Personalized Automated Driving Feature Suggestions
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Solution Overview
Problem
Automated driving features in vehicles are often not effectively promoted to consumers, leading to a lack of awareness and utilization of available technologies that could enhance driving experiences and safety.
Innovation Solution
A method and system that analyze driving data to determine if automated features like adaptive cruise control could have been used on a specific route, generating personalized suggestions for their use and presentation to users, thereby educating them on availability and benefits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If automated driving features are made available as optional equipment, then consumers have access to advanced driving technologies, but consumer awareness and utilization of these features remain low
Solution Approach 1:
The system analyzes actual driving data to determine when automated driving features could have been used, then provides feedback to consumers through personalized suggestions. This feedback loop transforms raw driving data into actionable information that educates consumers about feature availability and benefits, directly addressing the awareness problem.
Solution Approach 2:
The system enables consumers to self-educate about automated driving features by analyzing their own driving patterns and providing personalized recommendations. Instead of relying on traditional marketing or dealer promotions, consumers receive tailored information based on their actual driving behavior, making the information delivery self-directed and highly relevant.
2Loss of information
If personalized suggestions are generated based on driving data, then consumer awareness increases, but data processing requirements increase
Solution Approach 1:
The system extracts only the essential information needed for personalized suggestions from the vast amount of driving data. By focusing on specific driving patterns and scenarios where automated features could be beneficial, the system avoids processing unnecessary data, reducing computational complexity while maintaining effectiveness.
Solution Approach 2:
The system is designed to handle multiple types of driving data and analyze them through a unified framework. By creating a multi-functional processing system that can handle various data types (location, speed, time, route) through common analysis logic, the system reduces overall complexity compared to having separate processing systems for each data type.
Data Source
AI summary
A personalized suggestion for an automated driving feature of a vehicle can be made. Driving data for a travel route of a vehicle can be received. The driving data can include vehicle data and driving environment data. Based on the received driving data, it can be determined whether an automated driving feature could have been used for at least a portion of the travel route. Responsive to determining that the automated driving feature could have been used for the at least a portion of the travel route, a suggestion for using the automated driving feature can be generated. The suggestion can be presented to a user, such as the driver of the vehicle, or caused to be presented to the user. The automated driving feature may be currently included on the vehicle, or it may not be currently included on the vehicle.