Mobile Sensor Fusion for Parking Maneuver Characterization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing mapping, navigation, and location-based services struggle to accurately determine the details and characteristics of vehicle parking events, such as maneuver sequences and distance estimations, due to limitations in Global Positioning System (GPS) data and sensor accuracy.
Innovation Solution
A method and apparatus that utilize sensor data from mobile devices in vehicles to determine a sequence of semantic events and distance estimations, allowing for the detection and characterization of parking events, including the identification of parking modes and maneuvers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS data is used to determine vehicle parking events, then location information is obtained, but measurement precision and reliability are insufficient for detailed maneuver characterization
Solution Approach 1:
The patent segments the parking event detection into multiple independent sensor measurements (acceleration, velocity, position, orientation) that are processed separately and then integrated. Each sensor provides specific maneuver characteristics that, when combined, create a comprehensive picture of the parking event without relying solely on imprecise GPS data.
Solution Approach 2:
The patent merges data from multiple sensors (accelerometer, gyroscope, magnetometer, barometer, GPS) to overcome the limitations of individual sensors. By combining these diverse data sources, the system achieves both the precision needed for detailed maneuver characterization and the reliability required for accurate parking event detection.
2Measurement precision
If multiple sensors are used to capture detailed parking maneuvers, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent makes the mobile device universal by utilizing its existing multi-functional sensors (accelerometer, gyroscope, magnetometer, barometer, GPS) that serve multiple purposes. These sensors are not dedicated solely to parking detection but are general-purpose sensors that can characterize various aspects of vehicle motion, thereby reducing the need for additional specialized hardware.
Solution Approach 2:
The patent enables the mobile device to self-service the parking detection function by processing its own sensor data locally. The device's processor analyzes the sensor inputs and generates parking event characterizations without requiring external processing systems, thereby simplifying the overall system architecture despite using multiple sensors.
3Loss of information
If sensor data processing is performed to determine semantic events and distance estimations, then parking event characterization improves, but computational requirements and processing time increase
Solution Approach 1:
The patent performs preliminary action by continuously collecting and pre-processing sensor data during normal vehicle operation, so that when a parking event occurs, the data is already organized and ready for rapid analysis. This eliminates the need for real-time processing during the actual parking maneuver, reducing processing time while maintaining detailed event characterization.
4Device complexity
If GPS data is relied upon for parking detection, then system simplicity is maintained, but reliability and accuracy of parking event detection deteriorate
Solution Approach 1:
The patent introduces sensor data as an intermediary between the vehicle's motion and the parking event detection. Instead of relying directly on GPS data alone, the system uses sensor measurements (acceleration, velocity, orientation) as intermediaries to infer parking events, thereby improving reliability while maintaining reasonable system complexity.
Data Source
AI summary
An approach is provided for determining a vehicle parking event and respective characteristics using sensor data. The approach, for example, involves receiving sensor data from at least one sensor associated with a mobile device in a vehicle. The approach also involves processing the sensor data to determine a sequence of semantic events. The semantic events respectively indicate a maneuver performed by the vehicle. The approach further involves processing the sensor data to determine a distance estimation over which at least one of the semantic events is performed. The approach further involves detecting a parking event of the vehicle, a characterization of the parking event, or a combination thereof based on the sequence of semantic events and the distance estimation. The approach further involves providing the parking event, the characterization of the parking event, or a combination thereof as an output.