Perimeter Sensor Housing Layout for Vehicle Blind Spot Detection
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Solution Overview
Problem
Autonomous vehicles face blind spots and occlusions in their sensor fields of view due to the proximity of objects and environmental obstructions, which can impact driving decisions and operations.
Innovation Solution
An integrated sensor housing system is employed, combining lidar and image sensors with careful positioning to ensure unobstructed views and overlapping fields of view, along with additional sensors like radar, to enhance object detection and classification, particularly for objects within a threshold distance of the vehicle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are positioned close to the vehicle to detect nearby objects, then object detection capability within threshold distance is improved, but blind spots and occlusions increase due to vehicle structure interference
Solution Approach 1:
The patent positions sensors in three-dimensional space around the vehicle (front, rear, sides, top) to detect objects in multiple spatial dimensions. This dimensional approach allows the system to overcome blind spots caused by vehicle structure by observing objects from multiple angles and positions simultaneously.
Solution Approach 2:
The patent integrates multiple different types of sensors (lidar, radar, cameras, ultrasonic sensors) into a unified sensor system that works together. These nested sensor types complement each other, with each sensor type detecting different aspects of nearby objects, thereby reducing overall blind spots through multi-sensor fusion.
2Loss of information
If multiple sensors are integrated in a compact housing to reduce blind spots, then object detection coverage is improved, but sensor interference increases
Solution Approach 1:
The patent assigns specific functional roles to different sensor types based on their local characteristics and optimal performance zones. Each sensor type (lidar for distance, radar for velocity, cameras for classification) is positioned and configured to exploit its unique strengths while minimizing interference with other sensors in the integrated housing.
Solution Approach 2:
The patent employs signal processing and data fusion algorithms as intermediaries to separate and process signals from different sensor types. These intermediary processing systems filter out interference and combine sensor data in a way that maintains detection accuracy while accommodating the physical proximity of multiple sensors.
3Measurement precision
If sensors are positioned to achieve overlapping fields of view for better classification, then object classification accuracy is improved, but device complexity increases
Solution Approach 1:
The patent designs the integrated sensor housing to serve multiple functions simultaneously: detection, classification, and spatial mapping. The same sensor array that provides overlapping fields of view for classification also creates a comprehensive three-dimensional map of the environment, reducing the need for separate specialized systems.
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 system effectively classifies nearby objects as driveable or non-driveable, improving the vehicle's ability to make informed driving decisions by minimizing blind spots and sensor interference.
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 is arranged along the vehicle to have an unobstructed field of view of the region of the external environment
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.