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A Curve Trajectory Modeling Method for Human Drivers

A modeling method and driver's technology, applied in neural learning methods, character and pattern recognition, biological neural network models, etc., can solve the problems of accuracy and applicability dependence, regardless of consideration, and achieve good generalization performance

Active Publication Date: 2021-07-20
JIANGSU UNIV
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Problems solved by technology

This type of method does not consider the reasons for the formation of vehicle trajectories and the internal relationship with the traffic environment, and its accuracy and applicability depend entirely on the amount of historical data and the quality of the modeling method

Method used

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  • A Curve Trajectory Modeling Method for Human Drivers
  • A Curve Trajectory Modeling Method for Human Drivers
  • A Curve Trajectory Modeling Method for Human Drivers

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Embodiment Construction

[0043] The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0044] Such as figure 1 As shown, the human driver curve trajectory modeling method mainly includes the following steps: extracting the vehicle trajectory on the human driver curve, calculating the regression coefficient between the lateral offsets, and calculating the vehicle speed, sight distance and Road curvature, based on GRNN (General Regression Neural Network, GRNN) to establish a human driver curve trajectory model.

[0045] (1) Extract the vehicle trajectory on the curve of the human driver

[0046] ① Collect the trajectory information of different drivers driving the vehicle on the curve through the real vehicle

[0047] A two-way two-lane road was selected as the test road. figure 2 A top view of the road. The road consists of five parts, namely straight line section 1, transitional curve section 1, circular curve section, transitional curve s...

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Abstract

The invention discloses a human driver's curve trajectory modeling method, which belongs to the field of intelligent vehicle trajectory planning. Firstly, the vehicle trajectory on the human driver's curve is extracted, and then the regression coefficient between the lateral offset and the regression coefficient are calculated. Corresponding vehicle speed, sight distance and road curvature, and finally build a human driver curve trajectory model based on GRNN. The present invention can compare and analyze trajectory data at different starting positions and different vehicle speeds on the same scale, taking into account the continuity of vehicle trajectory, and closely linking roads, traffic environments, drivers and vehicles , enabling human driver curve trajectory modeling.

Description

technical field [0001] The invention belongs to the field of intelligent vehicle trajectory planning, and in particular relates to a modeling method for a human driver's driving trajectory on a curved road. Background technique [0002] At present, intelligent vehicle technology is developing rapidly. This technology can improve the safety and comfort of the car, and can provide an excellent human-vehicle interaction interface, leading the development direction of future automotive technology. An intelligent vehicle is a comprehensive system that integrates functions such as environmental perception, planning and decision-making, and multi-level assisted driving. It uses technologies such as computers, modern sensing, information fusion, communication, artificial intelligence, and automatic control. technology complex. One of the most basic functions of an intelligent vehicle is that it can independently plan a driving trajectory (this trajectory is generally called a refer...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/00G06K9/62G06N3/08
CPCG06N3/08G06F30/20G06F18/23
Inventor 李傲雪江浩斌周婕周新宸
Owner JIANGSU UNIV
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