Brake Light Detection for Sensor Calibration
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Solution Overview
Problem
Autonomous vehicles face inaccuracies in navigation due to unreliable sensor measurements, which can lead to dangerous or undesirable navigation when detecting nearby vehicles, as conventional methods fail to accurately calibrate acceleration data.
Innovation Solution
The system calibrates sensor measurements by detecting brake light status using LIDAR or radar sensors and image capture devices, generating calibrated acceleration probability distributions based on braking or non-braking calibration curves to improve measurement accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional sensor measurement methods are used, then the navigation system can operate with basic sensor data, but the measurement accuracy is insufficient leading to dangerous navigation
Solution Approach 1:
The system uses brake light detection as a feedback mechanism to validate and calibrate acceleration measurements. When brake lights are detected, the system adjusts the acceleration probability distribution to account for braking events, creating a closed-loop verification system that improves measurement reliability and navigation safety
Solution Approach 2:
The patent introduces brake light detection as an intermediary verification layer between raw sensor measurements and navigation decisions. This intermediary system cross-checks acceleration data by detecting brake light states, providing an additional validation mechanism that resolves contradictions in sensor readings and improves overall measurement accuracy
2Measurement precision
If brake light detection is integrated with sensor measurements, then measurement accuracy improves, but system complexity increases
Solution Approach 1:
The system achieves multi-functionality by using the same image capture device for both primary visual navigation tasks and brake light detection. This universal approach allows brake light calibration to be integrated into existing vision processing pipelines without requiring dedicated hardware, thereby improving measurement accuracy while minimizing additional system complexity
Solution Approach 2:
The patent merges brake light detection with existing sensor fusion algorithms by integrating the calibration process into the probability distribution framework already used for navigation. This combination approach unifies multiple functions (visual processing, brake detection, acceleration calibration) into a single integrated system, improving accuracy without proportionally increasing complexity
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
This approach enhances the precision of sensor measurements, enabling more accurate determination of vehicle location and speed, thereby improving navigation safety for autonomous vehicles.
Implementation Method 1
The acceleration information may be determined based on a LIDAR sensor or a radar sensor
Implementation Method 2
The acceleration information may be determined based on a LIDAR sensor or a radar sensor
Implementation Method 3
The image information may be generated by an image capture device of the second vehicle
Data Source
AI summary
Systems, methods, and non-transitory computer readable media may be configured to calibrate sensor measurements based on detection of brake light. Acceleration information of a first vehicle may be obtained. The acceleration information may define an acceleration probability distribution of the first vehicle. Image information may be obtained. The image information may define an image of the first vehicle. Whether a brake light of the first vehicle is on or off may be determined based on the image of the first vehicle. Based on a determination that the brake light of the first vehicle is on, a calibrated acceleration probability distribution of the first vehicle may be generated based on the acceleration probability distribution of the first vehicle and a braking-calibration curve.