Directed Alert Notification for Autonomous Vehicles
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Solution Overview
Problem
Autonomous-driving vehicles often operate in counterintuitive manners to humans, leading to potential traffic incidents due to differences in movement prediction between autonomous and human-driven vehicles, necessitating effective perception and alert systems to prevent collisions.
Innovation Solution
A system and method in an autonomous-driving vehicle that detects movable objects, determines a target object, and generates directed alert notifications based on perceptibility parameters, including visual, acoustic, and somatosensory levels, to effectively communicate with human drivers and pedestrians, using a combination of image processing, positioning, and locomotive control to anticipate and avoid potential collisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If autonomous-driving vehicles operate autonomously with limited or without human inputs, then automation level is improved, but predictability to human drivers deteriorates leading to potential traffic incidents
Solution Approach 1:
The system performs preliminary actions by detecting movable objects and determining their predicted moving paths in advance. It calculates potential collision risks before they materialize and prepares alert notifications proactively. This allows the autonomous vehicle to communicate its intentions and potential hazards to human drivers ahead of time, improving predictability while maintaining automation.
Solution Approach 2:
The alert notification system acts as an intermediary between the autonomous vehicle's decision-making system and human drivers. It translates the vehicle's autonomous operations and predicted actions into comprehensible alerts that human drivers can understand, bridging the gap between autonomous operation and human predictability expectations.
2Reliability
If the autonomous vehicle generates alert notifications to improve predictability, then safety is improved, but device complexity increases due to multiple detection and notification systems
Solution Approach 1:
The system employs a multi-functional alert notification apparatus that can generate multiple types of alerts (visual, acoustic, haptic) through a single integrated system. This universal apparatus handles various notification needs without requiring separate dedicated systems for each alert type, thereby improving safety while controlling complexity through consolidation.
Solution Approach 2:
The alert notification system provides localized, targeted alerts directed at specific human drivers or pedestrians identified as potential collision risks. Rather than generating universal alerts in all directions, the system concentrates notification resources on relevant targets, improving safety effectiveness while reducing overall system complexity by avoiding unnecessary notification channels.
3Reliability
If the system determines predicted moving paths and potential collision risks for all detected objects, then collision avoidance is improved, but processing time and computational load increase
Solution Approach 1:
The system performs partial analysis by focusing computational resources on determining predicted moving paths and collision risks only for objects that are relevant to potential collisions with the autonomous vehicle. Rather than analyzing all detected objects equally, it selectively processes those within critical zones or exhibiting trajectories that suggest potential conflict, thereby maintaining collision avoidance capability while reducing processing time.
Solution Approach 2:
The detection and analysis system segments the operational environment into different zones or priority levels based on potential collision risk. Objects in high-risk zones receive full predicted path analysis, while objects in lower-risk zones receive simplified monitoring. This segmentation allows the system to maintain high collision avoidance capability for critical threats while reducing overall computational load and processing time.
Data Source
AI summary
A system included and a computer-implemented method performed in an autonomous-driving vehicle are described. The system performs: detecting one or more movable objects; determining a target movable object from the one or more detected objects; determining a manner of generating a directed alert notification selectively toward the target movable object; and causing a directed alert notification of the determined manner to be generated toward the target movable object.