Autonomous Vehicle Perspective Update via Environmental Profile Generation
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Solution Overview
Problem
Autonomous vehicles face challenges in maintaining accurate object tracking and navigation due to limited network infrastructure for data transmission and high processing requirements for raw sensor data, leading to potential collisions and safety issues when they lose track of objects or encounter rapidly changing environmental conditions.
Innovation Solution
The implementation of a framework that includes a profile generator to create a smaller, more manageable profile of the environment, a data analyzer to update this profile based on differences and trigger events, and a vehicle control system to update the vehicle's perspective and path plan using the updated profile, allowing for efficient data transmission and reduced processing demands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If autonomous vehicles transmit raw sensor data through network infrastructure, then comprehensive environmental data is available, but network bandwidth is insufficient and transmission efficiency deteriorates
Solution Approach 1:
The patent extracts only the essential and changing environmental features from complete sensor data to create condensed profiles. The profile generator identifies and extracts relevant environmental elements (objects, road conditions, weather changes) that differ from previous states, transmitting only these extracted differences rather than complete raw data sets, thereby reducing network bandwidth requirements while maintaining data completeness for safety-critical information
Solution Approach 2:
The environmental data is segmented into discrete profile elements representing specific environmental features (objects, road conditions, weather). Each profile segment can be independently transmitted and processed, allowing selective transmission of only those segments that have changed or are relevant to current navigation decisions, improving transmission efficiency without losing critical information
2Measurement precision
If autonomous vehicles process raw sensor data onboard, then accurate environmental perception is achieved, but computational requirements and processing time increase
Solution Approach 1:
The system performs preliminary processing by generating environmental profiles that pre-identify and categorize relevant environmental features before transmission. This preliminary action of structuring data into meaningful profiles reduces the computational burden on receiving vehicles, as the data arrives in a processed, organized format rather than requiring complete raw sensor processing
Solution Approach 2:
Instead of transmitting and processing complete raw sensor data sets, the system creates simplified copies in the form of environmental profiles that capture the essential characteristics of the environment. These profile copies contain extracted features and state information sufficient for navigation decisions, reducing computational intensity while maintaining perception accuracy
3Reliability
If autonomous vehicles maintain continuous object tracking, then collision avoidance is improved, but system reliability decreases when objects are lost or environmental conditions change rapidly
Solution Approach 1:
The system implements feedback mechanisms where environmental profiles are continuously updated and compared against previous states. When objects are lost or environmental conditions change rapidly, the feedback loop triggers requests for additional sensor data from other vehicles or infrastructure, allowing the system to recover from tracking failures and maintain reliability through collaborative verification
Solution Approach 2:
The system prepares for potential tracking failures by maintaining profile-based environmental models that can serve as backup information sources. When continuous tracking of a specific object fails, the pre-established environmental profiles provide preliminary anti-action by offering alternative data about the environment that can prevent collision risks while tracking is restored
Data Source
AI summary
Methods, apparatus, systems and articles of manufacture are disclosed that provide an apparatus to analyze vehicle perspectives, the apparatus comprising a profile generator to generate a first profile of an environment based on a profile template and first data generated by a first vehicle; a data analyzer to: determine a difference between the first profile and a second profile obtained from a first one of one or more nodes in the environment; and in response to a trigger event, update the first profile based on the difference; and a vehicle control system to: in response to the trigger event, update a first perspective of the environment based on one or more of second data from the first one of the one or more nodes or the updated first profile; update a path plan for the first vehicle based on the updated first perspective; and execute the updated path plan.