Vehicle Passenger Detection via Solid Angle and Plausibility Check
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Solution Overview
Problem
Existing methods for dynamic ride-sharing and locating passengers in vehicle systems face challenges in accurately and efficiently identifying passengers, especially in uncertain or crowded meeting points, leading to potential delays and inefficiencies.
Innovation Solution
A method and system that continuously determine the position of a vehicle and a person to be found, define a near zone, capture image data, and use a plausibility check to detect and identify the person within a solid angle, with features like augmented reality displays and navigation data to assist the driver in locating the passenger efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual passenger identification methods are used at meeting points, then system complexity is low, but detection precision and identification accuracy deteriorate leading to delays
Solution Approach 1:
The system integrates multiple functions into a single automated platform: position determination via GPS, image capture via onboard cameras, automated face recognition, and augmented reality display. This multi-functional integration resolves the contradiction by achieving high detection precision while managing system complexity through unified architecture rather than separate manual processes
Solution Approach 2:
The patent replaces manual mechanical identification processes with automated electronic systems. The driver no longer manually searches for passengers; instead, the system automatically captures images, processes them through recognition algorithms, and presents results via AR display, substituting mechanical human effort with electronic automation to improve precision
2Productivity
If automated passenger location systems are implemented, then productivity and efficiency improve, but device complexity increases
Solution Approach 1:
The system performs preliminary actions by continuously determining positions of both vehicle and passenger before the actual meeting occurs. The GPS tracking and pre-capture of position data allow the system to prepare identification in advance, improving productivity by eliminating last-minute search delays while managing complexity through proactive data collection
Solution Approach 2:
The system serves itself by automatically performing all identification tasks without requiring manual intervention from the driver. The automated image capture, processing, and AR presentation create a self-service loop that improves productivity while containing complexity within the automated system rather than requiring complex human-system coordination
3Reliability
If continuous image capture is performed to improve detection reliability, then energy consumption and processing load increase
Solution Approach 1:
The system employs periodic action by capturing images continuously only when the vehicle is within the predetermined near zone of the passenger's last known position. This periodic activation based on spatial proximity improves reliability by ensuring captures occur at appropriate moments while reducing energy consumption by avoiding continuous capture regardless of vehicle location
4Reliability
If the search area is expanded to cover larger zones, then the probability of finding the passenger increases, but the time required for detection increases
Solution Approach 1:
The system applies local quality by concentrating the search effort in the specific near zone surrounding the passenger's last known position rather than expanding the search uniformly across large areas. This localized approach improves reliability by focusing computational resources on the most probable location while minimizing detection time by avoiding unnecessary searches in distant areas
Data Source
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AI summary
The invention relates to a method for the detection of one or more persons by a vehicle (10), said method comprising the following steps: determining (S01) at least once a position of a person (12) to be detected and ascertaining a local zone (30) around this position, wherein the local zone (30) is defined at least by a predetermined maximum distance from this position; determining (S02) continuously a current position of the vehicle (10); automatic continuous recording (S03) of image data which represents the surroundings of the vehicle (10), while the current position of the vehicle (10) within the local zone (30) that was most recently ascertained (S01) is determined (S02); determining (S04) at least once a solid angle (32) which comprises that position of the person (12) to be detected which was most recently determined (S01) proceeding from the current position of the vehicle (10); identifying (S05) persons (12, 14) in the solid angle (32) which was determined most recently in the image data recorded (S03); detecting (S06) the person (12) to be detected among the persons identified (12, 14) by means of a plausibility operation.