrian-vehicle interaction scene data; and a model parameter calibration step: preprocessing the obtained pedestrian walkingcharacteristic data and the obtained pedestrian-vehicle interaction scene data, and calibrating parameters of a logistic regression model and a social force model. According to the method, the improved social force model is utilized, the individual difference of pedestrians is fully considered, the pedestrian track prediction of the crossing street is applied to the field of automatic driving vehicle decision making, the driving safety of the automatic driving vehicle in the pedestrian-vehicle mixed zebra crossing area can be improved, the delay rate of the vehicle is reduced, and the road traffic capacity is improved.

Description

technical field [0001] The present invention relates to the field of decision-making algorithms for automatic driving, in particular to a method, system and medium for predicting trajectories of pedestrians crossing the street based on a social force model. In particular, it involves a pedestrian trajectory prediction method based on a social force model, and a complete set of processes from the preparatory work to the specific implementation method in the later stage is designed. Background technique [0002] In the field of autonomous driving, it is an important topic to understand the environment of autonomous vehicles, the behavior of traffic participants and make decisions based on this. Pedestrians are important participants in traffic and also a vulnerable group of traffic participants. . Its dynamic characteristics are complex, and its motion direction and speed change are highly random, so it is difficult to understand its motion behavior. [0003] At present, mos...

AI Technical Summary

Problems solved by technology

The probabilistic method has certain accuracy in predicting the decision of pedestrians to go and stop, but it is powerless to predict the trajectory of pedestrians who continue to walk in the face of oncoming vehicles; the CV and CA models are too simple to accurately describe the impact of pedestrians on the environment and the relationship between pedestrians and pedestrians. The influence of interaction, interaction between pedestrians and vehicles on pedestrian trajectories

In addition, the above methods rarely consider the influence of individual differences in pedestrians, which has certain limitations.

[0005] The social force (SF) model is a method widely used in pedestrian flow simulation in

Images