• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.182-194
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• 2017

Most of the drone (Unmanned Aerial Vehicle) research in terms of traffic management involves detecting and tracking roads or vehicles. The purpose of analyzing image footage in the transportation sector is to overcome the limitations of the existing traffic data collection system (vehicle detectors, DSRC, etc.). With regards to this, drones are the good alternatives. However, due to limitation in their maximum flight time, they are appropriate to use as a complementary rather than replacing the existing collection system. Therefore, further research is needed for utilizing drones for transportation analysis purpose. Traffic problems often arise from one particular section or a point that expands to the whole road network and drones can be fully utilized to analyze these particular sections. Based on the study on the uses of traffic survey analysis, this study is conducted by extracting traffic flow parameters from video images(range 800~1000m) of highway unit segments that were taken by drones. In addition, video images were taken at a high altitude with the development of imaging technologies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.101-111
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• 2017

This study propose a method to predict the bus arrival time by considering the signal delay time which is an element which can not be considered in the current bus arrival prediction information generation algorithm. In order to consider the signal delay time, travel time is divided into three components: service time, cruising travel time, and signal delay time. Signal delay time was estimated using intersection arrival time and TOD. The results show that most of the errors that occurred in predicting the arrival time are within about 30 seconds. Some of the estimates have large errors due to the nature of this methodology that uses the estimated value of the intersection arrival time rather than the observation value. It is also difficult to predict the arrival time of the express buses using this method. Future studies such as improving this through real-time location information will greatly improve the accuracy of the methodology.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.79-89
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• 2017

Current intersection with collectors allow entry and exit in the relevant sections just as defined by the pertinent design criteria without considering driving behavior of the vehicles coming in and out of the intersection. This study analyzed the roads in the weaving sections to review driving behavior. As a result, vehicles entering a main line are found to try to change a driving lane at a section 50~55m away from a nose part, while those entering a ramp from a main line try to change it at 35~40m from a nose part. Accordingly vehicles exiting to a connecting road from a main line were found to take prior action to change a lane earlier than those entering a main line. Conflict took place intensively at 35~40m section from the nose part entering a main line. Consequently, such conflict at an weaving section may be controlled by adjusting the length of driving lane making use of a double line (solid and dotted line) that can control changing a lane. Outcome of this study may be used as a basic data for operating and maintaining an weaving section of a intersection of a road and improving traffic safety.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.90-100
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• 2017

The purpose of this study is to detect and label the vehicles using the drone images as a way to overcome the limitation of the existing point and section detection system and vehicle gap estimation on Arterial road. In order to select the appropriate time zone, position, and altitude for the acquisition of the drone image data, the final image data was acquired by shooting under various conditions. The vehicle was detected by applying mixed Gaussian, image binarization and morphology among various image analysis techniques, and the vehicle was labeled by applying Kalman filter. As a result of the labeling rate analysis, it was confirmed that the vehicle labeling rate is 65% by detecting 185 out of 285 vehicles. The gap was calculated by pixel unitization, and the results were verified through comparison and analysis with Daum maps. As a result, the gap error was less than 5m and the mean error was 1.67m with the preceding vehicle and 1.1m with the following vehicle. The gaps estimated in this study can be used as the density of the urban roads and the criteria for judging the service level.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.124-140
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• 2017

There exists a limitation to provide proper advance information for safe maneuvering through guidance and caution signs in freeway mobile work zones, unlike fixed work zones. Although a work-protection vehicle is currently deployed at the rear of the work vehicle, more active countermeasures to prevent crashes are required. The purpose of this study was to propose a method to evaluate the safety in mobile work zones and to present effective countermeasures. Driving simulation experiments were conducted to analyze characteristics of driver's behavior in mobile and fixed work zones. Safety distance index (SDI) based on the comparison of stopping distances of a work-protection vehicle and a following subject vehicle was used to evaluate traffic safety. More dangerous driving behavior was observed in the mobile work zone. Especially, it was identified that the lane-change of vehicles following the work- protection vehicle was late. Therefore, it is necessary to actively introduce methods to provide warning information so that the driver can recognize the work-protection vehicle in advance and carry out appropriate evasive maneuvers.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.141-155
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• 2017

As the use of SNS becomes more active, many people are posting their thoughts about specific events in their SNS in the form of text. As a result, SNS is used in various fields such as finance and distribution to conduct service satisfaction surveys and consumer monitoring. However, in the transportation area, there are not enough cases to utilize unstructured data analysis such as emotional analysis. In this study, we developed an emotional analysis methodology that can be used in transportation by using highway VOC data, which is atypical data collected by Korea Expressway Corporation. The developed methodology consists of morpheme analysis, emotional dictionary construction, and emotional discrimination of the collected unstructured data. The developed methodology was verified using highway related tweet data. As a result of the analysis, it can be guessed that many information and information about the construction and the accident were related to the highway during the analysis period. Also, it seems that users complain about the delay caused by construction and accident.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.2
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• pp.135-148
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• 2020

The ongoing development of autonomous driving-related technology may cause different kinds of accidents while testing new changes. As a result, more information on ODD suitable for the domestic road environment will be necessary to prevent safety accidents. Besides, implementation of the Autonomous Vehicle Act will increase autonomous driving demonstrations on roads currently in use. This study describes an ODD for demonstrating an autonomous driving shuttle in downtown areas. It addresses a possible scenario of autonomous driving around a downtown road in Anyang. Geometric, operational, and environmental factors are considered while maintaining a domestic road environment and safety. Autonomous driving shuttles are demonstrated in 30 nodes, each identified by node type and signal-communication. Link criteria are an autonomous driving restriction in 42 morning peak (8-9am) hours, 39 non-peak (12-13pm) hours, and 40 afternoon peak (18-19pm) hours. In the future, conclusions may be considered for preliminary safety assessments of roads where autonomous driving tests are performed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.2
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• pp.18-35
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• 2020

Many human, roadway, and vehicle factors affect vehicle-pedestrian crashes. Especially, the roadway factors are easily defined and suitable for suggesting countermeasures. The characteristics of the road network are one of the roadway factors. The road network significantly influences behaviors and conflicts of drivers and pedestrians. A metropolitan city such as Seoul contains various types of road networks, and crash prevention strategy considering characteristics of the road network is required. In this study, we analyze the effects of road networks on vehicle-pedestrian crashes. In the study, high order road ratio, intersection ratio, high-low intersection ratio are considered as road network variables. Using Geographically Weighted Poisson Regression, crash frequencies in Dongs of Seoul are analyzed based on the road network variable as well as socioeconomic variables. As a result, Dongs are grouped by coefficient signs, and each group is suggested about improvement directions considering conflict situations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.2
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• pp.48-61
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• 2020

The objective of this study is to estimate traffic capacity based on the heavy-vehicle ratio in a two-lane freeway work zone where one lane is blocked by construction. For this, closed circuit television (CCTV) video data of the freeway work zone was collected, and the congestion at an upstream point was observed. The traffic volume at a downstream point was analyzed after a bottleneck was created by the blockage due to the upstream congestion. A distribution model was estimated using observed-time headway, and the road capacity was analyzed using a goodness-of-fit test. Through this process, the general capacity and an equation for capacity based on the heavy-vehicle ratio passing through the work zone were presented. Capacity was estimated to be 1,181~1,422 passenger cars per hour per lane (pcphpl) at Yeongdong, and 1,475~1,589pcphpl at Jungbu Naeryuk. As the ratio of heavy vehicles increased, capacity gradually decreased. These findings can contribute to the proper capacity estimation and efficient traffic operation and management for two-lane freeway work zones that block one lane due to a work zone.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.2
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• pp.62-73
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• 2020

Access management is aimed at preserving the road's high intercity mobility. In urbanized areas, immoderate acceleration lane-length requirements restrict the accessibility of land. Therefore, there are many opinions to revise the minimum acceleration lane-length requirement. For this purpose, it is important to diagnose the effects of slow vehicles on the mainline. This study analyzed a single merging vehicle's total delay occurrence depending on the mainline traffic flow rate and merging speed. A linear relationship was observed between the mainline traffic flow rate and total delay. As a merging speed increases gradually from 40km/h to 100km/h in 20km/h intervals, the total delay decreases by 5.0, 1.6, and 5.1 times, respectively. This shows that the ideal condition with the total delay is less than 0.5 vehicle·sec when there is no speed difference between the mainline and merging vehicle. On the other hand, given the one-second response time of drivers, the total delay occurrence was slightly low when the speed difference between the mainline and merging vehicle was less than 20km/h.