AI Auto Stop Control via Traffic Data Analysis
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Solution Overview
Problem
Existing auto stop systems on vehicles lack precision in controlling engine stop and start based on traffic conditions, leading to increased driver fatigue and reduced fuel efficiency, especially in congested areas.
Innovation Solution
An artificial intelligence apparatus that utilizes traffic information and an artificial neural network-based control model to determine the optimal control mode for the auto stop system, learning from user feedback to update and personalize the system's operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If the auto stop system is activated in all situations, then fuel efficiency is improved by reducing engine idle time, but driver fatigue increases and fuel efficiency worsens in congested areas due to frequent short-cycle stop-start operations
Solution Approach 1:
The system dynamically adjusts the auto stop control strategy based on real-time traffic conditions. In congested areas with frequent stops, the system determines to maintain engine operation rather than repeatedly stopping and restarting, thereby reducing driver fatigue while optimizing fuel efficiency according to actual driving conditions
Solution Approach 2:
The system changes the operational parameters of the auto stop system based on traffic situation analysis. By analyzing traffic information and determining appropriate control modes (activation, deactivation, or maintenance), the system optimizes the balance between fuel efficiency and driver comfort for different driving scenarios
2Loss of energy
If the auto stop system operates indiscriminately without considering traffic conditions, then engine idle time is reduced, but the system fails to adapt to different driving situations leading to increased driver fatigue and reduced overall fuel efficiency
Solution Approach 1:
The system continuously analyzes traffic information and driving conditions to provide feedback for adjusting auto stop operations. By monitoring traffic patterns, stop duration, and driving conditions, the system determines the appropriate control mode to activate or deactivate the auto stop function, ensuring adaptability to varying traffic situations
Solution Approach 2:
The system segments the driving environment into different traffic condition categories (e.g., congested areas, normal traffic, highway conditions) and applies different auto stop control strategies for each segment. This allows the system to optimize fuel efficiency in suitable conditions while avoiding excessive stop-start operations in congested areas
Data Source
AI summary
An embodiment of the present invention provides an artificial intelligence apparatus for controlling an auto stop function, including: an input unit configured to receive at least one of image information or sound information with respect to a periphery of a vehicle; a communication unit configured to receive data from an external device; a storage unit configured to store a control model for the auto stop function; and a processor configured to: acquire input data with respect to traffic information through at least one of the input unit or the communication unit, acquire base data used for determining a control of the auto stop function from the input data, determine a control mode for the auto stop function by using the base data and the control model for the auto stop function, and control the auto stop function according to the determined control mode, wherein the control mode is one of an activation mode which activates the auto stop function or a deactivation mode which deactivates the auto stop function.