Collision Distance Estimation Using Multi-Sensor Fusion
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Solution Overview
Problem
Existing advanced driver assistance systems (ADAS) face challenges in accurately estimating collision distances between vehicles and objects, which can lead to vehicle accidents due to non-operation or malfunction.
Innovation Solution
A collision distance estimation device and driver assistance system that includes image acquisition, object recognition, travel detection, and collision distance calculation units, using multiple cameras and wheel sensing information to estimate both longitudinal and lateral distances, and a brake control device to prevent collisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If collision distance estimation is performed using only single sensor or simple detection methods, then device complexity is reduced, but measurement precision deteriorates leading to inaccurate distance estimation
Solution Approach 1:
The patent combines multiple sensors (cameras, LIDAR, radar) and multiple detection methods (image processing, depth mapping, motion detection) into an integrated collision distance estimation system. This merging of multiple information sources enables accurate 3D distance estimation while maintaining system manageability through unified processing architecture.
Solution Approach 2:
The system transitions from 2D image detection to 3D spatial distance estimation by incorporating depth information through multiple cameras and LIDAR. This dimensional enhancement allows accurate calculation of collision distance in three-dimensional space, resolving the limitation of planar detection.
2Measurement precision
If multiple sensors and detection methods are integrated to improve measurement precision, then collision distance estimation accuracy is improved, but device complexity increases
Solution Approach 1:
The processing unit is designed with multi-functional capabilities to handle diverse sensor inputs (camera images, LIDAR point clouds, radar data) and perform multiple detection tasks (distance estimation, collision risk assessment, object tracking). This universal processing architecture reduces the need for separate dedicated systems for each function.
Solution Approach 2:
The patent introduces intermediate processing layers that standardize and integrate data from different sensor types before final collision distance calculation. These intermediary processing stages harmonize heterogeneous data formats and enable coherent fusion of multiple sensor inputs.
3Measurement precision
If real-time collision distance estimation is performed using complex multi-sensor fusion, then measurement precision is improved, but processing time increases
Solution Approach 1:
The system performs preliminary processing of sensor data including pre-calibration of sensors, pre-segmentation of point clouds, and pre-detection of potential collision objects before actual collision distance estimation. This preliminary preparation reduces the computational burden during real-time critical operations.
Solution Approach 2:
The processing architecture implements selective and prioritized computation that skips unnecessary processing steps for low-risk situations and rushes through critical calculation paths when collision risk is detected. This adaptive processing speed optimization ensures timely responses while maintaining accuracy.
Data Source
AI summary
The present invention relates to a collision distance estimation device and a driver assistance system using the same. The collision distance estimation device includes an image acquisition unit configured to acquire images of surroundings of a vehicle to generate image information, an image reading unit configured to detect and identify an object present around the vehicle from the image information to generate object recognition information, a travel detection unit configured to generate movement distance information on the basis of wheel sensing information, steering information, and the image information, and a collision distance calculation unit configured to calculate collision distance information on the basis of the object recognition information and the movement distance information.