Traffic State Prediction Using Communication Vehicle Sensor Data
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Solution Overview
Problem
Existing traffic information processing devices have low prediction accuracy for future traffic states due to reliance on communication from only a subset of vehicles that can transmit data to a server, leaving gaps in congestion information from vehicles without communication apparatuses.
Innovation Solution
A traffic information processing device that includes a communication unit, an information acquisition unit, and a traffic state prediction unit, which utilizes position and speed information from both communicating and non-communicating vehicles, including autonomously traveling vehicles, to predict future traffic changes, and adjusts vehicle allocation to improve data coverage and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traffic information is collected only from vehicles with communication apparatuses, then the system complexity is reduced, but the prediction accuracy of future traffic states deteriorates
Solution Approach 1:
The patent introduces communication vehicles as intermediary elements that collect traffic information from non-communicating vehicles using sensors (cameras, radar) and relay this information to the server. This mediator approach allows the system to incorporate data from all vehicles without requiring each vehicle to have direct communication capabilities, thus maintaining low system complexity while improving prediction accuracy through more comprehensive data collection.
2Measurement precision
If more vehicles are used to transmit traffic information, then the prediction accuracy improves, but the device complexity increases
Solution Approach 1:
The system segments vehicles into two functional groups: communication vehicles equipped with sensors and communication apparatuses that collect and transmit data, and non-communicating vehicles that provide traffic information passively through their physical presence and sensor detections. This segmentation allows comprehensive data collection from all vehicles while concentrating the communication burden on a subset, thereby improving prediction accuracy without proportionally increasing system complexity.
3Ease of operation
If vehicles without communication apparatuses are excluded from data collection, then the ease of operation is improved, but the quantity of available traffic information decreases
Solution Approach 1:
Communication vehicles perform multiple functions: they serve as both regular vehicles in traffic and as mobile data collection stations. By equipping these vehicles with sensors (cameras, radar, LIDAR) in addition to communication apparatuses, the system enables a single vehicle type to gather traffic information from all surrounding vehicles regardless of their communication capabilities, thus maintaining ease of operation while maximizing the quantity of collected traffic information.
Data Source
AI summary
A traffic information processing device includes a communication unit configured to communicate through a communication network with a plurality of communication vehicles configured to detect relative positions and relative speeds of vehicles around a host vehicle with respect to the host vehicle, an information acquisition unit configured to acquire position and speed information of the communication vehicle and position and speed information of vehicles around the communication vehicle from each of the communication vehicles traveling in a specific area through the communication unit, and a traffic state prediction unit configured to predict a future change in a traffic state of a road in the specific area based on the position and speed information from the communication vehicles acquired by the information acquisition unit.