• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.3
• /
• pp.1-14
• /
• 2017

Recently, the automobile industry is rapidly changing due to autonomous vehicles based on advanced ICT technology. As a result, studies related to autonomous vehicles have also been actively conducted. However, most studies are focusing on the autonomous driving technology so that the prediction of changes in road traffic safety and associated legal system due to the introduction of autonomous vehicles are lacking. The purpose of this study is to suggest improvement methods and priorities of road traffic safety projects according to the introduction of autonomous vehicles. As a result of the AHP analysis using the results of the questionnaire surveyed for autonomous driving car experts, it was analyzed that revision of the traffic safety inspection law and development of education system for autonomous driving motor drivers and operators should be given top priority.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.20 no.6
• /
• pp.264-279
• /
• 2021

Most automated vehicle evaluation scenarios are developed based on the typical driving situations that automated vehicles will face. However, various situations occur during actual driving, and sometimes complex judgments are required. This study is to define a situation that requires complex judgment for safer driving of an automated vehicle as a dilemma situation, and to suggest a driving strategy necessary to secure driving safety in each situation. To this end, we defined dilemma situations based on the automated vehicle ethics guidelines, the criteria for recognition of error rate in automobile accidents, and suggestions from the automated vehicle developers. In addition, in the defined dilemma situations, the factors affecting movement for establishing driving strategies were explored, and the priorities of factors affecting driving according to the Road Traffic Act and driving strategies were derived accordingly.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.6
• /
• pp.36-56
• /
• 2022

Traffic accidents occur in Korea are calculated with the 「Automobile Accident Negligence Ratio Certification Standard」 prepared by the 'General Insurance Association of Korea' and the insurance company's agreement or judgment is made. However, disputes are frequently occurring in calculating the negligence ratio. Therefore, it is thought that a more effective response would be possible if accident type according to the standard could be quickly identified using traffic accident information prepared by police. Therefore, this study aims to develop a model that learns the accident information prepared by the police and classifies it to match the accident type in the standard. In particular, through data mining, keywords necessary to classify the accident types of the standard were extracted from the accident data of the police. Then, models were developed to derive the types of accidents by learning the extracted keywords through decision trees and random forest models.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.23 no.4
• /
• pp.67-76
• /
• 2024

This study conducted an operational evaluation of an emergency vehicle preemption system that can be operated as a wide-area unit beyond the boundaries of local governments. Analyzed the speed reduction rate of emergency vehicle dispatch data and traffic speed data to analyze the speed reduction rate of emergency vehicles operating in a wide area and region. In Goyang City, local dispatches were reduced by 50.8% and regional dispatches by 55.8%, while in Paju City, local dispatches were reduced by 55.1% and regional dispatches by 62.5%. The wide-area emergency vehicle preemption system proved to be effective when emergency vehicles were dispatched outside of local boundaries, such as confirming that there were many dispatches from Paju-si to Goyang-si when there were no large hospitals nearby. This study aims to help spread the wide-area emergency vehicle preemption system. Translated with DeepL.com (free version)

• International Journal of Computer Science & Network Security
• /
• v.21 no.3
• /
• pp.145-152
• /
• 2021

In the Recent times, various technological enhancements in the field of artificial intelligence and big data has been noticed. This advancement coupled with the evolution of the 5G communication and Internet of Things technologies, has helped in the development in the domain of smart mine construction. The development of unmanned vehicles with enhanced and smart scheduling system for open-pit mine transportation is one such much needed application. Traditional open-pit mining systems, which often cause vehicle delays and congestion, are controlled by human authority. The number of sensors has been used to operate unmanned cars in an open-pit mine. The sensors haves been used to prove the real-time data in large quantity. Using this data, we analyses and create an improved transportation scheduling mechanism so as to optimize the paths for the vehicles. Considering the huge amount the data received and aggregated through various sensors or sources like, the GPS data of the unmanned vehicle, the equipment information, an intelligent, and multi-target, open-pit mine unmanned vehicle schedules model was developed. It is also matched with real open-pit mine product to reduce transport costs, overall unmanned vehicle wait times and fluctuation in ore quality. To resolve the issue of scheduling the transportation, we prefer to use algorithms based on artificial intelligence. To improve the convergence, distribution, and diversity of the classic, rapidly non-dominated genetic trial algorithm, to solve limited high-dimensional multi-objective problems, we propose a decomposition-based restricted genetic algorithm for dominance (DBCDP-NSGA-II).

• Journal of Intelligence and Information Systems
• /
• v.16 no.1
• /
• pp.57-69
• /
• 2010

The ubiquitous transportation system environments make it possible to collect each vehicle's position and velocity data and to perform more sophisticated traffic flow management at individual vehicle or platoon level through V2V and V2I communication. It is necessary to develop a new data processing methodology to take advantage of the ubiquitous transportation system environments. This paper proposed to build 3-dimension data profiles to maintain the detailed traffic flow information contained in the individual vehicles' data and at the same time to keep the profiles from the meaningless fluctuations. Also methods to build the platoon profile and the shock wave speed profile are proposed, which have not been possible under ITS(Intelligent Transportation System) environments.

• 한국ITS학회:학술대회논문집
• /
• 2010.05a
• /
• pp.145-147
• /
• 2010

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.23 no.1
• /
• pp.42-60
• /
• 2024

This study analyzed the characteristics of mixed traffic flows with autonomous vehicles on highway weaving sections and assessed the safety of vehicle-following pairs based on surrogate safety indicators. The intelligent driver model (IDM) was utilized to emulate the driving behavior of autonomous vehicles, and the weaving sections were divided into lengths of 300 and 600 meters for analysis within a micro-traffic simulation (VISSIM). Although significant differences were found in the average speed, density, and headway between the two sections through t-test results, no significant differences were observed when comparing the number of conflicts per indicator and the vehicle-following pair. Four safety indicators were selected for the mixed traffic evaluation based on their ability to represent risk levels similar to those perceived by drivers. The safety analysis, based on the selected four indicators, determined that autonomous vehicles following other autonomous vehicles were the safest pairing. Future research should focus on integrating these indicators into a single comprehensive index for analysis.

• 한국ITS학회:학술대회논문집
• /
• v.2006 no.10
• /
• pp.260-264
• /
• 2006

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.10a
• /
• pp.488-491
• /
• 2014

Based on a complete understanding research in Information and Communication Technologies (ICT), the Intelligent Transport Systems rapidly build up innovative applications to ensure real time attainment as well remote management of driven information, provide a huge range of services and involve many actors in automotive ecosystem. In this paper, we present an intelligent cloud computing for handling data received from traffic sensing technologies. Transportations technologies applied in ITS have played a great role in collecting data from devices deployed in vehicles and highway infrastructures utilizing broadband wireless technologies to the Cloud. In order to facilitate the interested in automotive industry to use data collected and afford services to the car's owner, a scalable acquisition, access to computing resources and offered services are the primary goal of the proposed cloud computing.