• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.317-319
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• 2021

In Korea, an intelligent transportation system(ITS) is established to efficiently operate traffic congestion on roads and is being used for traffic information collection and speed control systems. Currently, designated and dedicated lanes are in place to ensure traffic circulation and traffic safety, and systematic and accurate illegal vehicle crackdown systems with artificial intelligence technology are needed. In this study, we propose a vehicle number recognition model that can improve the efficiency of the traffic of designated vehicles. By applying computer vision technology, we are going to identify three-lane and four-lane multi-lane roads in real time and detect vehicle numbers by car to suggest ways to crack down on vehicles that violate the designated lane system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.236-238
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• 2022

According to the current Road Traffic Act, the 2020 amendment bill is currently in effect as a system that designates vehicle types for each lane for the purpose of securing road use efficiency and traffic safety. When comparing the number of traffic accident fatalities per 10,000 vehicles in Germany and Korea, the number of traffic accident deaths in Germany is significantly lower than in Korea. The representative case of the German autobahn, which did not impose a speed limit, suggests that Korea's speeding laws are not the only answer to reducing the accident rate. The designated lane system, which is observed in accordance with the keep right principle of the Autobahn Expressway, plays a major role in reducing traffic accidents. Based on this fact, we propose a traffic enforcement system to crack down on vehicles violating the designated lane system and improve the compliance rate. We develop a designated lane enforcement system that recognizes vehicle types using Yolo5, a deep learning object recognition model, recognizes license plates and lanes using OpenCV, and stores the extracted data in the server to determine whether or not laws are violated.Accordingly, it is expected that there will be an effect of reducing the traffic accident rate through the improvement of driver's awareness and compliance rate.

• Journal of Korean Society of Transportation
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• v.30 no.3
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• pp.119-127
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• 2012

For traffic safety, it is imperative for motorists to secure their clear view and to maintain a similar speed with others while driving in a lane. Large-sized vehicles at lower speeds, however, are likely to increase the risk of accident when they share a lane with cars. Although to overcome this complication the Korean Road Traffic Act established rules for the safe use of roads, the reality is that the rules are seldom observed strictly. In this light, this study was designed to analyze the severity of truck-involved accidents, thereby providing justification for the need of truck-designated lanes and thus contributing to measuring road safety more precisely. A binomial logistic regression model was applied to analyze the severity of truck-involved accidents. The analysis showed that several variables affect the severity of truck-involved accidents on freeways; i.e., violation against the rule of truck-designated lanes, weather, difference between daytime and nighttime, and parking on road shoulder. Moreover, the strong enforcement will be needed to make motorists observe the rule, because a Wald statistical test showed that the violation against the rule of truck-designated lanes has the largest influence on the severity.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.2
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• pp.85-94
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• 2016

Lane Designation is defined as reasonable road management to ensure the road safety and enhance road efficiency. While the lane designation system was abolished in 1999, it was redefined because of the increasing number of large vehicles in the passing lane, violent on driving and traffic accidents in 2000. The needs of improvement on operating the lane designation has been increasing more in recent due to the low ratio of compliance with the system and difficulties to keep the right lane due to need of turning and demand of widening of designates lane for two-wheeled vehicles and truck. In this study, we presented the improvement plan through the question survey, simulation analysis, safety evaluation. It found a problem that the low-speed vehicle is to use the upper level roadway, difficulties of supervision, the imbalance in the lane use, imbalance traffic and does not match the international standards. This study suggested five different alternatives through the survey. micro simulation has used in order to examine each alternative by management effectiveness and feasibility. It analyzed the traffic speed, efficiency, traffic balance of alternatives. Also, safety evaluation conducted in terms of the range of field-of-view to ensure the easiness of field of view by various configurational difference between the vehicles. By the analysis results of such indicators, This study presents proposals for improvement in operating designated lane that low-speed-big-sized vehicles keep to the right lane, and high-speed-small sized vehicles keep to the left lane.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.469-472
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• 2022

With the recent development of intelligent transportation systems, various technologies applying deep learning technology are being used. To crackdown on illegal vehicles and criminal vehicles driving on the road, a vehicle type classification system capable of accurately determining the type of vehicle is required. This study proposes a vehicle type classification system optimized for mobile traffic control systems using YOLO(You Only Look Once). The system uses a one-stage object detection algorithm YOLOv5 to detect vehicles into six classes: passenger cars, subcompact, compact, and midsize vans, full-size vans, trucks, motorcycles, special vehicles, and construction machinery. About 5,000 pieces of domestic vehicle image data built by the Korea Institute of Science and Technology for the development of artificial intelligence technology were used as learning data. It proposes a lane designation control system that applies a vehicle type classification algorithm capable of recognizing both front and side angles with one camera.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.239-241
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• 2022

Currently, in Korea, a multi-seater lane (HOV) and a designated lane system are being implemented to solve traffic congestion. However, in both systems, it is difficult to crack down on cases of violations without permission, so people are required to be assigned to areas that want to crack down. In this process, manpower and budget are inefficiently consumed. To compensate for these shortcomings, we propose the development of an integrated enforcement system through YOLO, a deep learning object recognition model. If the two systems are implemented and integrated using YOLO, they will have advantages in terms of manpower and budget over existing systems because only data learning and system maintenance are considered. In addition, in the case of violations in which it is difficult for the existing unmanned system to crack down, the effect of increasing the crackdown rate through continuous learning can be expected.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.2
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• pp.36-47
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• 2020

The objective of this study is to analyze the effect of the shoulder-use lane, which is a representative traffic management technique that increases the road capacity. The operation of the shoulder-use lane has been actively used as a countermeasure to improve traffic congestion, because it has the effect of improving traffic flow during rush hour. In Korea, the shoulder-use lanes are available at Gyeongbu, Yeongdong, and on the Seoul Outer Ring expressway, and their use is gradually increasing. Therefore, a comprehensive analysis was conducted to analyze the effects of the shoulder-use lane; including 1) analysis of individual shoulder lanes based on a time space diagram, and 2) analysis of shoulder lanes by road axis. These findings can contribute to the efficient installation and operation of shoulder-use lanes on expressways.