Driving Mode Decision Support for Autonomous Vehicles
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
There is a challenge in determining when a driver should choose to drive manually and when to let an autonomous vehicle take control, especially considering varying driving preferences and road conditions, which affects the driving experience and safety.
Innovation Solution
A method and system that provide driving mode decision support by receiving a user's driving profile and querying segment information, including a model driver profile, to determine the most suitable driving mode for each road segment, allowing users to select between manual, semi-autonomous, or fully autonomous driving based on their preferences and road conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system provides detailed driving mode recommendations based on multiple profiles and road segments, then the quality of decision support improves, but the system complexity increases
Solution Approach 1:
The system segments the driving route into multiple road segments and applies different driving mode recommendations to each segment based on specific characteristics (curvature, traffic lights, pedestrian crossings). This allows the complex decision support task to be divided into manageable segment-level decisions, improving reliability without overwhelming system complexity.
Solution Approach 2:
The system applies different driving mode recommendations to different road segments based on local characteristics. Each segment receives customized recommendations tailored to its specific features (e.g., curved segments suggest manual driving, straight segments with traffic lights suggest autonomous driving). This local customization improves decision quality while maintaining manageable system complexity through modular processing.
2Measurement precision
If the system integrates multiple driving profiles and road segment characteristics, then the accuracy of driving mode recommendations improves, but the information processing requirements increase
Solution Approach 1:
The system pre-processes and stores characteristics of multiple driving profiles and road segments before generating recommendations. By having this information readily available in structured formats, the system can quickly retrieve and compare relevant data during runtime, improving recommendation accuracy without excessive information processing load during actual operation.
Solution Approach 2:
The system extracts only the most relevant characteristics from the comprehensive set of driving profiles and road segment data for each specific recommendation. Instead of processing all available information, it selectively extracts key features (e.g., curvature for manual/autonomous decisions, traffic light presence for mode selection), reducing information processing requirements while maintaining high recommendation accuracy.
Data Source
AI summary
A driving mode decision support for a decision to select a driving mode of driving on at least one road segment is provided to a user of an autonomous vehicle. A driver driving profile of a user is received. Segment information defining the at least one road segment is queried. The segment information includes at least a model driver driving profile associated with the at least one road segment. A driving mode decision support for the user is determined for the at least one road segment based on the driver driving profile of the user and the model driver driving profile. An indication of the driving mode decision support is provided to the user. The driving mode decision support includes a recommended driving mode of driving on the at least one road segment.