Lateral Blind Spot Sensing With Optical Flow Path Prediction
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Solution Overview
Problem
Traditional advanced driver assistance systems (ADAS) and radar detection technologies fail to effectively differentiate between fixed and mobile objects, leading to unnecessary warnings and increased driver burden, and do not adequately address lateral blind spots, especially in crowded urban areas and during parking, where dangers can arise from pedestrians, animals, and other moving objects.
Innovation Solution
A mobile carrier warning sensor fusion system that includes a host connected to a light scanning unit and an image extraction unit, which scans objects on one side of the carrier, filters images using an optical flow method to predict object paths, and modifies the moving route to avoid dangerous situations by generating a second moving route that adjusts for predicted object paths and parking space constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radar detection technology is used to detect carrier surroundings, then detection coverage is improved, but the system cannot differentiate fixed or mobile objects leading to unnecessary warnings
Solution Approach 1:
The patent segments the detection system into multiple specialized units: radar detection unit for initial object detection, light scanning unit (lidar) for detailed spatial mapping, and image extraction unit for visual identification. Each unit handles specific aspects of object detection and classification, enabling the system to differentiate between fixed and mobile objects more effectively than a single radar system.
Solution Approach 2:
The host computer acts as an intermediary that integrates data from radar, light scanning, and image extraction units. It processes information from multiple sources to determine object mobility status, resolving the limitation of radar alone by combining multiple detection modalities to achieve accurate object classification.
2Reliability
If traditional ADAS warning systems are used, then driver protection is provided, but unnecessary warnings increase driver burden and bother
Solution Approach 1:
The system performs preliminary classification of detected objects using light scanning and image extraction before generating warnings. By pre-identifying whether objects are fixed or mobile and assessing their potential threat level, the system filters out non-threatening detections, reducing unnecessary warnings while maintaining comprehensive driver protection.
Solution Approach 2:
The system implements feedback mechanisms where warning generation is based on integrated analysis from multiple sensor units. The host continuously monitors object trajectories, speeds, and positions, adjusting warning generation dynamically based on real-time assessment of actual threat levels, thereby reducing false alarms while maintaining safety.
3Ease of manufacture
If dash cams are disposed only on front and rear sides, then cost is reduced, but lateral blind spots remain undetected
Solution Approach 1:
The light scanning unit and image extraction unit are designed to perform multiple functions: they detect objects in lateral blind spots, track object trajectories, classify objects as fixed or mobile, and provide data for route prediction. This multi-functionality allows comprehensive blind spot coverage without proportionally increasing system cost, as these units supplement rather than completely replace traditional cameras.
Solution Approach 2:
The patent introduces light scanning (lidar) which adds a new dimensional capability for detecting lateral blind spots that traditional front and rear cameras cannot cover. By adding this vertical/dimensional layer of detection capability, the system achieves comprehensive 360-degree awareness including previously undetectable lateral zones without requiring cameras on all sides.
4Measurement precision
If image optical flow method is used to classify object images, then object path prediction accuracy is improved, but processing complexity increases
Solution Approach 1:
The processing system is segmented into specialized units: the light scanning unit handles spatial mapping, the image extraction unit handles visual data capture, and the host computer performs optical flow analysis. By dividing the complex processing task across specialized components, the system achieves high path prediction accuracy while managing processing complexity through functional specialization and distributed computation.
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 provides effective prediction and prevention of dangerous situations by identifying and adjusting for lateral blind spots, enhancing driver safety during parking and navigation through crowded areas by intervening driving control and notifying the driver.
Implementation Method 1
a light scanning unit (20) disposed on one side of the mobile carrier (V)
Implementation Method 2
an image extraction unit (30) disposed on one side of the mobile carrier (V)
Data Source
AI summary
The present application is to provide a system for sensing and responding to a lateral blind spot of a mobile carrier and method thereof, which is applied for a mobile carrier during moving to a parking place. Firstly, a light scan unit and a depth image capture unit are used to scan a plurality of surrounding objects and capture a plurality of object depth images of the surrounding objects, and then a plurality of screened images are obtained according to a moving route of the mobile carrier for further obtaining correspondingly a plurality of forecasted lines to generate corresponded notice message for noting driver or ADAS. Due to the objects corresponding to the screened images and located on a blind position which is at one side of the mobile carrier, the notice message provides the driver preventing from the ignored danger by ignoring the blind position.