Windshield Edge Alerting for Driving Assistance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing driving assistance technologies fail to accurately estimate the possibility of collisions by not considering the behavior intention of pedestrians or other vehicles, leading to inappropriate alerts and low assistance levels.
Innovation Solution
A driving assistance system that predicts the behavior of moving objects within a predetermined range using behavior prediction information, including predicted route information and priority settings, and outputs alerts based on this information at the edge of the windshield, utilizing a processor and communication networks for accurate alert level determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If alert level is determined based only on current sensor information (distance, relative velocity), then the system responds quickly to detected objects, but the accuracy of collision possibility estimation deteriorates
Solution Approach 1:
The system performs preliminary action by acquiring behavior prediction information (such as planned routes, destination information, or intended maneuvers) from external sources before determining the alert level. This allows the system to anticipate future behavior of other vehicles and pedestrians, improving collision possibility estimation accuracy without sacrificing response speed, as the prediction data is prepared in advance
Solution Approach 2:
The patent introduces behavior prediction information as an intermediary element that mediates between current sensor data and alert level determination. This intermediary layer processes and integrates prediction data from external sources with real-time sensor information, enabling accurate collision estimation while maintaining fast response through structured information fusion
2Reliability
If the system issues alerts for all detected objects regardless of behavior intention, then no potential risks are missed, but driver distraction increases due to excessive alerts
Solution Approach 1:
The system applies local quality by differentiating alert levels based on the specific behavior intention of each detected object. Instead of uniform alerting, the system tailors the alert level (high, medium, low) to the local characteristics of each object's intended behavior, such as whether a pedestrian plans to cross the road or another vehicle intends to change lanes, thereby reducing unnecessary alerts while maintaining comprehensive risk detection
Solution Approach 2:
The patent utilizes parameter changes by varying the alert level parameter according to behavior prediction information. The system changes the alert parameter dynamically based on predicted behavior intentions, such as adjusting from high alert for objects with collision-intent behavior to low alert for objects with no collision intention, thus maintaining reliability while reducing driver distraction from excessive high-level alerts
3Measurement precision
If behavior prediction information from external networks is integrated, then alert accuracy improves, but system complexity increases
Solution Approach 1:
The system achieves universality by designing a multi-functional processing unit that handles both real-time sensor data and behavior prediction information from external networks. This unified processor performs multiple functions including data acquisition, prediction information integration, collision possibility estimation, and alert level determination, thereby improving alert accuracy while managing system complexity through functional consolidation
Solution Approach 2:
The patent employs an intermediary processing layer that standardizes the integration of behavior prediction information from external networks with internal sensor data. This intermediary module acts as a buffer and translator, converting diverse external prediction data into a unified format that can be processed by the existing alert determination system, thus improving accuracy without proportionally increasing overall system complexity
Data Source
AI summary
A driving assistance apparatus includes a memory and a processor having hardware. The processor is configured to acquire behavior prediction information of a moving object within a predetermined range centered on a subject vehicle to which driving assistance is applied, predict behavior content of the moving object within the predetermined range based on the acquired behavior prediction information of the moving object, and output a notification of an alert level corresponding to the predicted behavior content of the moving object at an edge of a windshield corresponding to a side on which the moving object, the behavior content of which has been predicted, exists, with respect to the position of a driver.