Adaptive Driver Assistance With AR Guidance and Skill-Based Intervention
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Solution Overview
Problem
High-performance sports cars are underutilized on public roads due to speed limits, and inexperienced drivers struggle to optimize performance and safety while driving on tracks, as existing driver assistance systems primarily focus on current vehicle dynamics without considering future paths or optimizing cost functions like time or mileage.
Innovation Solution
A method for performance-enhancing driver assistance that uses a localization device, ADAS sensors, and a calculation unit to optimize a cost function by determining an optimal trajectory and suggesting corrective actions through an augmented reality interface, while also actively assisting the driver with actuator devices to maintain safety and improve driving skills.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If electronic driver assistance devices continuously intervene to prevent dangerous situations, then safety is improved, but driving pleasure and performance enjoyment are reduced
Solution Approach 1:
The system dynamically adjusts the level of assistance based on driver skill level and situation criticality. Less experienced drivers receive more guidance and intervention, while experienced drivers receive minimal interference, allowing them to enjoy full driving pleasure while maintaining safety standards.
Solution Approach 2:
Different levels of assistance are provided in different driving situations and to different drivers. The system selectively applies electronic driver assistance only where needed based on real-time assessment of driver capability and situational risk, rather than uniform continuous intervention.
2Productivity
If driver assistance systems provide comprehensive real-time guidance, then driver performance is improved, but information overload occurs reducing driver attention
Solution Approach 1:
The system provides only the necessary amount of information for the current driving situation and driver skill level, rather than overwhelming the driver with all possible data. Information is filtered and prioritized to maintain optimal attention without overload.
Solution Approach 2:
The system monitors driver responses and performance in real-time, adjusting the amount and type of information provided based on driver skill assessment and current performance needs, creating an adaptive information delivery system.
3Productivity
If informative messages are provided to help drivers optimize performance, then driving skill development is improved, but the complexity of the interface increases
Solution Approach 1:
The interface complexity adapts dynamically to driver skill level. Less experienced drivers receive more detailed guidance and information, while experienced drivers receive simplified, minimal information, keeping the interface appropriately complex for each user.
Solution Approach 2:
Different interface elements and information types are activated based on specific driving situations and individual driver needs, rather than providing all possible information simultaneously. The interface presents only locally relevant information for each context.
Data Source
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AI summary
A method for the performance-enhancing driver assistance of a road vehicle (1) driven by a driver (DR). The method comprises the steps of detecting a plurality of dynamic data (DD) of the vehicle (1) by means of a control system (5), suggesting to the driver (DR), by means of an interface device (9) and depending on the plurality of dynamic data (DD), one or more corrective actions (CA) to be carried out in order to accomplish a mission (M) optimizing a cost function (CF), and estimating the driving ability of the driver (DR) in order to obtain a driver rating value (DRV), based on which the corrective actions (CA) to be suggested are to be changed.