Vehicle Optical Sensing for Low-Quality Region Detection
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Solution Overview
Problem
Existing vehicle surroundings detection systems struggle to minimize sensor gaps and uncertainties, leading to reduced trajectory planning capabilities and increased risk in highly automated vehicles.
Innovation Solution
Utilizing optical sensors to detect and improve low-quality regions by active illumination with various light sources, including invisible light, and fusing sensor data to enhance the surroundings model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the detection ranges of sensors are extended to improve coverage, then the quality of the surroundings model is improved, but sensor gaps and uncertainties cannot be minimized independently by the ego-vehicle
Solution Approach 1:
The patent introduces an intermediary illumination device (light source) that mediates between the sensor and the surrounding environment. By actively illuminating regions with poor detectability, the light source acts as a mediator that enhances the sensor's ability to detect objects in those regions, thereby improving reliability without extending the physical detection range of the sensor itself.
Solution Approach 2:
The system performs preliminary action by proactively identifying regions with low detectability quality and illuminating them before the sensor attempts to detect objects in those regions. This preliminary illumination ensures that when the sensor scans these areas, the objects are already properly lit, improving detection reliability in advance.
2Measurement precision
If active illumination is used to improve detectability of low-quality regions, then measurement precision is improved, but energy consumption increases
Solution Approach 1:
Instead of uniformly illuminating the entire surrounding area, the system applies local quality by selectively illuminating only those specific regions that have been identified as having low detectability quality. This localized approach concentrates energy only where needed, improving measurement precision in critical areas while minimizing overall energy consumption.
Solution Approach 2:
The system applies partial action by illuminating only a portion of the total detection area - specifically, only the regions with low quality detectability. This partial illumination is sufficient to improve measurement precision in the critical areas without the excessive energy consumption that would result from illuminating the entire surrounding environment.
3Reliability
If multiple sensors are used to improve surroundings model quality, then detection reliability is improved, but device complexity increases
Solution Approach 1:
The illumination device serves multiple functions: it illuminates the surrounding environment for optical sensors, and simultaneously serves as an active sensor itself by detecting reflected light properties. This multi-functionality allows the system to improve detection reliability without proportionally increasing device complexity, as the same hardware component performs multiple detection tasks.
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 the quality and coverage of the surroundings model, improving trajectory planning and reducing uncertainties, allowing for safer vehicle movements.
Implementation Method 1
detecting the surroundings of the vehicle by means of the at least one first surroundings detecting sensor
Implementation Method 2
the measure comprises illuminating the regions having low quality
Data Source
AI summary
A method for improved surroundings detection utilizing an optical sensor of a vehicle. The method includes detecting the surroundings of the vehicle and compiling a first surroundings model based on sensor data of the surroundings detecting sensor. The method also includes determining regions having low quality in the surroundings model by evaluating optical sensor data with an image evaluation device. The detectability of the regions having low quality are improved by taking a selected measure. The method also includes detecting the surroundings of the vehicle again with the optical sensor and comparing the sensor data of the optical sensor after taking the measure with the sensor data of the optical sensor prior to taking the measure. The sensor data following the measure is fused with the already existing sensor data in order to compile a second surroundings model.