Vehicle Control Method for Drowsy Driver Air Circulation
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Solution Overview
Problem
Current vehicle systems fail to effectively prevent driver drowsiness and resulting accidents by inadequately controlling air circulation, leading to decreased air-conditioner efficiency and increased carbon monoxide levels, which can cause distraction and decreased driver alertness.
Innovation Solution
A vehicle control method that acquires driver state information using cameras and sensors to determine drowsiness, adjusts air circulation modes based on indoor air quality, and switches to autonomous driving when drowsiness is detected, utilizing AI processing to improve reliability and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If outside air circulation mode is used to prevent driver drowsiness, then driver alertness is improved, but air-conditioner efficiency deteriorates due to increased indoor temperature
Solution Approach 1:
The system dynamically changes air circulation parameters (switching between inside and outside air circulation modes) based on real-time driver state detection. When driver drowsiness is detected, the system switches to outside air circulation to refresh the air and improve alertness, while normally operating in inside air circulation mode to maintain energy efficiency.
2Use of energy by moving object
If inside air circulation mode is used to maintain energy efficiency, then air-conditioner efficiency is improved, but driver alertness deteriorates due to increased carbon monoxide concentration
Solution Approach 1:
The system implements a feedback mechanism where driver state (alertness/drowsiness) is continuously monitored using cameras and sensors. Based on this feedback, the air circulation mode is automatically adjusted - switching to outside air circulation when drowsiness is detected and returning to inside air circulation when the driver is alert, thus balancing energy efficiency and driver safety.
3Device complexity
If manual driver monitoring is used to detect drowsiness, then system complexity is reduced, but detection precision deteriorates
Solution Approach 1:
The system employs a camera that serves multiple functions: capturing driver images for drowsiness detection, monitoring driver behavior, and potentially other vehicle safety functions. This multi-functional approach improves detection precision without proportionally increasing system complexity, as the same hardware component performs multiple tasks.
4Reliability
If autonomous driving mode is activated to prevent accidents, then driver safety is improved, but ease of operation deteriorates
Solution Approach 1:
The system dynamically switches between manual driving mode and autonomous driving mode based on real-time driver state assessment. When the driver is alert, manual control is maintained for ease of operation. When drowsiness is detected, the system automatically transitions to autonomous mode to ensure safety, creating a dynamic balance between driver control and safety.
Data Source
AI summary
A vehicle control method is disclosed. A vehicle control method according to an embodiment of the present disclosure can determine a drowsy state of a driver through AI processing of state information of the driver acquired from a sensor included in a vehicle. A processor can control a carbon dioxide concentration, a carbon monoxide concentration, a fine dust concentration and cooling efficiency inside the vehicle by causing the outside air to enter the vehicle or circulating the air inside the vehicle upon determining that the driver is in a drowsy state. The processor outputs a second warning and controls driving of the vehicle according to the second warning upon determining that the driver is continuously in the drowsy state. Accordingly, occurrence of accidents due to drowsiness of the driver can be reduced. One or more of an (autonomous vehicle, a user terminal and a server) of the present disclosure can be associated with artificial intelligence modules, drones (unmanned aerial vehicles (UAVs)), robots, augmented reality (AR) devices, virtual reality (VR) devices, devices related to 5G service, etc.