• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.4
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• pp.44-55
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• 2013

Intelligent transportation systems allow us to have valuable opportunities for collecting reliable wide-area coverage traffic and weather data. Significant efforts have been made in many countries to apply these data. This study identifies the critical points for classifying rain intensity by analyzing the relationship between rainfall and the amount of speed reduction. Then, traffic prediction performance by rain intensity level is evaluated using relative errors. The results show that critical points are 0.4mm/5min and 0.8mm/5min for classifying rain intensity (slight, moderate, and heavy rain). The best prediction performance is observable when previous five-block speed data is used as inputs under normal weather conditions. On the other hand, previous two or three-block speed data is used as inputs under rainy weather conditions. The outcomes of this study support the development of more reliable traffic information for providing advanced traffic information service.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.29-41
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• 2017

In this study, we used individual trip data to estimate a macroscopic fundamental diagram (MFD) that relates flow (or production) to density (or state) in Daegu metropolitan city. The individual trip data were generated by processing data that were collected from DSRC-based (dedicated short range communication) traffic data collection system. Using the processed individual trip data, we first examined whether the assumptions for MFD are valid, and then the relation between outflow and accumulation was estimated in our study site. As a result, we found that i) the assumptions are valid to construct MFD; and ii) the reproducible and well-defined MFDs exist in the network level.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.134-143
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• 2020

With the worldwide spread of African swine fever, interest in livestock epidemics is growing. Livestock transport vehicles are the main cause of the spread of livestock epidemics, but no empirical quarantine procedures and standards related to the mobility of livestock transport vehicles in South Korea. This study extracted livestock-related vehicles' trajectory by utilizing the facility visit history data from the Korea Animal Health Integrated System and the DTG (Digital Tachograph) data from the Korea Transportation Safety Authority and presented them as exposure indexes aggregating the link-time occupancy of each vehicle. As a result, a total of 274,519 livestock-related vehicle trajectories were extracted, and exposure values by link and zone were quantitatively derived. Through this study, it is expected that prior monitoring of livestock transport vehicles and the establishment of post-disaster prevention policies would be provided.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.1-15
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• 2023

In this study, the number of truck traffic accidents was predicted by using Poisson and negative binomial regression analysis to understand what factors affect accidents using expressway data. Significant variables in the truck traffic accident prediction model were continuous driving time, link length, truck traffic volume. number of bridges and number of drowsy shelters. The calculated LOSS rating was expressed on the national expressway network to diagnose the risk of truck accidents. This is expected to be used as basic data for policy establishment to reduce truck accidents on expressways.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.221-239
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• 2022

Various elements such as geometry, traffic safety facilities, congestion level, weather, etc., need to be appropriately reflected in the assessment scenario evaluating the driving safety of automated vehicles. Therefore, this study first established a scenario structure and defined the layer of elements, to derive the elements to be reflected in the automated driving safety evaluation. After that, all elemental candidates that can be reflected in each layer were derived by reviewing the relevant literature. Finally, as a result of an expert survey, 77 items were selected to be reflected in the automated driving safety evaluation. The selected elements are expected to be actively utilized in developing scenarios for the driving safety evaluation of automated vehicles in simulation, proving ground, and real road assessments.

• Journal of Information Processing Systems
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• v.1 no.1 s.1
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• pp.27-31
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• 2005

Vehicle detector system based on image processing technology is a significant domain of ITS (Intelligent Transportation System) applications due to its advantages such as low installation cost and it does not obstruct traffic during the installation of vehicle detection systems on the road[1]. In this paper, we propose architecture for vehicle detection by using image processing. The architecture consists of two main parts such as an image processing part, using high speed FPGA, decision and calculation part using CPU. The CPU part takes care of total system control and synthetic decision of vehicle detection. The FPGA part assumes charge of input and output image using video encoder and decoder, image classification and image memory control.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.137-154
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• 2019

This study analysed the center control emergency vehicle preemption[EVP] test result on the 1.782 km section around Gangbuk Fire Station. The pros and cons between center control and site control EVP was compared through the review of existing research. The test site was selected based on the higher link speed for choosing low congested area and 4 to 6 lane road. EVP operates green extension under the estimated arrival time to each intersection. This study is about EVP system field application and its evaluation by analyzing EVP operation result with the emergency vehicle's trace, GPS data. The impact on the surrounding traffic was analysed in delay from the queue length survey. Analysis showed the decrease in averge travel time 41.81%, but the increase in delay of surrounding traffic slightly. It is expected that EVP can be applied to the expanded area by researching EVP compensation scheme.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.175-189
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• 2023

Fault detection and diagnosis (FDI) algorithms are actively being researched for ensuring the integrity and reliability of environment perception sensors in autonomous vehicles. In this paper, a fault detection algorithm based on a multi-sensor perception system composed of radar, camera, and lidar is proposed to guarantee the safety of an autonomous vehicle's perception system. The algorithm utilizes reference generation filters and residual generation filters based on finite impulse response (FIR) filter estimates. By analyzing the residuals generated from the filtered sensor observations and the estimated state errors of individual objects, the algorithm detects faults in the environment perception sensors. The proposed algorithm was evaluated by comparing its performance with a Kalman filter-based algorithm through numerical simulations in a virtual environment. This research could help to ensure the safety and reliability of autonomous vehicles and to enhance the integrity of their environment perception sensors.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.8
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• pp.1157-1162
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• 2013

This thesis describes the active cruise control which is a part of AVHS(Advanced Vehicle and Highway System) in the ITS(Intelligent Transportation Systems). The active cruise control is a system which recognizes some obstructions and vehicles in front, drives in safe speed and puts on the brake in dangerous situations as the driver simply turns on the switch without stepping on the accelerator and brake. PID controller is used in the speed-control by linearizing the longitudinal model of the vehicle, obstacle detecting algorithm which makes use of the laser scanner is proposed to recognize the situation in front and the system's performance is tested.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.33-43
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• 2016

Public transportation card data, which is collected for purposes of the Integrated Public Transportation Fare System, provides neither transfer time nor transfer frequency occurring on the metropolitan city-rail (MCR). And because there are no transfer toll gates installed on the MCR, data on transfers between lines are estimated through means such as elicitations using survey questionnaire, or otherwise through macroscopic observations, which poses the risk of transfer time and frequencies being underestimated. For the accurate estimation thereof, an explanation of the transit path that arises between the Entry-and Exit-Gates must be provided. The purpose of this research is twofold : 1) to build a transit path model to reflect the current state of transfer movements on the basis of transportation card reader data, and 2) to deduce information on transfers occurring in the greater metropolis. To achieve these aims, the idea of Big Nodes is introduced in the model to align transportation card reader operation system characteristics with those of the MCR network. The link-label method is applied in the model as well to make certain that the MCR network runs in an effective manner. Administrative information obtained by the transportation card reader is used to derive transfer time and frequency both in the city's mid-zones, and in the Seoul-Gyeonggi-Incheon district's large-zones. Public transportation card data from a single specific day in year 2014 is employed in the building of the quantified transfer specific data. Extended usage thereof as providing comprehensive data of transfer resistance on the MCR is also examined.