Vehicle Destination Prediction and Control System
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle navigation systems struggle to provide control information and services to drivers who do not pre-set their destinations, especially those using mobile navigation, limiting the provision of relevant information and convenience.
Innovation Solution
A method and system that predict a vehicle's destination based on driving patterns and models, generating vehicle control information to optimize operations such as fuel efficiency and accident prevention, even without explicit destination input, by using driving information and personal data to classify destinations as 'living' or 'activity' types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system provides comprehensive vehicle control information and services, then the reliability and driver benefit are improved, but the device complexity and system requirements increase
Solution Approach 1:
The system automatically predicts destination and generates control information without requiring driver input or navigation operation, making the system self-sufficient and reducing operational complexity while maintaining comprehensive control capabilities
Solution Approach 2:
The system integrates multiple functions including destination prediction, control information generation, and various vehicle operations (DPF regeneration, urea replenishment, fuel efficiency optimization) into a single unified platform, reducing overall system complexity through consolidation
2Ease of operation
If the system automatically predicts destination without user input, then the ease of operation is improved, but the measurement precision and accuracy of destination prediction may deteriorate
Solution Approach 1:
The system uses driving pattern information from multiple sources including vehicle sensors, navigation data, and historical records to continuously refine and validate destination predictions, ensuring high accuracy while maintaining automatic operation
Solution Approach 2:
The system pre-stores multiple driving models with characteristic driving patterns and destination information, allowing it to quickly match and predict destinations based on accumulated data without requiring real-time complex calculations or user input
3Productivity
If the system collects and processes extensive driving information for prediction, then the productivity and service quality are improved, but the loss of information privacy and data security risks increase
Solution Approach 1:
The system processes and analyzes driving information locally within the vehicle or in distributed segments rather than centralizing all data collection, allowing selective processing of only necessary information for destination prediction while preserving privacy-sensitive data
Solution Approach 2:
The system transforms raw driving data into aggregated driving pattern characteristics and models, changing the form of information from detailed personal data to generalized behavioral patterns that maintain predictive accuracy while reducing privacy risks
Data Source
AI summary
Provided are a method and a system for controlling at least one feature of a vehicle based on a destination predicted when a driver of the vehicle does not input a specific destination to a navigation system of the vehicle. A driving pattern is determined using driving information of a vehicle. A driving model corresponding to the driving pattern among pre-stored driving models is determined. A destination of the determined driving model is identified as a prediction destination. Control signal corresponding to the prediction destination for controlling at least one feature of the vehicle is generated for performing a vehicle operation according to the vehicle control information.