V2V Blind Spot Detection via Composite Sensor Fusion
Solution Overview
Problem
Drivers and driverless vehicles often fail to detect potential dangers behind obstructions, such as unseen vehicles or debris, due to blind spots in their 360-degree view of the surroundings, leading to accidents.
Innovation Solution
A vehicle-to-vehicle (V2V) communication system that shares real-time data streams to create a composite 360-degree view, allowing vehicles to 'see' through obstructions by combining their own direct view with data from other vehicles, thereby identifying and highlighting potential dangers and filling in blind spots.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vehicles rely solely on their own sensors to detect obstacles, then device complexity is reduced, but detection capability deteriorates due to blind spots caused by obstructions
Solution Approach 1:
The patent merges sensor data from multiple vehicles to create a composite environmental model. Each vehicle's sensor data is combined with data from neighboring vehicles to fill blind spots and provide a more complete picture of the environment, thereby improving detection capability without requiring each individual vehicle to have omnidirectional sensors.
Solution Approach 2:
The patent introduces a communication system as an intermediary that facilitates data exchange between vehicles. This mediator enables vehicles to share sensor data and environmental models, allowing each vehicle to infer the presence of obstacles in blind spots through information from other vehicles without direct line-of-sight detection.
2Reliability
If vehicles share real-time data streams to fill blind spots, then detection capability improves, but data processing complexity increases
Solution Approach 1:
The patent segments the environmental data into different components (direct sensor data, inferred obstacle data, blind spot information) and processes them separately. This segmentation allows the system to manage complex data processing by handling different data types through specialized algorithms rather than processing all data uniformly.
Solution Approach 2:
The patent performs preliminary processing of sensor data at each vehicle before sharing, creating pre-processed environmental models that are then combined. This preliminary action reduces the overall processing complexity by preparing data in advance rather than requiring real-time processing of all raw sensor data from all vehicles.
3Reliability
If vehicles use V2V communication to share environment data, then safety improves by detecting hidden obstacles, but communication system complexity increases
Solution Approach 1:
The patent implements a universal communication protocol that handles multiple functions (data sharing, blind spot identification, obstacle inference) through a single V2V communication framework. This multi-functionality reduces communication system complexity by consolidating multiple specialized systems into one unified communication infrastructure.
Data Source
AI summary
In a vehicle communication system of vehicles, vehicles share environment data such as their location data and 360 degree view of the world with other vehicles using direct vehicle-to-vehicle (V2V) real-time data streams. A displayable map of potentially dangerous obstructions on the surrounding roadway is formed using in vehicle environment sensors allowing a driver or the controls of a driverless vehicle to be warned of the danger. A map of blind spots is built up to speed up the processing of incoming data in order to create a more complete picture of surrounding vehicles. Shared data is used to position each vehicle relative to the target vehicle. By sharing obstruction maps between vehicles, a more complete picture of the roadway can be displayed—and one vehicle can in effect “see” through another vehicle or an obstruction.