Collaborative Vehicle Warning Generation for Occluded Collision Detection
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Solution Overview
Problem
Existing automated vehicle collision avoidance systems rely on first-person sensor data and are limited by occlusions and sensor sight angles, failing to effectively detect potential collisions between vehicles or objects due to their reliance on individual vehicle observations without collaborative analysis.
Innovation Solution
Implementing a collaborative approach where observer vehicles or modules, not involved in the potential collision, analyze and share data on vehicle and object positions and movements to predict collisions, enabling distributed computational analysis and warning messages to affected vehicles, even when occlusions or limited sensor views are present.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If first-person sensor data from individual vehicles is used for collision detection, then the system is simple to implement, but collision detection accuracy deteriorates due to occlusions and limited sensor sight angles
Solution Approach 1:
The patent combines sensor data from multiple vehicles and external observers into a unified collision detection system. By merging first-person observations from involved vehicles with third-person observations from observer vehicles and infrastructure, the system overcomes individual sensor limitations and achieves comprehensive collision detection coverage.
Solution Approach 2:
The patent introduces observer vehicles and infrastructure as intermediary entities that collect and share observational data about potential collisions. These intermediaries provide independent verification and additional perspectives that弥补 the limitations of direct sensor observations from involved vehicles.
2Use of energy by moving object
If individual vehicle observations are used without collaborative analysis, then the system requires less computational resources, but the ability to detect potential collisions deteriorates
Solution Approach 1:
The patent segments the collision detection function across multiple independent entities including involved vehicles, observer vehicles, and infrastructure. Each entity performs localized analysis of its sensor data and shares results through communication networks, distributing computational workload while improving overall detection reliability.
Solution Approach 2:
The patent implements feedback mechanisms where observational data and collision assessments are continuously shared between vehicles and infrastructure through communication networks. This feedback loop enables real-time collaboration and verification, enhancing collision detection reliability through multiple independent assessments.
Data Source
AI summary
Methods and apparatus to generate vehicle warnings are disclosed. An example apparatus includes a sensor to detect a vehicle, where the sensor is associated with an observer of the vehicle, an object tracker to determine a motion of the vehicle, an accident estimator to calculate a likelihood of a collision of the vehicle based on the determined motion, and a transceiver to transmit a message to the vehicle upon the likelihood of the collision exceeding a threshold, where the message includes information pertaining to the collision.