Automotive Sensor Fusion Module for Synchronized Object Detection
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Solution Overview
Problem
Advanced driver assistance systems (ADAS) and autonomous vehicles face challenges in synchronizing object detection across sensors disposed at different positions, leading to difficulties in accurately identifying objects outside a vehicle due to varying sensing periods and data formats.
Innovation Solution
An automotive sensor integration module that includes a plurality of sensors such as optical cameras, infrared cameras, radar, and lidar, with a signal processing unit to synchronize detection data from these sensors based on their respective sensing periods and output synchronized data, while also detecting and blocking malfunctioning sensors to ensure accurate object classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple sensors are disposed at different positions to detect objects, then the coverage area is improved, but the synchronization of detection data becomes difficult
Solution Approach 1:
The system segments detection data from different sensors (camera, radar, lidar) with different sensing periods, converting them into separately synchronized data streams that can be processed and integrated without mutual interference, thus maintaining both wide coverage and synchronization accuracy
Solution Approach 2:
A central processing unit acts as an intermediary that receives detection data from multiple sensors disposed at different positions, standardizes their different data formats and sensing periods, and integrates them into synchronized detection results, enabling both spatial distribution and temporal coordination
2Reliability
If sensors with different sensing periods are used, then the detection capability is improved, but the data synchronization complexity increases
Solution Approach 1:
The system changes the parameter of data representation by converting detection data from sensors with different sensing periods into a standardized format with unified time parameters, enabling synchronization without requiring complex coordination mechanisms while preserving the unique detection capabilities of each sensor type
3Measurement precision
If multiple types of sensors are integrated, then the object identification accuracy is improved, but the system complexity increases
Solution Approach 1:
The system merges detection data from multiple sensor types (camera, radar, lidar) that have different sensing periods and data formats into unified synchronized detection data, achieving improved object identification accuracy while managing system complexity through standardized processing procedures
Data Source
AI summary
An automotive sensor integration module including a plurality of sensors which differ in at least one of a sensing period or an output data format, and a signal processing unit configured to synchronize, when a malfunctioning sensor is detected from among the plurality of sensors, pieces of detection data output from remaining sensors other than the detected sensor to substantially simultaneously output the synchronized data as sensing data.