Driving Tendency Analysis Using Image Sensors for Vehicle Control
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Solution Overview
Problem
Current Advanced Driver Assistance Systems (ADAS) face challenges in accurately controlling vehicles due to varying driving tendencies of drivers, which can lead to safety issues on the road, as they do not adequately consider individual driving habits and behaviors.
Innovation Solution
A method and apparatus for analyzing driving tendencies using image sensors and non-image sensors to capture data, processing it with a controller to identify objects and events, and sharing driving tendency information through vehicle-to-vehicle communication to enhance vehicle control and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If ADAS systems control vehicle braking and steering based on standard algorithms, then basic driving assistance functions are provided, but the systems cannot adapt to individual driver behaviors and tendencies, reducing control accuracy and safety
Solution Approach 1:
The system performs preliminary analysis of driver behavior by continuously monitoring driving operations and storing driving tendency information before actual driving situations occur. This allows the system to pre-establish driver profiles and behavioral patterns, enabling accurate adaptation when controlling vehicle braking and steering operations.
Solution Approach 2:
The system implements feedback mechanisms by analyzing driver operations, determining driving tendencies from this analysis, and using this information to adjust subsequent vehicle control operations. The controller continuously receives feedback from sensors monitoring driver behavior and modifies braking and steering control accordingly to match the detected driver tendencies.
2Measurement precision
If multiple sensors and processing units are added to detect and analyze driver tendencies, then driving tendency detection accuracy is improved, but the system complexity and cost increase
Solution Approach 1:
The system uses existing ADAS sensors and processing units to perform multiple functions - both their original functions and driver tendency analysis. The controller leverages already-acquired driving operation data for dual purposes: standard vehicle control and driving tendency detection, avoiding the need for separate dedicated hardware systems.
Solution Approach 2:
The system analyzes driver tendencies using the driver's own operating patterns and behavior data that are naturally generated during normal driving. The driver effectively provides the analysis data through their own actions, eliminating the need for separate data collection mechanisms or additional sensing hardware.
3Reliability
If driving tendency information is shared through vehicle-to-vehicle communication, then overall road safety is improved, but communication data processing requirements and system complexity increase
Solution Approach 1:
The system extracts and transmits only essential driving tendency information through vehicle-to-vehicle communication, separating critical safety-related data from comprehensive driver behavior data. This selective extraction approach enables safety improvements through information sharing while minimizing communication data processing requirements and system complexity.
Data Source
AI summary
Disclosed are a method and an apparatus for analyzing a driving tendency and a system for controlling a vehicle. The apparatus includes: an image sensor disposed in a vehicle so as to have a field of view exterior of the vehicle, the image sensor configured to capture image data; and a controller comprising at least one processor configured to process the image data captured by the image sensor, wherein the controller is configured to: identify a plurality of objects present in the field of view, responsive at least in part to processing of the image data; determine whether an event is generated, based on at least one of a processing result of the image data and pre-stored driving information of the vehicle; analyze a driving tendency of a driver, based on the driving information and the processing result of the image data, when it is determined that the event is generated; and set a driving level corresponding to the driving tendency of the driver.