Vehicle V2V Drowsiness Detection and Avoidance Control
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Solution Overview
Problem
Current Advanced Driver Assist Systems (ADAS) do not effectively account for the driver state of surrounding vehicles, which can impact driving conditions, leading to potential safety hazards due to drowsy drivers.
Innovation Solution
A vehicle system that communicates with surrounding vehicles to detect driver drowsiness and adjust its speed and direction to avoid them, using a communicator, detector, driving assistance module, and controller to receive and analyze driver state information, determine drowsiness, and control the vehicle's speed and direction accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the vehicle uses Advanced Driver Assist Systems to monitor driver status and surrounding environment, then driving convenience and information provision are improved, but the system cannot effectively respond to drowsy drivers in surrounding vehicles, creating a safety hazard
Solution Approach 1:
The patent uses communication modules as intermediaries to transmit driver state information from surrounding vehicles to the host vehicle's controller. This allows the host vehicle to obtain information about drowsy drivers in surrounding vehicles without directly monitoring them, resolving the information loss problem while improving safety through V2V communication.
Solution Approach 2:
The system performs preliminary detection and analysis of driver state information from surrounding vehicles before actual collision risks arise. By continuously receiving and analyzing driver state data, the system can predict potential hazards from drowsy drivers and take preventive actions, improving reliability through advance warning.
2Reliability
If the vehicle continuously receives and analyzes driver state information from surrounding vehicles to determine drowsiness, then driving safety is improved, but communication energy and processing time are increased
Solution Approach 1:
The controller periodically receives driver state information from surrounding vehicles at predetermined time intervals rather than continuously. This periodic sampling approach maintains adequate detection accuracy for identifying drowsy states while significantly reducing communication energy consumption and processing loads compared to continuous monitoring.
Solution Approach 2:
The system selectively processes only the necessary driver state information parameters required for drowsiness detection, rather than analyzing all available data. This partial action approach achieves sufficient detection reliability while minimizing energy consumption and processing requirements.
3Reliability
If the vehicle automatically controls driving assistance module to avoid surrounding vehicles with drowsy drivers, then safety is improved, but driver autonomy and control precision may be reduced
Solution Approach 1:
The system provides feedback to the driver by notifying them of detected drowsy drivers in surrounding vehicles and the automated avoidance actions taken. This feedback mechanism maintains driver awareness and control authority while enabling automated safety interventions, resolving the contradiction between autonomous protection and driver autonomy.
Solution Approach 2:
The system applies preliminary anti-action by automatically adjusting driving parameters to prevent collision with drowsy drivers before a hazardous situation develops. The controller proactively controls the driving assistance module to maintain safe distances or change lanes, preventing potential accidents while preserving driver choice through notification.
Data Source
AI summary
A vehicle may include a communicator configured to receive driver state information from a surrounding vehicle, a detector configured to obtain driving information related to surrounding vehicle, a driving assistance module configured to control at least one of a driving speed or a driving direction and a controller configured to determine whether a driver of the surrounding vehicle is in drowsiness state based on whether the received driver state information satisfies a predetermined condition and if the driver of the surrounding vehicle is determined as drowsiness state, control the driving assistance module to avoid the surrounding vehicle.