Autonomous Vehicle Sensor Fusion for Clearing Occluded Views
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Solution Overview
Problem
Autonomous vehicles face sensor occlusions due to positioning, environmental obstacles, and electromagnetic interference, which hinder clear detection of moving objects in target regions.
Innovation Solution
Implementing a system with multiple sensors, such as LIDAR and RADAR, to scan and adjust viewing directions to ensure a clear view of target regions by determining sensor suitability through line-of-sight and interference assessments, allowing effective monitoring of moving objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single sensor is used to monitor the target region, then the device complexity is reduced, but the reliability of detection is worsened due to sensor occlusions from positioning, environmental obstacles, and electromagnetic interference
Solution Approach 1:
The patent combines multiple sensors (LIDAR and RADAR) into a unified sensor system that collaboratively monitors the target region. The LIDAR sensor provides high-resolution spatial mapping while the RADAR sensor detects moving objects through electromagnetic waves, merging their complementary capabilities to achieve reliable detection despite individual sensor occlusions
Solution Approach 2:
The sensor system is designed with multi-functionality where each sensor type serves multiple purposes: LIDAR provides both static environment mapping and motion detection through point cloud analysis, while RADAR provides moving object detection and velocity measurement through Doppler effects, creating a universal monitoring system that handles various detection scenarios
2Reliability
If multiple sensors are deployed to overcome occlusions, then the reliability of monitoring is improved, but the device complexity increases
Solution Approach 1:
The monitoring system is segmented into specialized sensor components with distinct functions: LIDAR sensors are positioned and configured for static environment mapping and occlusion detection, while RADAR sensors are optimized for moving object detection. This segmentation allows each sensor type to excel at its specific task while contributing to overall system reliability
Solution Approach 2:
The patent introduces an intermediary processing system that receives data from multiple sensors, performs line-of-sight assessments, identifies occlusions, and coordinates sensor operations. This intermediary layer manages the complexity of multiple sensors by providing centralized control and data fusion, making the system manageable while maintaining high reliability
3Reliability
If sensors scan the entire environment including intermediate regions, then the detection coverage is improved, but the loss of time for data processing increases
Solution Approach 1:
The LIDAR sensor performs preliminary scanning of the environment to create a static point cloud map of the scene before moving object detection begins. This preliminary action identifies stationary objects, structures, and potential occlusions in advance, allowing the RADAR sensor to focus specifically on detecting changes and moving objects without processing entire static scenes repeatedly
Solution Approach 2:
The system implements partial scanning by focusing sensor attention on relevant regions: after the LIDAR creates a comprehensive environmental map, the RADAR sensor performs targeted scanning of areas where moving objects are likely to be present, rather than continuously scanning the entire environment, thus reducing processing time while maintaining detection coverage
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 ability of autonomous vehicles to navigate safely by overcoming sensor occlusions, ensuring accurate detection of moving objects in all directions and improving maneuvering capabilities.
Implementation Method 1
transmitting a laser pulse and detecting a returning pulse, if any, reflected from an object in the environment
Implementation Method 2
determining the distance to the object according to the time delay between the transmitted pulse and the reception of the reflected pulse
Implementation Method 3
emitting radio signals and detecting returning reflected signals
Implementation Method 4
distances to radio-reflective features can be determined according to the time delay between transmission and reception
Implementation Method 5
estimate relative motion of reflective objects based on Doppler frequency shifts in the received reflected signals
Data Source
AI summary
A method is provided that involves identifying a target region of an environment of an autonomous vehicle to be monitored for presence of moving objects. The method also involves operating a first sensor to obtain a scan of a portion of the environment that includes at least a portion of the target region and an intermediate region between the autonomous vehicle and the target region. The method also involves determining whether a second sensor has a sufficiently clear view of the target region based on at least the scan obtained by the first sensor. The method also involves operating the second sensor to monitor the target region for presence of moving objects based on at least a determination that the second sensor has a sufficiently clear view of the target region. Also provided is an autonomous vehicle configured to perform the method.