Automated Driving Takeover Practice by Scene and Driver Proficiency
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Solution Overview
Problem
Conventional automated driving systems often request drivers to take back control in inappropriate driving scenes, leading to inefficient practice and potential safety issues due to infrequent practice in varied driving conditions.
Innovation Solution
A vehicle control device that calculates a proficiency level for taking back driving based on time and actions, identifies current driving scenes, and adjusts practice frequency and intervals accordingly to ensure suitable practice in various driving scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the automated driving system requests drivers to take back control in various driving scenes without selection, then the system can maintain basic automation functionality, but the driver practice becomes inefficient and safety is compromised due to inappropriate practice scenarios
Solution Approach 1:
The patent applies local quality by evaluating and selecting specific driving scenes based on their suitability for taking back driving practice. Instead of uniformly applying practice requests across all driving scenes, the system identifies scenes with specific characteristics (e.g., low traffic density, simple road geometry, favorable weather conditions) and selectively requests practice only in those appropriate local contexts, thereby maintaining both adaptability and safety.
Solution Approach 2:
The system performs preliminary evaluation of driving scenes before requesting taking back driving practice. By pre-assessing scene suitability using surrounding data and predefined criteria, the system prepares and selects appropriate practice opportunities in advance, ensuring that practice requests are only made when conditions are favorable, thus preventing unsafe practice scenarios.
2Reliability
If the automated driving system limits taking back driving practice to only suitable driving scenes, then safety is improved, but the frequency and variety of practice opportunities are reduced
Solution Approach 1:
The patent applies dynamics by adaptively adjusting the frequency and timing of taking back driving practice requests based on the driver's proficiency level and the current driving scene characteristics. The system dynamically modifies practice opportunities to maximize both safety and frequency - increasing practice frequency in suitable scenes while maintaining safety constraints, rather than using a fixed or overly restrictive approach.
Solution Approach 2:
The system implements feedback mechanisms to evaluate driver performance during taking back driving practice and uses this information to adjust future practice requests. By monitoring driver responses and proficiency development, the system optimizes the frequency and selection of practice opportunities, ensuring adequate practice frequency while maintaining safety through continuous assessment of driver capability.
3Productivity
If the automated driving system requests taking back driving frequently to improve driver proficiency, then driver skill improvement is accelerated, but the practice may occur in inappropriate driving scenes causing safety issues
Solution Approach 1:
The patent applies parameter changes by evaluating multiple parameters of the driving scene (traffic density, road type, weather conditions, surrounding vehicles) and the driver's current state (proficiency level, attention status) to determine optimal practice opportunities. The system adjusts the frequency and timing of practice requests by changing these evaluation parameters dynamically, ensuring high-frequency practice occurs only when scene parameters indicate safety, thus resolving the contradiction between proficiency improvement speed and safety.
Data Source
AI summary
A control device is configured to: perform automated driving for automatically performing driving operations of the vehicle; make a driver practice taking back driving from automated driving to manual driving, where at least part of the driving tasks are performed by the driver, during automated driving and calculate proficiency level of taking back driving based on one or both of a time period required for taking back driving when practicing taking back driving and action of the driver in the period for taking back driving; identify a current driving scene based on surrounding data showing a state of the surroundings of the vehicle; and practice taking back driving by a frequency in accordance with the proficiency level calculated when last practicing taking back driving in the same driving scene as the present.