Perimeter Sensor Housing Layout to Reduce Blind Spot Occlusion
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Solution Overview
Problem
Self-driving vehicles face challenges in detecting and classifying objects immediately adjacent to them due to blind spots and occlusions in sensor fields of view, which can impact driving decisions and autonomous operations.
Innovation Solution
An external sensing module is configured with a lidar sensor and an image sensor co-located in a single housing section, along with additional sensors like radar, to provide a comprehensive view of the environment, including a close-in camera system that classifies objects within a threshold distance of the vehicle, minimizing blind spots and occlusions by careful sensor positioning and illumination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are positioned to cover the immediate vicinity of the vehicle, then object detection capability is improved, but blind spots and occlusions worsen due to sensor housing interference
Solution Approach 1:
The patent positions the image sensor in a vertically aligned second housing section separate from the horizontally arranged lidar sensor, utilizing the vertical dimension to eliminate occlusions. This spatial separation in multiple dimensions allows both sensors to maintain unobstructed fields of view of the immediate vehicle vicinity, resolving the contradiction between detection capability and blind spots.
2Device complexity
If multiple sensor types are co-located in a single housing, then device complexity is reduced, but sensor interference worsens
Solution Approach 1:
The patent divides the sensor system into multiple housing sections: a first housing section for the lidar sensor and a vertically aligned second housing section for the image sensor. This segmentation physically separates the sensors to eliminate interference while maintaining integration benefits, resolving the contradiction between reduced complexity and sensor interference.
3Measurement precision
If the image sensor is positioned to capture close-in objects, then classification accuracy is improved, but field of view obstruction worsens due to housing structure
Solution Approach 1:
The image sensor is positioned in a second housing section vertically aligned with the lidar sensor's first housing section. This vertical separation eliminates field of view obstructions caused by horizontal housing structures, allowing the image sensor to capture unobstructed views of close-in objects for accurate classification while maintaining sensor integration.
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
The solution enhances object detection and classification capabilities, enabling the vehicle to distinguish between driveable and non-driveable objects, thereby improving safety and operational efficiency in autonomous driving modes by reducing reliance on conservative behaviors and enhancing sensor fusion accuracy.
Implementation Method 1
The lidar sensor is configured to detect objects in a region of an external environment around the vehicle
Implementation Method 2
The image sensor provides a selected resolution for objects within the threshold distance of the vehicle to classify objects detected by the lidar sensor
Data Source
AI summary
The technology relates to an exterior sensor system for a vehicle configured to operate in an autonomous driving mode. The technology includes a close-in sensing (CIS) camera system to address blind spots around the vehicle. The CIS system is used to detect objects within a few meters of the vehicle. Based on object classification, the system is able to make real-time driving decisions. Classification is enhanced by employing cameras in conjunction with lidar sensors. The specific arrangement of multiple sensors in a single sensor housing is also important to object detection and classification. Thus, the positioning of the sensors and support components are selected to avoid occlusion and to otherwise prevent interference between the various sensor housing elements.