Vehicular Micro Cloud Mapping for Incomplete Roadway Anomaly Views
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Solution Overview
Problem
Connected vehicles rely on onboard sensors to detect anomalies, but their maps are inadequate due to limited perspectives, and traditional Vehicle-to-Everything (V2X) communication faces issues like latency and underdeveloped infrastructure, making it unsuitable for generating accurate anomaly maps.
Innovation Solution
An anomaly client and detector cooperate to form a vehicular micro cloud, allowing vehicles to share anomaly maps and sensor data, creating a collaborative environment for improved anomaly detection and mapping, including stationary or mobile micro clouds that can follow moving anomalies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional V2X communication is used to share anomaly maps between vehicles, then multiple perspectives can be combined to improve map accuracy, but latency and communication overhead increase
Solution Approach 1:
The system segments the anomaly mapping task by having each vehicle independently detect and map anomalies from its own perspective using onboard sensors, then combines these segmented local maps into a comprehensive anomaly map through the vehicular micro cloud, reducing the need for continuous communication while maintaining accuracy
Solution Approach 2:
The system merges multiple local anomaly maps from different vehicles into a single comprehensive anomaly map by combining perspectives from multiple sources within the vehicular micro cloud, improving map accuracy without requiring real-time continuous communication between all vehicles
2Loss of information
If traditional V2X communication infrastructure is used, then vehicles can exchange anomaly information, but the underdeveloped infrastructure limits effectiveness
Solution Approach 1:
The system implements self-service by enabling vehicles to autonomously detect, process, and share anomaly information through their onboard sensors and processors within the vehicular micro cloud, reducing dependency on external V2X infrastructure while maintaining effective information sharing
Solution Approach 2:
The vehicular micro cloud serves multiple functions including anomaly detection, map generation, information sharing, and collaborative processing using only onboard vehicle resources, making the system universally applicable regardless of V2X infrastructure availability
3Device complexity
If a single vehicle creates anomaly maps using only its onboard sensors, then the system is simple to implement, but the maps are incomplete due to limited perspective
Solution Approach 1:
The system merges anomaly maps from multiple vehicles within the vehicular micro cloud, combining their different perspectives and sensor data to create a more complete and accurate comprehensive anomaly map while maintaining relative system simplicity
Solution Approach 2:
The system adds another dimension to anomaly mapping by incorporating spatial perspectives from multiple vehicles positioned at different locations, transforming single-vehicle 2D maps into multi-perspective 3D spatial understanding of the environment
Data Source
AI summary
The disclosure includes embodiments for generating improved anomaly maps. In some embodiments, a method for a connected vehicle includes detecting an occurrence of an anomaly in a roadway environment based on sensor data describing the roadway environment. The method includes creating, by the connected vehicle, an anomaly map that describes the anomaly. The method includes modifying an operation of a communication unit of the connected vehicle to receive one or more other anomaly maps describing the anomaly from one or more cooperation endpoints in the roadway environment. The method includes generating an updated anomaly map based on the anomaly map created by the connected vehicle and the one or more other anomaly maps created by the one or more cooperation endpoints so that an accuracy of the updated anomaly map is improved.