Vehicle Image Processing for Behavior Detection in Self-Driving

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Solution Overview

Problem

Self-driving devices lack an effective method to accurately identify the behavior of other vehicles, leading to inadequate response to road conditions, which affects safety and reliability.

Innovation Solution

An automobile image processing method using a deep learning model to analyze images and determine the behavior of vehicles by outputting state parameters such as brake lamp, steering lamp, door, and wheel pointing direction states, enabling accurate identification of braking, steering, and parking behaviors.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If no effective method is used for identifying vehicle behavior, then the system remains simple, but the self-driving device cannot accurately respond to road conditions, affecting safety and reliability

Engineering Contradiction:
Improvesafety and reliability of self-drivingVSAvoidcomplexity of image processing system
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent segments the image processing task into distinct components: detecting brake lamp states, steering lamp states, door states, and wheel pointing direction states. Each component is processed independently through the deep learning model, allowing the system to handle complex vehicle behavior analysis through modular detection of individual state parameters

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent introduces a deep learning model as an intermediary between the input images and the vehicle behavior determination. This intermediary processes the raw image data and extracts meaningful state parameters (brake lamp, steering lamp, door, wheel states) that bridge the gap between visual input and behavioral interpretation

Inventive Principle:
Principle #24Intermediary (Mediator)

2Measurement precision

If deep learning model is used to analyze images and determine vehicle behavior, then measurement precision of vehicle state parameters is improved, but device complexity increases

Engineering Contradiction:
Improveprecision of vehicle state parameter detectionVSAvoidcomplexity of deep learning processing system
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent transforms the image analysis task from detecting complex vehicle behaviors directly to detecting specific state parameters (brake lamp on/off, steering lamp direction, door open/closed, wheel pointing direction). This parameter transformation simplifies the detection problem while maintaining high precision, as each parameter represents a discrete, easily classifiable state

Inventive Principle:
Principle #35Parameter changes

Data Source

PatentEP3570214B1Automobile image processing method and apparatus, and readable storage medium
Publication Date: 2023.11.29 APOLLO INTELLIGENT DRIVING (BEIJING) TECHNOLOGY CO LTD
  • EP3570214B1 patent drawingFigure 1~2
  • EP3570214B1 patent drawingFigure 3
  • EP3570214B1 patent drawingFigure 4~5

AI summary

The present invention provides an automobile image processing method and apparatus, and a readable storage medium. A to-be-processed image collected by a collecting point of automobile images is obtained, where the collecting point is provided on a self-driving device; the to-be-processed image is processed using a deep learning model, and a state parameter of an automobile in the to-be-processed image is outputted; and an automobile behavior in the to-be-processed image is determined according to the state parameter. Thus the to-be-processed image collected by the collecting point can be processed using the deep learning model to obtain the state parameter for determining the automobile behavior, and thus the automobile behavior can be obtained, thereby providing a foundation and a basis for the self-driving device to adjust the driving strategy according to the road condition.