In-Parking Navigation Using Multi-Modal Trajectory Tracking
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Solution Overview
Problem
Existing navigation systems face challenges in accurately guiding vehicles to vacant parking spaces within parking facilities without positioning satellite coverage, such as GPS, due to signal interference or loss of line-of-sight, and lack of real-time occupancy data, leading to inefficient parking experiences.
Innovation Solution
The system utilizes multi-modal trajectories from mobile device sensor data, including accelerometers, gyroscopes, and magnetometers, to estimate parking occupancy levels and navigate vehicles to vacant spaces by tracking vehicle and pedestrian movements within parking facilities, even without GPS signals, using machine learning models for predictive analytics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS satellite positioning is used for navigation, then positioning accuracy is improved, but navigation reliability deteriorates in areas with signal interference or loss of line-of-sight to satellites
Solution Approach 1:
The patent introduces intermediate positioning markers (beacons) deployed within the parking facility as mediators between the vehicle's navigation system and the external GPS satellites. These beacons transmit signals that can be received and processed by the mobile device even when direct satellite signals are blocked, enabling continuous positioning and navigation throughout the parking facility including underground levels.
Solution Approach 2:
The patent replaces the satellite-based electromagnetic positioning system with a local wireless signal-based positioning system using deployed beacons. This substitution allows the navigation system to function independently of satellite signals by using locally generated radio frequency signals from beacons as the positioning reference.
2Device complexity
If traditional navigation systems without real-time occupancy data are used, then system complexity is reduced, but parking efficiency deteriorates due to inability to guide vehicles to vacant spaces
Solution Approach 1:
The patent implements a self-service positioning system where mobile devices carried by users automatically track their own trajectories through the parking facility using sensor fusion (accelerometer, gyroscope, magnetometer data). The system processes local beacon signals and multi-modal trajectory data to independently determine positioning and occupancy information without requiring complex centralized infrastructure or real-time operator intervention.
Solution Approach 2:
The patent creates a multi-functional navigation system that simultaneously provides positioning, occupancy estimation, and route guidance to vacant spaces. The same infrastructure of deployed beacons and mobile device processing serves multiple purposes: tracking vehicle trajectories, estimating parking occupancy levels, and guiding users to available spaces, eliminating the need for separate systems for each function.
3Measurement precision
If parking facility operators manually monitor and report occupancy data, then data accuracy is improved, but operational cost and time consumption increase significantly
Solution Approach 1:
The patent implements a feedback-based occupancy estimation system where the navigation system continuously collects trajectory data from multiple users, processes this information to update occupancy status in real-time, and uses this updated information to guide subsequent users. The system automatically feeds back occupancy levels to the navigation algorithm, enabling dynamic route optimization without manual intervention.
Solution Approach 2:
The system performs self-monitoring of occupancy by automatically processing trajectory data from mobile devices. Instead of requiring operators to manually count and report parking space availability, the system autonomously estimates occupancy levels by analyzing the collected trajectory information from users navigating the facility.
Data Source
AI summary
An approach is provided for in-parking navigation based on mobile device sensor data, the resulted semantic events, and an estimated parking occupancy level. The approach, for example, involves receiving parking information from in-parking navigation system(s) of vehicle(s) and/or mobile device(s) associated with the vehicle(s) traveling in a parking facility with no or a positioning satellite coverage below a threshold. The parking information indicates parking spot location(s) occupied by the vehicle(s). The in-parking navigation system(s) determines the at least one parking spot location based on tracking multi-modal trajectories of the mobile device(s). The multi-modal trajectories comprise vehicle trajectory segment(s) traveling within the parking facility and pedestrian trajectory segment(s) traveling to/from pedestrian entry or exit point(s) of the parking facility. The approach also involves determining an occupancy level of the parking facility based on the parking information. The approach further involves providing the occupancy level of the parking facility as an output.