Vehicle Identification Using Sensor and Network Data Correlation
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Solution Overview
Problem
Existing vehicle identification systems face inaccuracies due to low GPS accuracy and inability to detect vehicles sheltered by other objects, which can compromise driving safety by misrecognizing neighboring vehicles' positions.
Innovation Solution
A method and system that combines sensor data from radar, lidar, and cameras with inter-vehicle communication network data to identify and track neighboring vehicles, using similarity estimation methods to establish mapping relations between data sets and improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS data is used for vehicle position information, then the system can obtain position data from neighboring vehicles, but the position accuracy is low due to GPS limitations
Solution Approach 1:
The patent combines GPS data from the inter-vehicle communication network with sensor data (radar, lidar, camera) from the host vehicle to create a more accurate and reliable position identification system. By merging these two data sources, the system compensates for GPS inaccuracies and can identify vehicles even when they are sheltered by other objects.
2Measurement precision
If sensors are mounted on the host vehicle to detect neighboring vehicles, then the system can obtain accurate sensor data, but it cannot detect vehicles that are sheltered by other objects
Solution Approach 1:
The patent merges sensor data from the host vehicle with communication network data from neighboring vehicles to achieve both accurate detection and comprehensive coverage. The sensor data provides precise information for visible vehicles, while the network data extends detection coverage to vehicles that are sheltered or out of direct sensor range.
3Adaptability or versatility
If only inter-vehicle communication network data is used, then the system can receive information from all neighboring vehicles, but the position information may be incorrect due to low GPS accuracy
Solution Approach 1:
The patent uses sensor data as feedback to verify and correct the position information received from the inter-vehicle communication network. By comparing network data with actual sensor detections, the system can identify and correct GPS inaccuracies, ensuring both comprehensive coverage and high precision.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances driving safety by accurately identifying and tracking neighboring vehicles, even when they are out of sight, by correlating sensor data with network data, thereby correcting GPS inaccuracies and ensuring timely warnings and safe maneuvers.
Implementation Method 1
The at least one sensor may include at least one selected from a combination of a Radio Detection And Ranging (radar)
Implementation Method 2
The at least one sensor may include at least one selected from a combination of a Radio Detection And Ranging (radar), a Light Detection and Ranging (lidar)
Data Source
AI summary
A vehicle identification method and system are provided. The method includes: identifying a first vehicle to be a second vehicle based on a first group of data and a second group of data, the first group of data representing information of the first vehicle obtained through at least one sensor, and the second group of data representing information received from the second vehicle through an inter-vehicle communication network. By the method, an identity of the first vehicle in the inter-vehicle communication network can be known, the first group of data may be used to check the accuracy of the second group of data, and the second vehicle may be still tracked even if it is out of sight of the at least one sensor.