Parking Facility Object Plausibility Checks for Automated Valet Guidance
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Solution Overview
Problem
Existing automated valet parking systems lack efficient infrastructure-supported assistance to ensure safe and reliable navigation through parking facilities by accurately identifying and verifying the presence of objects before initiating or continuing automated trips.
Innovation Solution
A method involving receiving area signals, comparing them to reference areas, detecting objects, checking their plausibility, and ascertaining infrastructure assistance data to guide vehicles safely, using environmental sensors and continuous data analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If environmental sensors continuously scan the area for objects during automated valet parking operations, then safety is improved by detecting potential collisions, but false detections may occur leading to unnecessary interruptions in parking operations
Solution Approach 1:
The system performs preliminary actions by continuously monitoring the area and detecting objects before the automated parking operation proceeds. Environmental sensors scan the parking area in advance to identify potential obstacles, allowing the system to prepare appropriate responses before the vehicle moves, thereby ensuring safety without causing interruptions during actual parking operations
Solution Approach 2:
The system implements feedback mechanisms where detection results are continuously analyzed and used to adjust parking operations. When objects are detected, the system provides feedback to the control unit which then determines whether to interrupt or continue operations based on plausibility assessment, creating a closed-loop system that balances safety with operational efficiency
2Object-affected harmful factors
If the system interrupts automated parking operations upon detecting any object, then collision risk is reduced, but operational efficiency deteriorates due to unnecessary stops for false detections
Solution Approach 1:
The system performs preliminary plausibility assessments of detected objects before interrupting operations. Environmental sensors detect objects and the system evaluates their plausibility as real obstacles using historical data and pattern recognition, allowing it to distinguish between genuine hazards and false detections, thereby reducing unnecessary interruptions while maintaining collision avoidance
Solution Approach 2:
The system introduces an intermediary plausibility assessment mechanism between object detection and operation interruption. Rather than directly stopping operations upon detection, the system uses environmental sensor data, historical patterns, and analysis algorithms as intermediaries to verify whether detected objects represent real collision risks, filtering out false alarms before triggering safety responses
3Productivity
If the system uses historical area data to verify object plausibility, then false detections are reduced improving operational continuity, but response time increases due to additional verification steps
Solution Approach 1:
The system performs preliminary actions by continuously storing and updating historical area data in advance during normal operations. Environmental sensor data from previous scans is saved and organized, so when new objects are detected, the system can immediately query pre-existing historical information without waiting for data collection, enabling fast plausibility verification that maintains both operational continuity and rapid response
Solution Approach 2:
The system adds another dimension by utilizing temporal data from historical scans alongside spatial object detection. Instead of relying solely on current sensor readings, the system incorporates time-based historical area information to verify object plausibility, creating a multi-dimensional verification approach that filters false detections while maintaining response speed through efficient data comparison
Data Source
AI summary
A method for the infrastructure-supported assistance of a motor vehicle during a trip guided in at least partially automated fashion within a parking facility. The method includes: receiving area signals representing an area of the parking facility at an instantaneous time; comparing the area to a reference area associated with the area to recognize a change between the area and the reference area; detecting an object located in the area, if a change is recognized between the area and the reference area, where, if an object situated in the area is detected, its existence is checked for plausibility; ascertaining infrastructure assistance data for infrastructure-supported assisting of the motor vehicle for a trip guided in at least partially automated fashion through the area, based on the checking of the existence of the object for plausibility; outputting infrastructure assistance data signals that represent the ascertained infrastructure assistance data.