An Adaptive Correction Prediction Method of Surrounding Vehicle Behavior Based on Driving Prediction Field

Abstract

The invention discloses a surrounding vehicle behavior adaptive correction prediction method based on a driving prediction field, step 1: surrounding vehicle behavior discretization and data set preprocessing: dividing the surrounding vehicle behavior into N typical behaviors according to the horizontal and vertical directions; step 2: Obtain the time series data of the vehicles involved in the traffic environment: each vehicle participating in the traffic environment uses the positioning system to obtain the position, speed, and acceleration of the vehicle at each moment in real time; Step 3: Establish a driving prediction field: establish Driving Prediction Field E of Three Elements of Comfort P ,E P =E S +E E +E C ; Step 4: Establish a surrounding vehicle behavior prediction model based on the maximum likelihood estimation method; Step 5: Real-time prediction of surrounding vehicle behavior and model adaptive correction. The invention comprehensively considers the safety, efficiency and driving comfort that affect the driver's behavior, establishes a driving prediction field in the driving area of ​​the target vehicle, and conducts qualitative and quantitative analysis, and proposes a new idea for surrounding vehicle behavior prediction.

Description

technical field [0001] The invention belongs to the technical field of intelligent driving, and in particular relates to a surrounding vehicle behavior adaptive correction prediction method based on a driving prediction field. Background technique [0002] Nowadays, whether it is advanced driver assistance systems or fully autonomous vehicles, scholars in various fields have aroused extensive research interests. There is no doubt that automotive intelligence has become one of the most important trends and trends in the development of the automotive industry. The reason is that smart vehicles not only have more efficient, safer and cleaner performance in the transportation system, but also can release humans from manipulating vehicles during driving. The real traffic environment is often complex and highly uncertain. In this environment, humans are actually very good drivers, because humans can infer the behavioral intentions of surrounding traffic participants and predict th...

AI Technical Summary

Problems solved by technology

Another feasible solution is to directly predict the behavior through the prototype trajectory of the surrounding target vehicle, which can obtain higher computational efficiency, but this type of method regards the predicted target vehicle as an independent individual when performing motion prediction. It is difficult to carry out stable and accurate long-term motion behavior prediction in the traffic environment, because no matter Whether it is a human-driven traffic vehicle or a traffic vehicle with autonomous driving capabilities, it is an intelligent body that responds to the surrounding environment.

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