Vehicle Movement Filtering for Low-Latency Collision Prediction
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Solution Overview
Problem
Conventional Mobile Edge Computing (MEC) systems lack limitations on the positioning of collision prediction vehicles, leading to increased server load as they target all network-connected vehicles, including those unlikely to be subject to processing.
Innovation Solution
A management device that acquires and provides movement information of vehicles within a predetermined range, using a controller to limit processing targets and enhance efficiency by focusing on vehicles within a specific geographical area, such as cells or tracking areas, through 5G networks, thereby reducing latency and optimizing server load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the server processes all network-connected vehicles without positioning limitations, then comprehensive vehicle monitoring is achieved, but server load increases
Solution Approach 1:
The patent applies local quality by implementing positioning-based filtering that differentiates between vehicles within the target area and those outside. The server selectively processes movement information only for vehicles located within the predetermined area, applying different treatment qualities to different spatial locations. This resolves the contradiction by maintaining comprehensive monitoring capability while reducing processing load through location-based prioritization.
2Adaptability or versatility
If the server targets all vehicles connected to the network, then complete coverage is achieved, but processing efficiency decreases
Solution Approach 1:
The patent applies segmentation by dividing the vehicle population into two distinct segments: vehicles within the predetermined area and vehicles outside the area. The server processes movement information selectively for the first segment while filtering out the second segment. This segmentation maintains the ability to provide complete coverage when needed while significantly improving processing efficiency by focusing computational resources on the relevant subset of vehicles.
3Measurement precision
If movement information is acquired for all vehicles, then accurate collision prediction is possible, but information processing time increases
Solution Approach 1:
The patent applies local quality by implementing area-based filtering that concentrates processing resources on vehicles within the predetermined area. This spatial differentiation maintains collision prediction accuracy for relevant vehicles while reducing overall processing time by excluding vehicles outside the area of interest. The local quality principle ensures that processing intensity is matched to the spatial relevance of each vehicle.
Data Source
AI summary
In the management apparatus, the controller acquires, in response to a request from an information processing apparatus connected to the network, movement information related to the movement of a plurality of vehicles in which any of the plurality of user devices included in a predetermined range exists in the vehicle. Further, the controller provides the acquired movement information to the information processing apparatus.