Autonomous Parking Preference Management
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Solution Overview
Problem
Current autonomous parking systems do not allow for personalized parking preferences, which can affect the comfort and safety of drivers and occupants during ingress and egress.
Innovation Solution
A system that associates driver and occupant parking space preferences with identified individuals, using sensors and a Human Machine Interface (HMI) to determine a relative parking position within a potential parking space based on these preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If autonomous parking systems use standardized positioning without personalization, then system complexity is reduced, but ingress and egress comfort deteriorates
Solution Approach 1:
The system stores parking preferences for multiple occupants in advance within the transport's memory. When an occupant enters, the system retrieves their stored preferences and applies them automatically, eliminating the need for real-time negotiation or manual adjustment during parking operations.
Solution Approach 2:
The transport system automatically identifies which occupant is present through sensors, retrieves that occupant's stored preferences, and autonomously positions the transport accordingly without requiring the occupant to manually input preferences each time.
2Adaptability or versatility
If the system accommodates multiple occupancy scenarios with different preferences, then adaptability improves, but device complexity increases
Solution Approach 1:
The system divides the occupancy space into distinct zones (driver seat, front passenger seat, rear seats) and uses sensors to identify which zone is occupied. Each zone is associated with a specific occupant profile, allowing the system to selectively apply preferences only for occupied zones rather than managing all possible scenarios simultaneously.
Solution Approach 2:
The transport system uses a single preference storage mechanism that serves multiple functions: storing preferences for different occupants, retrieving preferences based on occupancy detection, and applying preferences for various parking scenarios (parallel parking, perpendicular parking, angled parking).
Data Source
AI summary
An example operation includes one or more of associating a driver parking space preference to an identified driver of a transport, associating at least one occupant parking space preference to at least one identified occupant of the transport and determining a relative parking position within a potential parking space based on the driver parking space preference and the at least one occupant parking space preference.