Driving Style Evaluation System for Autonomous Vehicles
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Solution Overview
Problem
Autonomous or semi-autonomous vehicles may lack operator trust due to differences in driving styles between human drivers and robotic systems, leading to reduced adoption of automatic driving features.
Innovation Solution
A driving style evaluation system that records and processes data during manual driving modes to determine a preferred driving style, which is then executed by the vehicle in autonomous or semi-autonomous modes, using a processor and controller to personalize driving maneuvers based on driver feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous or semi-autonomous vehicles use standardized robotic driving styles, then operational safety and consistency are improved, but operator trust and acceptance deteriorate due to style mismatches with individual driver preferences
Solution Approach 1:
The system dynamically adapts the autonomous vehicle's driving style based on the operator's detected preferences. The controller adjusts driving parameters (acceleration, braking, steering) in real-time to match the operator's individualistic driving patterns, transforming a static robotic style into a dynamic, personalized driving experience that maintains both safety and adaptability
Solution Approach 2:
The system changes driving parameters such as acceleration rates, braking force, and steering responsiveness to align with the operator's preferred driving style. By modifying these parameters based on detected operator preferences, the system resolves the contradiction between maintaining consistent safety standards and adapting to individual driving personalities
2Adaptability or versatility
If the vehicle system collects and processes extensive driving data to determine preferred driving styles, then driving style personalization is improved, but system complexity and data processing requirements increase
Solution Approach 1:
The system performs preliminary data collection during manual driving modes before autonomous operation begins. By gathering and analyzing driving data in advance, the system establishes the operator's driving style preferences beforehand, reducing the complexity of real-time decision-making during autonomous operation while still achieving personalized driving experiences
3Ease of operation
If the vehicle operates in autonomous mode with robotic control, then driver workload is reduced, but operator trust and confidence decrease due to differences in driving style execution
Solution Approach 1:
The system implements feedback mechanisms that allow the operator to express preferences and reactions to autonomous driving behaviors. By continuously monitoring operator responses and adjusting driving style accordingly, the system builds operator trust while maintaining low workload, creating a collaborative relationship between human and machine
Data Source
AI summary
A driving style evaluation system includes a processor receiving driving data associated with at least one driving style category during operations performed by a driver during a first driving mode, the processor determining a preferred driving style for each of the at least one driving style categories based on the driving data. Also included is a controller configured to execute commands associated with the preferred driving style during operation of the vehicle in a second driving mode.