Adaptive Traffic Sign Display Order for Driver Safety
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Solution Overview
Problem
Conventional auxiliary driving information systems do not consider a driver's habits, familiarity with the route, or environmental conditions when determining the display order of indicator objects, which can impact driving safety.
Innovation Solution
A method and system that use image recognition and vehicle data to determine the familiarity of the driver with the road section and their driving habits, then prioritize traffic signs based on traffic violation history and dangerous situations, adapting the display order of auxiliary driving information accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the display order of indicator objects is determined mainly based on default system settings, then the system operation is simple, but the adaptability to driver habits and road conditions is poor
Solution Approach 1:
The system collects driver behavior data (lane changes, speed adjustments) and road condition data, then uses this feedback to dynamically adjust the display order of traffic signs. The processing unit analyzes historical driving data and current road conditions to personalize the information presentation for each driver.
Solution Approach 2:
The display order of indicator objects transitions from static (default settings) to dynamic (adjusted based on real-time driver behavior and road conditions). The system continuously adapts the priority order of displayed traffic signs according to changing driving contexts and individual driver patterns.
2Reliability
If the display order is adjusted based on multiple factors including driver habits and road conditions, then the adaptability improves, but the system complexity increases
Solution Approach 1:
The system automatically collects and analyzes driver behavior data without requiring manual input. The processing unit autonomously processes driving history data, identifies driver patterns, and adjusts the display order independently, reducing the need for complex manual configuration interfaces.
Solution Approach 2:
The system pre-processes and stores driver behavior data and road condition information in advance. When a driving situation arises, the processing unit quickly retrieves relevant pre-analyzed data to determine the optimal display order, reducing real-time computational complexity.
3Loss of information
If all identified traffic signs are displayed to the driver, then the information completeness is high, but the information overload may distract the driver
Solution Approach 1:
The system extracts and prioritizes only the most relevant traffic signs for display based on driver habits and current road conditions. The processing unit filters out less critical information and presents only the essential indicator objects in a customized order, preventing information overload while maintaining completeness of critical data.
Solution Approach 2:
Different traffic signs are assigned different display priorities based on their relevance to the current driving context and individual driver needs. The system applies different presentation qualities (prominence, timing) to different types of indicator objects rather than treating all information uniformly.
Data Source
AI summary
In a system for adaptively providing auxiliary driving information, a processing unit, which is installed in a vehicle, acquires traffic sign(s) from vehicle driving images, and determines whether a driver of the vehicle is familiar with a current road section, and whether the driver has good driving habits. Based on the determinations and reference information that is related to a traffic violation history and/or a dangerous situation of the current road section, the processing unit selects prompt object(s) from the traffic sign(s), and determines a prompt order of the prompt object(s). Then, the processing unit causes an output module to perceivably output the prompt objects in the prompt order.