Hybrid Road User Detection With Extended Sensor Validation
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Solution Overview
Problem
Current detection systems for road users, particularly cooperative sensors, face issues such as data validation limitations, sensor failure, and lack of overload protection, leading to incomplete situational awareness and potential collision warnings outside the collision avoidance area, as well as inefficiencies in processing multiple approaching vehicle positions.
Innovation Solution
A system comprising a first detection device for a primary detection area and a second detection device with a cooperative sensor that provides instruction data to extend the detection range, allowing for earlier detection of road users before they enter the primary area, using a combination of non-cooperative and cooperative sensors like radar and ADS-B systems, with a control unit for data synchronization and fusion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If cooperative sensors are used to detect road users, then detection range is extended, but data validation reliability deteriorates due to system errors and hacker attacks
Solution Approach 1:
The system merges cooperative sensors (ADS-B, transponders) with non-cooperative sensors (radar) to create a hybrid detection system. The radar provides independent validation of cooperative sensor data, while the cooperative sensors extend detection range. This combination resolves the contradiction by maintaining reliability through cross-validation while preserving extended detection range through cooperative sensor data.
Solution Approach 2:
The system implements feedback mechanisms where the radar continuously monitors and validates positions of aircraft detected by cooperative sensors. When discrepancies are detected or validation is required, the system triggers re-detection and validation cycles, providing continuous feedback to maintain data reliability while using cooperative sensor data for extended range detection.
2Measurement precision
If the second sensor validates all detected aircraft positions, then detection accuracy is improved, but processing time increases due to the need to check each aircraft individually
Solution Approach 1:
The system applies validation selectively rather than uniformly to all detected aircraft. It focuses validation resources on aircraft in critical areas (collision avoidance zones, aircraft with suspicious trajectories, or those detected only by cooperative sensors). This local quality approach maintains high detection accuracy for critical targets while reducing overall processing time by not validating every detected aircraft equally.
Solution Approach 2:
The system uses radar to create independent copies of aircraft position data for validation purposes, rather than directly processing all cooperative sensor data. This allows parallel validation processes and reduces the time penalty of validation by working with replicated data structures that can be processed efficiently.
3Reliability
If the radar search beam continuously sweeps the entire collision avoidance area, then all aircraft are detected, but detection time is excessive and cannot keep up with multiple approaching vehicles
Solution Approach 1:
The system performs preliminary detection using cooperative sensors (ADS-B, transponders) that continuously provide aircraft position data without requiring active radar scanning. This preliminary action identifies aircraft of interest before the radar needs to validate their positions, allowing the radar to focus its sweeping beam only on specific targets rather than continuously scanning the entire collision avoidance area.
Solution Approach 2:
The radar search beam pattern is made dynamic rather than static. Instead of continuously sweeping the entire collision avoidance area at uniform speed, the system adapts the beam's position, angle, and dwell time based on real-time aircraft positions, threats levels, and validation requirements. This dynamic approach maintains comprehensive detection coverage while significantly reducing overall detection time by concentrating radar resources on critical areas.
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 detection accuracy and range, enabling earlier identification of road users, improved situational awareness, and timely collision avoidance maneuvers, while addressing sensor failure and data validation limitations.
Implementation Method 1
6 shows a so-called Active Electronically Scanned Array (AESA) radar, in which the search beam is swiveled electronically
Implementation Method 2
Cooperative sensors actively announce their position and possibly other data such as speed/identification via appropriate communication devices (e.g. via radio)
Data Source
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AI summary
A device for detecting a road user 50 comprises a first detection device 110 for detecting road user 50 in a first detection area 115. First detection device 110 is designed to repeatedly detect first detection area 115 and to prevent road user 50 from entering first detection area 115 detect and/or to detect the road user 50 in an extended first detection area 215 in response to a briefing in an angular section 11 beyond the first detection area 115 . The device further comprises a second detection device 120 for detecting road user 50 in a second detection area 125 and is designed to provide data about road user 50 required for the instruction in response to the detection of road user 50 and to transmit it to the first detection device 110 for instruction . As a result, the road user 50 can be detected by the first detection device 110 before entering the first detection area 115 .