KR-20260062286-A - SYSTEM AND METHOD FOR JUDGING THE LEVEL OF AUTONOMOUS TRAM OPERATION ACCORDING TO CLIMATE CONDITIONS

KR20260062286AKR 20260062286 AKR20260062286 AKR 20260062286AKR-20260062286-A

Abstract

The present invention relates to a system and method for determining the level of operation of an autonomous tram considering climate and environmental conditions. The autonomous driving tram operation level determination system considering climate environment conditions according to the present invention includes a driving environment recognition unit that transmits driving environment information including a climate environment, and an autonomous driving operation level determination unit that monitors the driving environment information and determines the autonomous driving operation level.

Inventors

전희균
황현철
곽재호
이수형
박성원
최경준
이상엽
이현석
백지현

Assignees

한국철도기술연구원

Dates

Publication Date: 20260507
Application Date: 20241029

Claims (19)

A driving environment recognition unit that transmits driving environment information including climate environment; and Autonomous driving level determination unit that monitors the above driving environment information and determines the autonomous driving level A system for determining the level of autonomous tram operation considering climate and environmental conditions including
In paragraph 1, The above driving environment recognition unit includes a weather estimation module that estimates the weather using images acquired through a camera, a braking distance estimation module that estimates the braking distance of a vehicle using GPS data, and a visibility estimation module that estimates the visibility distance using point cloud data from a LiDAR. Autonomous tram operation level determination system considering climate and environmental conditions.
In paragraph 2, The above weather estimation module inputs image information acquired through a camera placed on the tram into a pre-trained weather classification model to derive probability values of weather conditions. Autonomous tram operation level determination system considering climate and environmental conditions.
In paragraph 2, The above braking distance estimation module calculates speed values using changes in GPS coordinate values and estimates braking distance using driving equations. Autonomous tram operation level determination system considering climate and environmental conditions.
In paragraph 2, The above visibility estimation module performs preprocessing on the LiDAR point cloud, analyzes the distance distribution of each point cloud from the origin coordinates, and estimates the visibility. Autonomous tram operation level determination system considering climate and environmental conditions.
In paragraph 2, The above-mentioned autonomous driving level determining unit determines the autonomous driving level for autonomous driving possible, conservative driving, and autonomous driving impossible, and provides a driving guide according to the determined driving level. Autonomous tram operation level determination system considering climate and environmental conditions.
In paragraph 6, The above autonomous driving level determining unit determines the driving level as autonomous driving impossible when the visibility distance is smaller than the braking distance. Autonomous tram operation level determination system considering climate and environmental conditions.
In paragraph 6, The above-mentioned autonomous driving level determining unit determines whether autonomous driving is possible based on the weather judgment result when the braking distance is greater than the margin braking distance, or determines whether autonomous driving is possible or conservative operation by verifying reliability. Autonomous tram operation level determination system considering climate and environmental conditions.
In a method for determining the level of autonomous tram operation considering climate and environmental conditions, performed by a system for determining the level of autonomous tram operation considering climate and environmental conditions, (a) a step of perceiving the driving environment; and (b) A step of determining the level of autonomous driving using the perception results of the above driving environment A method for determining the level of autonomous tram operation considering climate and environmental conditions including
In Paragraph 9, The above step (a) recognizes the driving environment based on the day/night determination result, weather estimation result, braking distance estimation result, and visibility estimation result. Method for determining the level of autonomous tram operation considering climate and environmental conditions.
In Paragraph 10, The above step (a) involves inputting images acquired through a camera into a weather classification model and accumulating the result values of the weather classification model a preset number of times to generate the weather estimation result for the current weather condition. Method for determining the level of autonomous tram operation considering climate and environmental conditions.
In Paragraph 9, The above step (a) involves acquiring GPS data, calculating the distance traveled through the time-unit coordinate difference, calculating the current speed by dividing the distance traveled by the time unit, and generating the braking distance estimation result required for the current speed using a braking distance model. Method for determining the level of autonomous tram operation considering climate and environmental conditions.
In Paragraph 9, The above step (a) involves acquiring LiDAR data, performing downsampling into a voxel grid, calculating the distance between the origin and the point cloud, and generating the above visibility distance estimation result using values corresponding to preset categories. Method for determining the level of autonomous tram operation considering climate and environmental conditions.
In Paragraph 9, The above step (b) determines the level of autonomous driving operation for autonomous driving possible, conservative operation, and autonomous driving impossible, and provides an operation guide according to the determined level of operation. Method for determining the level of autonomous tram operation considering climate and environmental conditions.
In Paragraph 14, The above step (b) determines the level of operation as impossible to autonomous driving when driving at night or when the visibility distance is smaller than the braking distance. Method for determining the level of autonomous tram operation considering climate and environmental conditions.
In Paragraph 14, Step (b) above determines whether autonomous driving is possible based on the weather judgment result when the braking distance is greater than the margin braking distance, or determines whether autonomous driving is possible or conservative operation by verifying reliability. Method for determining the level of autonomous tram operation considering climate and environmental conditions.
An input interface device for receiving input information including receiving camera data, GPS data, and LiDAR data; A memory storing a program that determines the level of autonomous driving using the above input information; and It includes a processor that executes the above program, and The above processor provides a driving guide based on the result of determining the above driving level. Autonomous tram operation level determination system considering climate and environmental conditions.
In Paragraph 17, The above processor generates a weather estimation result using the camera data, generates a braking distance estimation result using the GPS data, and generates a visibility estimation result using the LiDAR data. Autonomous tram operation level determination system considering climate and environmental conditions.
In Paragraph 17, The above processor determines the level of operation of the above autonomous driving regarding autonomous driving possible, conservative operation, and autonomous driving impossible. Autonomous tram operation level determination system considering climate and environmental conditions.

Description

System and Method for Judging the Level of Autonomous Tram Operation According to Climate Conditions The present invention relates to a system and method for determining the level of autonomous tram operation considering climate and environmental conditions. Autonomous driving refers to a system that detects the surrounding environment in real time and operates a vehicle safely without human intervention through the fusion of various sensors. In autonomous driving, adverse weather conditions affect sensor data, degrading object detection performance and serving as one of the major obstacles hindering the operation. It has been reported that over 30,000 vehicle collision accidents occur annually due to rain, sleet, and icy road conditions, and the risk of accidents during rainy weather is estimated to be 70% higher than usual. According to the prior art (Korean Published Patent Application No. 10-2022-0062183), a system has been proposed to calculate a target driving speed and control the driving of a vehicle based on at least one of weather information, road surface information, or the minimum detection distance detectable by a sensor, which are included in the external environment information. However, this has limitations in that it cannot respond to various variables regarding climatic conditions (snow, fog, etc.) and has a problem in that it cannot detect obstacles when forward visibility is not secured due to climatic conditions. FIG. 1 illustrates a system for determining the level of autonomous tram operation considering climate and environmental conditions according to an embodiment of the present invention. FIG. 2 illustrates a dataset related to weather estimation using camera data according to an embodiment of the present invention. FIG. 3 illustrates the braking distance according to the speed of a tram according to an embodiment of the present invention. FIG. 4 illustrates criteria for determining the driving environment and the level of autonomous driving capability according to an embodiment of the present invention. FIG. 5 illustrates a method for determining the level of autonomous tram operation considering climate and environmental conditions according to an embodiment of the present invention. FIG. 6 illustrates a process for determining the level of autonomous tram operation according to climate conditions in accordance with an embodiment of the present invention. FIG. 7 is a block diagram showing a computer system for implementing a method according to an embodiment of the present invention. The aforementioned objectives of the present invention, as well as other objectives, advantages, and features, and the methods for achieving them, will become clear from the embodiments described in detail below together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below but can be implemented in various different forms, and the following embodiments are provided merely to easily inform those skilled in the art of the purpose, structure, and effects of the invention, and the scope of the rights of the present invention is defined by the description in the claims. Meanwhile, the terms used in this specification are for describing the embodiments and are not intended to limit the invention. In this specification, the singular form includes the plural form unless specifically stated otherwise in the text. As used in this specification, "comprises" and/or "comprising" do not exclude the presence or addition of one or more other components, steps, actions, and/or elements to the mentioned components, steps, actions, and/or elements. Autonomous tram operation level determination system considering climate and environmental conditions According to an embodiment of the present invention, weather information, braking distance, and visibility are estimated by utilizing sensors (camera, lidar, GPS) and artificial intelligence applied to an autonomous driving tram, and the feasibility of autonomous driving operation is determined using the estimation results. FIG. 1 illustrates a system for determining the level of autonomous tram operation considering climate and environmental conditions according to an embodiment of the present invention. A system for determining the level of autonomous driving tram operation considering climate environment conditions according to an embodiment of the present invention includes a driving environment recognition unit (100) that transmits driving environment information including a climate environment, and an autonomous driving operation level determination unit (200) that monitors the driving environment information and determines the level of autonomous driving operation. A driving environment recognition unit (100) according to an embodiment of the present invention includes a weather estimation module (110) that estimates the weather using an image acquired through a camera, a braking distance estimation module