Driver lane change intention identification method based on hidden Markov model

A recognition method and a driver's technology, applied in the field of recognition of drivers' lane-changing intentions based on hidden Markov models, can solve problems such as distrust and large differences in driverless machines

Inactive Publication Date: 2019-03-12
UNIV OF SHANGHAI FOR SCI & TECH
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AI Technical Summary

Problems solved by technology

If changing lanes is unreasonable, or if the lane-changing strategy is quite different from the way people think about changing lanes, it will make people feel distrustful of unmanned machines

Method used

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  • Driver lane change intention identification method based on hidden Markov model
  • Driver lane change intention identification method based on hidden Markov model
  • Driver lane change intention identification method based on hidden Markov model

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Embodiment Construction

[0030] 1. Establishment of lane-changing intention recognition model

[0031] In order to identify the current driving behavior, by analyzing the characteristics and rules of the vehicle in the lane-changing phase, the speed of the lane-changing vehicle, the inter-vehicle distance and speed difference between the lane-changing vehicle and the front and rear vehicles in the original lane, and the target vehicle and the front and rear vehicles are selected as Observing the state parameters, and selecting lane change and going straight as the implicit state parameters, a recognition model of the driver's lane change intention is established by using the observed state to obtain the implicit state. as follows figure 1 A schematic diagram of a lane-changing vehicle is shown. where G fo is the straight-line distance between the lane-changing vehicle S and the vehicle in front of the lane-changing vehicle; G ro is the straight-line distance between the lane-changing vehicle S and ...

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Abstract

The invention relates to a driver lane change intention identification method based on a hidden Markov model. The driver lane change intention identification method based on the hidden Markov model isbuilt through analysis on the running state of a car and the running states of surrounding vehicles, and that is to say, through the observation states of observable lane change characterization parameters, hidden driver lane change intention is predicted. On the basis of a highway vehicle database which centralizes NGSIM data, lane change characterization parameter samples are extracted, the hidden Markov model is trained and verified with an HMM toolbox editing algorithm in MATLAB, and finally a prediction result of the driver lane change intention has high accuracy.

Description

technical field [0001] The invention relates to an unmanned driving technology, in particular to a method for identifying a driver's lane-changing intention based on a hidden Markov model. Background technique [0002] Unmanned driving is one of the main development directions of future automobiles. Research on unmanned vehicles is of great significance to ensure road traffic safety, improve road traffic capacity, and protect people's property safety. [0003] Unmanned driving is a comprehensive technology integrating environmental perception and cognition, dynamic planning and decision-making, behavior control and execution, among which perception and cognition are one of the most critical links in unmanned driving. Prerequisites for planning and decision-making. However, in practical applications, it is difficult to establish an accurate driver cognitive behavior model, especially the lane-changing behavior model, which is a commonly used driving behavior that is difficul...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02G06F17/18G06F17/16
CPCG05D1/0221G05D1/0223G05D1/0253G05D1/0276G05D2201/0212G06F17/16G06F17/18
Inventor 孙涛李洁
Owner UNIV OF SHANGHAI FOR SCI & TECH
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