Drowsy Driving Detection With Safe Shoulder Lane Change Control
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Solution Overview
Problem
Fatal accidents due to driver drowsiness on highways are increasing, and existing vehicle systems lack effective solutions to autonomously detect and respond to drowsy driving situations to prevent such incidents.
Innovation Solution
A driver assistant system equipped with an internal camera to detect drowsiness, sensors for front and rear views to assess the environment, and a controller that processes data to transmit control signals to braking or steering devices to safely stop the vehicle on the shoulder, using a combination of cameras, LiDAR, and radar for object detection and lane change decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple sensors and cameras are installed to detect drowsy driving and surrounding objects, then detection accuracy and safety are improved, but device complexity and cost increase
Solution Approach 1:
The patent combines multiple detection functions into a single integrated driver assistant system that processes data from the internal camera, first sensor, and second sensor through a unified controller. This merging approach maintains high detection accuracy while reducing overall system complexity by consolidating multiple independent systems into one coordinated unit.
Solution Approach 2:
The controller performs multiple functions including processing drowsiness data from the internal camera, processing object detection data from both sensors, determining lane change feasibility, and controlling braking and steering devices. This multi-functionality reduces the need for separate dedicated systems for each function.
2Reliability
If the system autonomously performs lane change and stopping operations, then driver safety is improved, but the extent of automation increases system complexity
Solution Approach 1:
The system performs preliminary detection and assessment actions before executing autonomous lane change and stopping operations. The controller first determines whether lane change is possible by processing sensor data about surrounding objects, then proceeds to autonomous control only when safe conditions are confirmed. This preliminary assessment reduces automation complexity by maintaining human oversight for critical decisions.
Solution Approach 2:
The system continuously monitors driver state through the internal camera and surrounding environment through sensors, providing feedback to the controller which adjusts control actions accordingly. This feedback mechanism enables safe automation by allowing the system to respond to changing conditions while maintaining appropriate levels of autonomous control.
3Measurement precision
If the system processes multiple data sources simultaneously to make lane change decisions, then decision accuracy is improved, but processing time and computational load increase
Solution Approach 1:
The system performs preliminary processing of sensor data to determine lane change feasibility before executing the actual lane change maneuver. By pre-assessing whether the lane change is possible based on processed sensor information, the system reduces real-time processing requirements during critical maneuver execution.
Solution Approach 2:
The decision-making process is segmented into distinct stages: first processing drowsiness detection data, then processing object detection data from sensors, then determining lane change feasibility, and finally executing control actions. This segmentation allows complex multi-source data processing to occur in manageable stages rather than simultaneously.
Data Source
AI summary
Provided is a driver assistance system including an internal camera installed in a vehicle to detect whether a driver is in a drowsy driving, and configured to photograph a state of eyes of the driver to acquire drowsiness data, a first sensor installed in the vehicle to have a front-side view of the vehicle, and configured to acquire first sensor data to detect an object in the front-side view, a second sensor installed in the vehicle to have a rear-side view of the vehicle and configured to acquire second sensor data to detect an object in the rear-side view, and a controller including at least one processor configured to process the drowsiness data, the first sensor data, and the second sensor data, wherein the controller is configured to: if a result of processing the drowsiness data is that the driver has closed the driver's eyes for a predetermined time or longer, transmit a control signal to at least one of a braking device or a steering device to perform a lane change for stopping the vehicle based on a result of processing the first sensor data and the second sensor data.