Infrastructure Sensor Context Learning for Vehicle Awareness
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Solution Overview
Problem
Vehicles face difficulties in developing a comprehensive contextual awareness of roadway segments due to limited sensor perspectives and computational resources, especially when approaching intersections or merging onto roads, as they acquire data quickly while moving.
Innovation Solution
Infrastructure-based devices with stationary sensors positioned along roadway segments gather and process data over time, learning static and dynamic aspects to provide a comprehensive understanding of the environment, which is then communicated to approaching vehicles, reducing the computational burden and enhancing situational awareness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If vehicle sensors acquire data while moving through the roadway segment, then the vehicle can maintain its speed and mobility, but the sensor perspective is limited and the acquisition time is constrained, reducing measurement precision and completeness of contextual awareness
Solution Approach 1:
The patent introduces an infrastructure device as an intermediary between the roadway environment and the vehicle. This stationary device acts as a mediator that collects comprehensive sensor data from multiple perspectives (cameras, LIDAR, microphones) and processes it into contextual information, which is then provided to the moving vehicle. This resolves the contradiction by allowing the vehicle to move at normal speed while still obtaining high-precision contextual awareness through the intermediary's processed data.
2Productivity
If the vehicle processes sensor data in real-time while moving, then the system can respond quickly to changing conditions, but the limited computational time and resources reduce the accuracy and comprehensiveness of the contextual assessment
Solution Approach 1:
The patent extracts the complex data processing function from the moving vehicle and relocates it to a stationary infrastructure device. The vehicle's onboard computer only needs to receive and use the pre-processed contextual information, while the heavy computational burden of analyzing multi-sensor data is performed by the infrastructure device with unlimited processing time and resources. This resolves the contradiction between processing speed and accuracy.
3Adaptability or versatility
If the vehicle uses onboard sensors and computing resources to develop contextual awareness, then the system maintains independence and autonomy, but the limited perspective and computational resources constrain the comprehensiveness of the environmental understanding
Solution Approach 1:
The patent merges the sensing capabilities of the infrastructure device with the vehicle's onboard sensors. The infrastructure device provides supplementary contextual information that complements the vehicle's own sensor data, creating a more complete environmental understanding. The vehicle maintains its independence by still using its own sensors and making final decisions, while gaining enhanced awareness from the combined information source.
Data Source
AI summary
System, methods, and other embodiments described herein relate to providing contextual awareness about a roadway segment from an infrastructure device. In one embodiment, a method includes, in response to receiving a context request from a nearby vehicle, acquiring sensor data from at least one infrastructure sensor associated with the roadway segment. The method includes analyzing the sensor data to produce a roadway context by executing a learning module over the sensor data. The roadway context is a characterization of a current state of the roadway segment. The method includes communicating the roadway context to the nearby vehicle to improve a situational awareness of the nearby vehicle about the roadway segment.