Dynamic Map Server for Vehicular Sensor Data Optimization
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Solution Overview
Problem
Existing communication methods for dynamic maps in vehicular environments often lead to network bandwidth shortages due to inefficient data collection and distribution, particularly in scenarios with multiple vehicles requesting and sharing sensor information.
Innovation Solution
A communication method and server system that selectively gather and distribute data by identifying and utilizing specific sensors with overlapping observation ranges, prioritizing data size and type, to efficiently fill unobserved regions in dynamic maps, thereby optimizing network resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all vehicles request images of necessary ranges from other vehicles, then comprehensive dynamic map coverage is achieved, but overall communication volume increases and network band becomes insufficient
Solution Approach 1:
The patent extracts only the essential and non-redundant sensor data needed to fill unobserved regions in dynamic maps. Instead of transmitting complete sensor images or all available data, the system identifies specific unobserved regions and requests only the minimal necessary data from other vehicles to cover these regions, thereby reducing overall communication volume while maintaining comprehensive map coverage.
Solution Approach 2:
The patent applies partial action by requesting data only for specific unobserved regions rather than obtaining complete sensor data from all vehicles. The system determines the minimum necessary data quantity required to fill gaps in dynamic map coverage, avoiding excessive data transmission while ensuring sufficient information is gathered for comprehensive situational awareness.
2Loss of information
If sensor information is distributed to vehicles using roadside units, then dynamic map data availability is improved, but network band is wasted and becomes insufficient
Solution Approach 1:
The patent performs preliminary actions by having vehicles pre-share their sensor information attributes (such as sensor types, observation ranges, and data characteristics) with the server. This allows the server to pre-calculate which vehicles possess data that can fill unobserved regions before actual dynamic map generation occurs, enabling efficient targeted data requests rather than broad distribution through roadside units, thus optimizing network band utilization.
Solution Approach 2:
The patent introduces a server as an intermediary between vehicles and roadside units. The server acts as a intelligent mediator that receives sensor information attributes from vehicles, determines unobserved regions in dynamic maps, and selectively requests specific data from appropriate vehicles. This intermediary architecture replaces inefficient broad distribution through roadside units with targeted point-to-point communication, reducing network waste while improving information availability.
3Measurement precision
If comprehensive sensor data is collected from multiple vehicles, then dynamic map accuracy is improved, but data redundancy increases and network efficiency decreases
Solution Approach 1:
The patent applies local quality by treating different spatial regions of the dynamic map differently. Instead of uniformly collecting data from all vehicles across all regions, the system identifies specific unobserved regions and selectively requests data only from vehicles whose sensor observation ranges can cover those particular regions. This localized approach ensures high map accuracy in critical unobserved areas while avoiding redundant data collection in already well-observed regions, thereby improving network efficiency.
Data Source
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AI summary
A method used in a server includes configurating a dynamic map by superimposing time-changing information on a road onto a static map based on first data indicative of surrounding information acquired by a first sensor mounted in a roadside unit; computing a first region that is incapable of being observed by the first sensor; receiving a plurality of attribute information items related to respective second sensors mounted in respective vehicles running on the road from the vehicles; selecting a specific second sensor from among the second sensors based on the attribute information items and the first region; receiving specific second data acquired by the specific second sensor among a plurality of pieces of second data acquired by the second sensors; reconfigurating the dynamic map by filling the first region by using the specific second data; and distributing the reconfigurated dynamic map to at least one of the vehicles.