Road Abnormality Detection via Multi-Vehicle Behavior Analysis
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Solution Overview
Problem
Current methods for detecting road abnormalities, such as potholes, face challenges in accuracy due to reliance on vehicle behaviors that may not consistently indicate the presence of abnormalities, leading to potential errors and increased computational load when analyzing multiple vehicles.
Innovation Solution
An information processing apparatus and method that determine road abnormalities by analyzing the behaviors of multiple vehicles within a predetermined range, using data from sensors like wheel speed and steering angle to identify patterns indicative of potholes, such as S-shaped travel trajectories and changes in wheel acceleration, to improve detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If road abnormalities are detected based on individual vehicle sensor data (wheel speed, steering angle), then detection can be performed in real-time, but detection accuracy is reduced due to inconsistent vehicle behaviors and potential false positives
Solution Approach 1:
The patent combines sensor data from multiple vehicles traveling in the same area to detect road abnormalities. By merging observations from several vehicles, the system overcomes the inconsistency of individual vehicle behaviors and achieves more reliable detection. The server collects wheel speed and steering angle data from multiple vehicles and analyzes them collectively to determine the presence of road abnormalities.
Solution Approach 2:
The patent introduces a server as an intermediary that collects, stores, and analyzes sensor data from multiple vehicles. This intermediary component enables the system to aggregate data from different sources, perform comprehensive analysis, and make more accurate determinations about road abnormalities than any single vehicle could achieve alone.
2Reliability
If multiple vehicles' sensor data are analyzed to improve detection accuracy, then reliability increases, but computational load and system complexity increase
Solution Approach 1:
The patent divides the detection system into separate functional components: vehicles equipped with sensors, a server for data collection and analysis, and a notification system. This segmentation allows each component to perform its specific function efficiently, reducing the complexity burden on individual elements while maintaining overall system reliability through coordinated operation.
3Measurement precision
If comprehensive sensor data from multiple vehicles are processed, then detection accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The patent implements preliminary action by having vehicles continuously transmit their sensor data to the server, which stores the data in advance. This preliminary data collection and storage eliminates the need for real-time processing when an abnormality is detected, as the server already has the necessary historical data ready for analysis, thus reducing processing time while maintaining accuracy.
Data Source
AI summary
A controller is provided which is configured to determine, in response to obtaining first information about a possibility of an abnormality in a road, the abnormality in the road based on behaviors of a plurality of vehicles in a predetermined range including a position corresponding to the first information.