Departure Time Estimation Using Vehicle and Personal Data
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Solution Overview
Problem
Existing vehicle control systems do not effectively account for user-specific data to estimate departure times, leading to inefficiencies in preparing vehicles for user arrival and optimizing fleet operations.
Innovation Solution
A method that combines vehicle-related data with personal data to estimate departure times, utilizing data from mobile devices and sensors to improve accuracy, allowing for anticipatory vehicle preparation and optimized fleet planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vehicle control systems use only vehicle-related data for departure time estimation, then system complexity is reduced, but estimation reliability deteriorates
Solution Approach 1:
The patent combines vehicle-related data (from vehicle sensors and systems) with personal data (from user mobile devices and profiles) to estimate departure times. This merging of data sources from different systems resolves the contradiction by achieving more reliable estimation through comprehensive data while managing the complexity through integrated processing architecture.
Solution Approach 2:
The system processes multiple types of data (vehicle status, user location, appointment information, historical patterns) through a unified departure time estimation algorithm. This multi-functional approach allows the same system to handle diverse data sources and provide reliable estimates without requiring separate specialized systems for each data type.
2Measurement precision
If the system collects and processes both vehicle-related data and personal data, then departure time estimation accuracy is improved, but data processing requirements increase
Solution Approach 1:
The system performs preliminary processing of personal data on user mobile devices before transmission to the vehicle system. User profiles, appointment schedules, and historical patterns are pre-processed and stored locally, reducing the computational burden on the vehicle system and minimizing energy consumption during actual departure time estimation.
Solution Approach 2:
The patent introduces an intermediary data processing layer that selectively filters and prepares personal data before combining it with vehicle-related data. This intermediary layer reduces the volume of data requiring intensive processing while maintaining estimation accuracy, thereby reducing energy consumption.
3Measurement precision
If the system uses personal data from mobile devices, then user-specific estimation accuracy is improved, but data security requirements increase
Solution Approach 1:
The system uses the mobile device as an intermediary that processes and anonymizes personal data before transmission to the vehicle system. Sensitive information is encrypted and only necessary aggregated data (such as approximate location and time patterns) are transmitted, reducing security risks while maintaining user-specific estimation accuracy.
Solution Approach 2:
The patent creates anonymized copies of personal data for processing purposes while retaining the original sensitive data securely on the user's mobile device. These copies contain only the information necessary for departure time estimation, reducing exposure of sensitive personal information while maintaining accuracy.
Data Source
AI summary
Technologies and techniques for estimating a departure time for a user of a vehicle. A departure time may be estimated for a user using a vehicle by obtaining vehicle-related data on the vehicle and obtaining personal data on the user. The departure time may be estimated on the basis of the vehicle-related data and the personal data.