• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.143-160
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• 2023

It is important to secure the golden time of emergency vehicles for quick responses in disaster situations, such as fire, rescue, and first aid. This study proposes plans Emergency Vehicle Preemption (EVP) based on the analysis of emergency vehicle operation to secure the golden time of emergency vehicles and increase driving safety. The emergency vehicle dispatch statistics, emergency vehicle traffic accident statistics, and survey were used for the analysis. As a result of the analysis, the frequency of dispatch of emergency vehicles and traffic accidents are increasing gradually, but the rate of securing the golden time of emergency vehicles is approximately half, indicating that improvement measures are urgent. In the questionnaire survey, most citizens consent to the necessity of introducing EVP. In addition, the criteria for the range of emergency vehicles that could provide EVP and the allowable time for waiting were derived. These results could be used to prepare EVP operation strategies, and it is expected to contribute to improving emergency vehicle operation safety and increasing the golden time securing rate through a rapid expansion of EVP.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.20-37
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• 2023

Although traffic signal installations are continuously expanding, the effect of preventing traffic accidents remains unverified. Totally, 7,045 traffic accident data (such as signal violations) registered with TCS were manually searched for a 7-year period from 2013 to 2019 for 1,602 traffic signals in Daejeon Metropolitan City. The top 20 traffic accident intersections were identified, the traffic accident investigation records and field maps were viewed to compare the driving direction and signal phase of the violated vehicle, and the cause of the traffic accident was divided into insufficient signal operation design (operation) and driver negligence (intentional). Results of the analysis revealed that 75% of traffic accidents occurred in thru-left-turn traffic signals and overlap; moreover, extending the yellow time or operating all red signals due to countermeasures against traffic accidents occurring in yellow signals resulted in reduced traffic accidents. Data indicated that Permissive Left Turn requires improvement with the signal operation. In addition, since The Korean National Police Agency is not computerized for traffic accident sites and signal-related data, the lack of manpower necessitates improvement and utilization of TCS when establishing traffic accident prevention measures. It is believed that it will contribute to signal operation by analyzing vast amounts of data collected in the field and presenting improvement measures.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.19-29
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• 2023

The accident rate in South Korea is simply classified according to the road type and the number of lanes, but other countries apply various factors affect accidents. In this study, national highways where accidents occurred were divided into urban, rural, older, and modern roads using TAAS(Traffic Accident Analysis System) data, and a model of accident costs savings is suggested. As a result of analyzing 1,416.2 km, the fatality rate(person/100mil-vehicle·km) was 4.21 for urban-older, 1.37 for urban-modern, 2.18 for rural-older, and 0.99 for rural-modern roads. The rates of urban roads had a higher result than rural. The injury rate(person/100mil-vehicle·km) for urban-older was 182.63, that for urban-modern was 103.42, that for rural-older was 67.44, and that for rural-modern road was 42.96, which showed a similar pattern to fatality rates. Accident rates of a modern road were much lower than the KDI Guideline. The benefit of applying the result of this study was calculated and the valuation of accident costs savings is increased from 0.6% to 14.1%, while B/C is improved from 0.626 to 0.724.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.79-88
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• 2024

We used actual field data to analyze from a traffic engineering perspective how AI and edge computing technologies affect the reduction of traffic accidents. By providing object information from 20m behind with AI object recognition, the driver secures a response time of about 3.6 seconds, and with edge technology, information is displayed in 0.5 to 0.8 seconds, giving the driver time to respond to intersection situations. In addition, it was analyzed that stopping before entering the intersection is possible when speed is controlled at 11-12km at the 10m point of the intersection approach and 20km/h at the 20m point. As a result, it was shown that traffic accidents can be reduced when the high object recognition rate of AI technology, provision of real-time information by edge technology, and the appropriate speed management at intersection approaches are executed simultaneously.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.32-48
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• 2023

Autonomous driving technology is shaping the future of personalized travel, encouraging personalized travel, and traffic impact could be influenced by individualized travel behavior during the transition of driving entity from human to machine. In order to evaluate traffic impact, it is necessary to estimate the total number of trips based on an understanding of individual travel characteristics. The Activity-based model(ABM), which allows for the reflection of individual travel characteristics, deals with all travel sequences of an individual. Understanding the relationship between travel and travel must be important for assessing traffic impact using ABM. However, the ABM has a limitation in the data hunger model. It is difficult to adjust in the actual demand forecasting. Therefore, we utilized a Tour-based model that can explain the relationship between travels based on household travel survey data instead. After that, vehicle registration and population data were used for correction. The result showed that, compared to the KTDB one, the traffic generation exhibited a 13% increase in total trips and approximately 9% reduction in working trips, valid within an acceptable margin of error. As a result, it can be used as a generation correction method based on Tour, which can reflect individual travel characteristics, prior to building an activity-based model to predict demand due to the introduction of autonomous vehicles in terms of road operation, which is the ultimate goal of this study.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.3
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• pp.1-16
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• 2024

In the present highway design guidelines suggest that the capacity of one-lane hi-pass lanes is 2,000 veh/h for mainline toll plaza and 1,700 veh/h for interchange toll plaza. However, in a study conducted in early 2010, capacity of the mainline toll plaza was presented with 1,476 veh/h/ln to 1,665 veh/h/ln, and capacity of the interchange toll plaza was presented as 1,443 veh/h/ln. Accordingly, this study examined the feasibility of the capacity of the currently proposed highway one-lane hi-pass lane. Based on the 2021 individual vehicle passing data collected from the one-lane hi-pass gantry, the speed-traffic volume relationship graph and headway were used to calculate and compare capacity. In addition, the bootstrapping technique was introduced to utilize the headway and new processing methods for collected data were reviewed. As a result of the analysis, the one-lane hi-pass capacity could be estimated at 1,700 veh/h/ln for the interchange toll plaza, and at least 1,700 veh/h/ln for the mainline toll plaza. In addition, by using the bootstrap technique when using headway data, it was possible to present an estimated capacity similar to the observed capacity.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.4
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• pp.37-53
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• 2024

This study selected bicycle road hazard detection factors for mobile IoT sensor device operation and developed service application plans. Twelve bicycle road hazard detection factors were derived through a focused group interview, and a fuzzy AHP-based importance analysis was conducted on 30 road and transportation experts. As a result, 'damage to pavement' (1st overall) and 'environmental obstacle' (2nd) with low visibility but a high risk of accidents were selected the most. The factors in terms of facility management, such as 'disconnected route occurrence' (4th), 'artificial obstacle' (5th), 'effective width' (6th), and 'poor drainage' (7th), were selected as the upper and middle areas. Factors that are not direct accident-inducing factors, such as 'loss of road markings' (11th) and 'free space width' (12th), were selected the least. Based on this, a plan was presented to apply the bicycle road hazard detection service and a service operation strategy according to real-time performance. Nevertheless, follow-up studies, such as human behavioral analysis based on bicycle operators, analysis according to the bicycle road type, service demonstration, and pilot operation, will be needed to develop safe bicycle road management is expected.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.67-74
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• 2022

In recent, the number of real-time traffic information sources and providers has increased as increasing smartphone users and intelligent transportation system facilities installed at roadways including vehicle detection system (VDS), dedicated short-ranged communications (DSRC), and global positioning system (GPS) probe vehicle. The accuracy of such traffic information would vary with these heterogeneous information sources or spatiotemporal traffic conditions. Therefore, the purpose of this study is to propose an empirical strategy of heterogeneous information fusion to improve the accuracy of real-time traffic information. To carry out this purpose, travel speed data collection based on the floating car technique was conducted on 227 freeway links (or 892.2 km long) and 2,074 national highway links (or 937.0 km long). The average travel speed for 5 probe vehicles on a specific time period and a link was used as a ground truth measure to evaluate the accuracy of real-time heterogeneous traffic information for that time period and that link. From the statistical tests, it was found that the proposed fusion strategy improves the accuracy of real-time traffic information.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.12
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• pp.1113-1118
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• 2012

Smart grid and intelligent transportation system draw significant interest since they are considered as one of the green technologies. These systems require a large number of sensors, actuators, and controllers. Also, machine-to-machine (M2M) communications is important because of the automatic control. The LTE-Advanced networks is preparing a set of functions that facilitate the M2M communications, and particularly the development of an efficient call admission control mechanism is critical. A method that groups MTC devices according to QoS constraints and determines the admission depending on the QoS satisfaction is limitedly applied only if the data transmission period and the maximum delay are identical. This paper proposed a call admission control that is free from such limitation and also optimizes the admission process under the certain condition of the transmission period and maximum delay. The theorems regarding the proposed method are presented with the proofs. The simulations confirms its validity and shows it is better in call admission probability than existing works.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.3 s.37
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• pp.3-11
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• 2006

The need for edge detection about topography data from the high resolution satellite imagery is happening with increasing frequency according to many people utilize the its imagery as various fields recently. Many experts is recognizing of other GIS will make use of the road detection from the high resolution satellite imagery, including ITS (Intelligent Transportation Systems) and urban planning. This paper is comparative analysis of LPF (Low Pass Filtering) and HPF (High Pass Filtering) for roads edge detection from high resolution satellite imagery. As a result, LPF and HPF can be highlight selective pixels at edge area about input data. In case or applying to other techniques such as LPF for the same purpose, they aye more effective for wide road width which often cause the slight distortion of boundary or overall change of brightness values on the whole Image. Whereas, HPF has ability to enhance selectively detailed components in a target image.