Vehicle Controller Detection for Fleet Wheel Misalignment Accountability
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Solution Overview
Problem
Vehicle-sharing fleet managers face difficulties in assessing when vehicle abnormalities occur and identifying the user responsible, as users often fail to report unnoticed or unreported issues.
Innovation Solution
A vehicle controller detects abnormalities using sensors and a diagnostic model, transmitting notifications to a fleet management system that associates the abnormality with the assigned user record, enabling tracking and cost allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If users are relied upon to report vehicle abnormalities, then the system is simple and low-cost, but the reliability of abnormality detection deteriorates due to unnoticed or unreported issues
Solution Approach 1:
The vehicle monitoring system performs self-diagnosis using onboard sensors and a diagnostic model to automatically detect abnormalities such as wheel misalignment, eliminating the need for user reporting while maintaining system simplicity
Solution Approach 2:
The manual user reporting process is replaced with an automated electronic monitoring system using sensors and diagnostic algorithms, transitioning from a human-dependent mechanical process to an automated technical system
2Reliability
If automated sensor-based detection is implemented, then the reliability of abnormality detection improves, but the device complexity increases due to additional sensors and diagnostic systems
Solution Approach 1:
The diagnostic model serves multiple functions by analyzing data from various sensors (steering wheel state, vehicle wheel state) to detect different types of abnormalities including wheel misalignment, making the system multi-functional rather than requiring separate specialized systems
Solution Approach 2:
The diagnostic model acts as an intermediary that processes sensor data and translates it into actionable abnormality detections, simplifying the complexity by providing a centralized interpretation layer between raw sensor data and system responses
3Loss of information
If user identification and cost allocation are implemented, then the accountability and cost recovery improve, but the information processing complexity increases
Solution Approach 1:
The system establishes a feedback loop where abnormality data is continuously tracked and associated with user records, enabling automatic cost allocation and accountability tracking without requiring complex manual intervention
Solution Approach 2:
User records are pre-established and linked to vehicle usage data before abnormalities occur, allowing for automatic identification and cost allocation when abnormalities are detected, rather than requiring complex post-event investigation
Data Source
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AI summary
A method includes detecting, by a vehicle controller (116), a vehicle abnormality based on data from one or more sensors (114) and a diagnostic model (136). The data is indicative of a steering wheel state, a vehicle wheel state, or a combination thereof such that the vehicle abnormality includes a vehicle wheel misalignment. The method further includes transmitting, by the vehicle controller (116), a notification to a fleet management system (102) in response to the vehicle abnormality being detected. The notification includes information indicative of a vehicle identification of the vehicle, the vehicle abnormality, or a combination thereof. Additionally, the method further includes associating, by the fleet management system (102), the vehicle abnormality with an assigned user record based on the information from the notification.