ANPR-Based ADAS Feature Detection for Nearby Vehicle Differentiation
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Solution Overview
Problem
There is a need for an improved system for Highly Autonomous Vehicles (HAVs) to differentiate between vehicles with and without Advanced Driver Assistance Systems (ADAS) features in their vicinity, as existing technologies do not adequately address this differentiation.
Innovation Solution
A method and system using Automatic Number Plate Recognition (ANPR) to identify vehicles and determine their ADAS features, enabling HAVs to differentiate between vehicles with and without ADAS, and communicate this information in real time, allowing for adjustments in speed and direction to avoid collisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ANPR is used to identify vehicles and determine ADAS features, then the ability to differentiate between vehicles with and without ADAS is improved, but the system complexity increases
Solution Approach 1:
The patent introduces an intermediary database system that stores vehicle identification data and ADAS feature information. The ANPR camera captures license plate images, which are then matched against the database to retrieve pre-stored ADAS features. This intermediary database acts as a mediator between the simple ANPR identification and the complex ADAS feature determination, reducing the computational burden on the autonomous vehicle's processing system while maintaining high accuracy in vehicle differentiation.
2Reliability
If real-time communication of ADAS features is implemented, then safety and collision avoidance are improved, but the data processing time and computational load increase
Solution Approach 1:
The patent implements preliminary action by pre-storing vehicle ADAS feature data in a centralized database before the vehicles are on the road. When the autonomous vehicle captures an image of another vehicle's license plate, it performs a quick database lookup to retrieve pre-analyzed ADAS features rather than performing complex real-time analysis. This preliminary preparation of data eliminates the need for time-consuming computational analysis during critical driving moments, enabling rapid response while maintaining high reliability in collision avoidance.
Data Source
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AI summary
Provided are a method and system for determining Advanced Driver Assistance Systems (ADAS) features in a first vehicle, the method comprising operating a computing device configured to:receive one or more identifiers of the first vehicle; identify the first vehicle based on the one or more identifiers; and determine from a vehicle database whether the identified first vehicle has ADAS features.