Driving trajectory predicting system integrating kinematic model and behavioral cognition model

Abstract

The invention discloses a driving trajectory predicting system integrating a kinematic model and a behavioral cognition model. The driving trajectory predicting system is characterized in that an interactive mixing module subjects the prediction result of each prediction module at a last time moment to interactive mixing to output a mixed result used for prediction at a next time moment; the prediction module comprises a behavioral cognition trajectory prediction module based on behavioral cognition and a motion trajectory prediction module based on kinematics; the behavioral cognition trajectory prediction module and the motion trajectory prediction module performs prediction according to the mixed result output by the interactive mixing module and output respective prediction results including a vehicle position and a covariance matrix; a fusion updating module fuses a final prediction result according to the prediction results, updates a weight coefficient, and outputs a vehicle position and a covariance matrix at a certain time moment in the future. The driving trajectory predicting system can continuously estimate the position state and the driving behavior of the vehicle in a vehicle driving process, predicts a driving trajectory, and provides assistance for intelligent driving decision.

Description

technical field [0001] The invention relates to the field of intelligent driving, in particular to a driving trajectory prediction system. Background technique [0002] Intelligent driving vehicles have a positive effect on traffic safety, traffic efficiency, environmental protection and energy saving. Intelligent driving vehicles use the perception system to sense the parameters of the driving environment and identify the type of target; through the cognitive system, the understanding of the driving environment, such as the understanding of driving behavior intentions, is improved, and future environmental changes are estimated and predicted, and other road users such as The decision-making mechanism of vehicles and pedestrians makes a correct understanding of the environment; completes driving behavior and path planning through the decision-making system and execution system, and realizes driving operation tasks. Among them, environmental cognition technology is a deep un...

AI Technical Summary

Problems solved by technology

However, the trajectory prediction method based on behavioral cognition has a large prediction error in a short period of time

[0004] At this stage, there are several problems in intelligent driving technology, behavior cognition and trajectory prediction: first, it cannot autonomously recognize and predict changes in the driving environment, and the decision-making system has a low level of intelligence, making it difficult to cope with the needs of complex traffic environments; The trajectory prediction method based on kinematics can only predict in a short period of time, and the prediction error in a long period of time is large; the third is that the trajectory prediction method based on behavior cognition can predict the driving trajectory for a long time, but it does not consider Vehicle dynamics, the prediction error in a short period of time is relatively large; fourth, the fusion method of multiple trajectory prediction models is based on fixed parameters, which cannot meet the needs of complex environments

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