Parking Area Mapping with Geofences for Autonomous Valet Parking
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Solution Overview
Problem
Current self-driving vehicle technologies face challenges in navigating complex environments like crowded city streets, limiting their ability to perform all driving tasks autonomously, and there is a need for systems that can efficiently map parking areas for autonomous parking.
Innovation Solution
A system and method for mapping parking areas using a computing device that receives designators for points of interest, drop-off, and parking locations, along with survey data from remote devices equipped with locating sensors, to generate detailed parking maps that include geofences and waypaths, enabling autonomous vehicles to park and pick up users at specific locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If autonomous vehicles are deployed to perform all driving tasks, then automation level increases, but reliability decreases due to inability to handle complex environments like crowded city streets
Solution Approach 1:
The patent segments autonomous driving into two distinct operational modes: automated valet mode for parking operations and manual mode for complex environment navigation. The system divides the driving task spectrum, allowing the automated system to handle only well-defined parking maneuvers while requiring human intervention for unpredictable situations, thereby maintaining high automation benefits while ensuring reliability through human oversight when needed.
2Productivity
If automated systems are used for all driving tasks, then productivity increases, but loss of information increases due to baffling circumstances in poorly labeled and crowded city streets
Solution Approach 1:
The system performs preliminary mapping and surveying of parking areas before autonomous operations begin. Remote devices capture and store detailed information about parking location geometries, access paths, and environmental features in advance. This pre-collected information is stored in a database and used by the automated system during operations, eliminating the need for real-time information gathering and preventing information loss in complex environments.
3Measurement precision
If remote devices with locating sensors are used for mapping, then measurement precision increases, but device complexity increases
Solution Approach 1:
The patent introduces a centralized server as an intermediary that manages the complexity of remote mapping devices. The server coordinates multiple remote devices, processes their survey data, performs geometric calculations, and generates standardized parking area models. This intermediary absorbs the computational complexity, allowing individual remote devices to remain relatively simple while achieving high measurement precision through coordinated multi-device operation and sophisticated server-side processing.
Data Source
AI summary
Aspects relate to systems and methods for mapping a parking area for autonomous parking. An exemplary method includes receiving a point of interest designator for a point of interest, a drop-off location designator for a drop-off location, a parking location designator for a parking location, and a parking path designator for a parking path between the drop-off location and the parking location, receiving survey data of the point of interest from a remote device having at least a locating sensor, wherein survey data includes a drop-off geofence for the drop-off location, a parking geofence for the parking location, and a parking waypath for the parking path, and generating a parking map for the point of interest, wherein the parking map includes the drop-off location designator, the parking location designator, the parking path designator, the drop-off geofence, the parking geofence, and the parking waypath.