Connected Vehicle Sensor Data Fusion for Enhanced Environmental Awareness
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Solution Overview
Problem
Conventional automotive technologies rely on sensors installed on vehicles to enhance driver views, but they are limited to visible information and cannot provide timely data on obstacles or conditions not within their range or capabilities, such as low visibility conditions or dynamic updates.
Innovation Solution
The system facilitates the sharing of sensor data between connected vehicles, using networked devices to augment and enhance the view data by combining information from multiple sources, including sensors on other vehicles and infrastructure, to provide a more comprehensive and timely view of the environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If sensors are installed on a single vehicle to enhance driver view, then the system structure remains simple, but the information coverage is limited to what the local sensors can detect
Solution Approach 1:
The patent combines sensor data from multiple vehicles and infrastructure sources into a unified enhanced view system. Sensors on other vehicles capture environmental data that is then merged with local sensor data through network communication, expanding information coverage beyond what a single vehicle's sensors can detect.
Solution Approach 2:
The system enables sensor data to serve multiple purposes: local vehicles use their own sensors for immediate detection, while the same data is shared network-wide to provide enhanced views for other vehicles. This multi-functional use of sensor data maximizes information utility without proportionally increasing system complexity.
2Loss of time
If sensors are installed on a single vehicle, then the system complexity remains low, but the timeliness of obstacle detection is insufficient when obstacles are out of range
Solution Approach 1:
Sensors on other vehicles detect obstacles and environmental conditions in advance before the local vehicle reaches those areas. This preliminary detection allows the system to prepare and transmit warning information to the local vehicle before the driver would otherwise encounter the obstacle, reducing detection time.
Solution Approach 2:
The network infrastructure acts as an intermediary that collects sensor data from multiple vehicles and relays relevant information to the local vehicle. This mediator enables timely obstacle detection by bridging the gap between distant sensors and the local driver without requiring direct line-of-sight detection.
3Loss of information
If only local sensor data is used, then the data processing is simple, but the comprehensiveness of environmental information is insufficient
Solution Approach 1:
The enhanced view system segments environmental monitoring into multiple independent sensor sources distributed across different vehicles and infrastructure points. Each sensor captures a specific portion of the environment, and the system integrates these segmented data sources to create a comprehensive environmental picture.
Solution Approach 2:
The system merges sensor data from multiple vehicles and infrastructure sources with local sensor data. This combination integrates diverse environmental information from different spatial locations and detection capabilities, creating a comprehensive view that exceeds what any single sensor source could provide.
Data Source
AI summary
Network connectivity is used to share relevant visual and other sensory information between vehicles, as well as delivering relevant information provided by network services to create an enhanced view of the vehicle's surroundings. The enhanced view is presented to the occupants of the vehicle to provide an improved driving experience and/or enable the occupants to take proper action (e.g., avoid obstacles, identify traffic delays, etc.). In one example, the enhanced view comprises information that is not visible to the naked eye and/or cannot be currently sensed by the vehicle's sensors (e.g., due to a partial or blocked view, low visibility conditions, hardware capabilities of the vehicle's sensors, position of the vehicle's sensors, etc.).