AVP Vehicle Identification via Driving Behavior Comparison
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Solution Overview
Problem
Existing methods for identifying AVP motor vehicles in automated valet parking systems rely on light code recognition, which can be inefficient and require additional time for vehicle localization.
Innovation Solution
A method that compares the driving behavior of an AVP motor vehicle, determined on the vehicle side, with the driving behavior of other vehicles in the same region, as determined by the infrastructure side, to identify and localize the AVP motor vehicle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If light code recognition is used to identify AVP motor vehicles, then vehicle identification can be achieved, but the process is inefficient and requires additional time for vehicle localization
Solution Approach 1:
The infrastructure determines the driving behavior of the AVP motor vehicle during manual guidance within the parking area before the AVP process officially starts. This preliminary determination of driving behavior (trajectory, speed, acceleration patterns) allows the system to pre-identify and pre-localize the vehicle, so that when the AVP process begins, the vehicle is already identified and localized, eliminating waiting time.
Solution Approach 2:
The system compares the driving behavior determined on the infrastructure side with the driving behavior determined on the motor vehicle side. This feedback mechanism verifies identification accuracy by cross-checking independently determined driving behaviors, ensuring reliable vehicle identification while maintaining efficiency.
2Productivity
If driving behavior comparison is used to identify AVP motor vehicles, then vehicle localization time is reduced, but the complexity of the identification process increases
Solution Approach 1:
The AVP motor vehicle itself determines its own driving behavior (trajectory, speed, acceleration) during manual guidance and transmits this information to the infrastructure. The infrastructure then compares this self-reported driving behavior with its own observations. This self-service approach simplifies the overall system architecture by utilizing the vehicle's own sensors and processing capabilities rather than requiring complex external identification systems.
Solution Approach 2:
The driving behavior determination system serves multiple functions: it identifies the vehicle, localizes the vehicle, and provides verification through comparison. This multi-functional approach consolidates multiple identification methods into a single unified process, reducing overall system complexity while improving efficiency.
Data Source
AI summary
A method for identifying an AVP motor vehicle for an AVP process, wherein a driving behavior of the AVP motor vehicle that is manually guided within a region of a parking area is determined on the motor vehicle side, wherein the driving behavior determined on the motor vehicle side is compared with a driving behavior, determined on the infrastructure side, of a motor vehicle located in the same region of the parking area or a plurality of motor vehicles located in the same region of the parking area in order to identify the AVP motor vehicle. Furthermore a method for identifying an AVP motor vehicle for an AVP process, to a device, to a motor vehicle, to a computer program, to a machine-readable storage medium and to a system for identifying an AVP motor vehicle for an AVP process.