KR-20260066907-A - ITS big data collection and analysis system for autonomous driving

Abstract

This document describes the development of a big data collection and analysis program for establishing optimal data, which is the most critical element in introducing Intelligent Transportation Systems (ITS). Specifically, it describes the development of a program that extracts optimal data tailored to five major categories and sixteen medium categories of service fields related to ITS. The program is composed of three modules—collection, analysis, and verification—along with modules for feedback application and error and error cause analysis.

Inventors

• 김민성

Assignees

• (주)케이앤에프컴퍼니

Dates

Publication Date

20260512

Application Date

20241105

Claims (1)

1. Module Design for Building an Optimized ITS Database

Description

ITS big data collection and analysis system for autonomous driving This invention is in the field of technology related to traffic control systems as an Intelligent Transport System. As a next-generation transportation system that integrates advanced information and communication technologies such as AI and sensors into existing transportation systems including roads, vehicles, and signal systems, it is utilized for traffic volume-sensitive real-time signal control, traffic flow guidance, parking guidance, and driving guidance systems. Big data analysis data is an essential element in various related devices, technologies, and systems. The technology forming the background of this invention is the field of big data technology. The five major categories—safe driving support, autonomous driving support, intersection passage support, protection of vulnerable road users, and emergency repayment support—can be organized into 16 medium categories, such as vehicle collision prevention support, driving support in hazardous road sections, road surface condition and weather information provision support, driving support in road work sections, regulatory information provision support, merging support, lane change and overtaking support, cooperative vehicle following support, intersection collision accident prevention support, signal information provision support, e.g., Uber Bus (child protection vehicle) operation guidance, school zone/silver zone warning, collision prevention support for vulnerable road users, emergency situation notification support, emergency vehicle right of way support, and disaster/earthquake information provision. After collecting big data, including data collection links from institutions related to the relevant medium classification and specialized institutions, as well as data collection available on the internet, the design is configured to classify and analyze 16 medium classifications, verify and apply data, modify conditions through feedback, and analyze the causes of errors and discrepancies.