• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.5
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• pp.13-21
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• 2013

Super high-rise buildings of combined use such as large shopping malls and multiplex etc. have larger parking facilities than general buildings and are characteristic of an increase in the number of the entrance and the exit connecting internal external space of the parking lot. These features cause a congestion of internal traffic by increasing car driving distance in the parking lot, and vehicle idling increases by drivers wander the parking lot in order to find parking space. In addition, they make drivers suffer from lots of difficulties due to parking including increasing their walking line after parking. Therefore, in this study, we developed individual parking information provision algorithm to specify the optimal parking place for drivers according to the purpose of visiting a building and the drivers' moving path, and selected new construction site for the second lotte world in order to evaluate the algorithm developed and performed evaluation. As a result of the evaluation, it was analyzed that in the case of applying the individual parking information provision algorithm compared to the existing parking information provision algorithm, moving distance in the parking lot decreases around 7.43~83.4%, and that in the case of $CO_2$ emission, it decreased about 47.7% on average, which indicates that the efficiency resulted from application of the individual parking information provision algorithm is very high as the application effects are tested.

• Journal of Korean Society of Transportation
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• v.21 no.1
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• pp.53-63
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• 2003

The Origin-Destination(OD) matrix is very important in describing transport movements in a region. The OD matrix can be estimated using traffic counts on links in the transport network and other available information. This information on the travel is often contained in a target OD matrix and traffic counts in links. To estimate an OD matrix from traffic counts, they are the major input data which obviously affects the accuracy of the OD matrix estimated, Generally, the quality of an estimated OD matrix depends much on the reliability of the input data, and the number and locations of traffic counting points in the network. Any Process regarding the traffic counts such as the amount and their location has to be carefully studied. The objective of this study is to select of the optimal location of traffic counting points for the OD matrix estimation. The model was tested in nationwide network. The network consists of 224 zones, 3,125 nodes and 6,725 links except to inner city road links. The OD matrix applied for selection of traffic counting points was estimated to 3-constrained entropy maximizing model. The results of this study follow that : the selected alternative to the best optimal counting points of six alternatives is the alternative using common links of OD matrix and vehicle-km and traffic density(13.0% of 6,725 links), however the worst alternative is alternative of all available traffic counting points(44.9% of 6,725 links) in the network. Finally, it should be concluded that the accuracy of reproduced OD matrix using traffic counts related much to the number of traffic counting points and locations.

• Journal of Korean Society of Transportation
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• v.35 no.5
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• pp.458-467
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• 2017

The expressway of the Korea has an important role in freight movement because 76 percent of the commodity is transported by trucks. However, there has been few indices on the role of expressways regarding freight transportation and truck traffic. The objective of this study is to propose four freight transportation related indices using ITS-related system such as TCS and HS-Wim: total truck's travel miles ($veh{\cdot}km/year$), total freight transport miles ($ton{\cdot}km/year$). efficiency of truck's travel ($veh{\cdot}km/km$), and efficiency of freight movement ($ton{\cdot}km/km$). These truck and freight related indices were estimated and compared by two different data sources: traffic volume data using VDS and OD data using TCS. These indices were designed to estimated on real time and updated every day and month.

• Korean Journal of Community Nutrition
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• v.12 no.5
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• pp.617-629
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• 2007

To ensure the microbiological safety of food items prepared after cooking process, this study was aimed to identify the hazards related with cooked foods donated to foodbanks through quantitative microbial analysis. Five foodbanks located in Incheon and Gyeonggi area among government-dominant foodbanks were surveyed from February to June, 2007. Manager, recipient, donator, type and quantity of donated foot and facility and equipment were examined for the general characteristics of foodbank. The time and temperature of food md environment were measured at steps from after-production to before-distribution, and the microbial analysis was performed mainly with indicator organism and major pathogens. The amount of cooked foods donated to each foodbank was about 20 to 30 servings and consisted of 80% of total donated foods. Only three foodbanks had separate offices for foodbank operation and four institutions had at least one temperature-controlled vehicle. The flow of donated foods was gone through the steps; production, meal service and holding at donator, collection by foodbank, transport (or holding after transport) and distribution to recipients. It took about 3.8 to 6.5 hours at room temperature from after-production to before-distribution. Only aerobic plate counts (APC) and coliforms were found in microbial analysis. The APC after production were relatively high in $8.2{\times}10^5,\;7.4{\times}10^5,\;6.9{\times}10^5$ and $4.2{\times}10^5 CFU/g$ while $2.8{\times}10^6, \;9.4{\times}10^5,\;1.0{\times}10^6$ and $5.4{\times}10^5CFU/g$ before distribution in mixed Pimpinella brachycarpa, mixed chard mixed amaranth and mixed spinach, respectively. The levels of coliforms in mixed chard and mixed spinach were complied with the standards of the Ministry of Education and Human Resources Management The level of APC in boiled pork was increased from $< 1.0{\times}10 CFU/g$ to $4.0{\times}10^2 CFU/g$. One of delivery vessels was shown $6.2{\times}10^3 CFU/100 cm^2$ in APC, which was over the standards for environment. One of serving tables also showed the high level of $1.2{\times}10^3 CFU/100 cm^2$ in APC and $6.6{\times}10^2 CFU/100 cm^2$ in coliforms. These results suggest the sanitary management of holding at donator and the time-temperature control are key factors to ensure the safety of cooked foods donated to foodbank.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.4
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• pp.153-163
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• 2017

This research is based on the previous research that personally preferred safe distance, rotating angle and speed are differentiated. Thus, we use machine learning model for recognizing maneuvering modes trained per personal or per similar driving pattern groups, and we evaluate automatic driving according to maneuvering modes. By utilizing driving knowledge, we subdivided 8 kinds of longitudinal modes and 4 kinds of lateral modes, and by combining the longitudinal and lateral modes, we build 21 kinds of maneuvering modes. we train the labeled data set per time stamp through RNN, LSTM and Bi-LSTM models by the trips of drivers, which are supervised deep learning models, and evaluate the maneuvering modes of automatic driving for the test data set. The evaluation dataset is aggregated of living trips of 3,000 populations by VTTI in USA for 3 years and we use 1500 trips of 22 people and training, validation and test dataset ratio is 80%, 10% and 10%, respectively. For recognizing longitudinal 8 kinds of maneuvering modes, RNN achieves better accuracy compared to LSTM, Bi-LSTM. However, Bi-LSTM improves the accuracy in recognizing 21 kinds of longitudinal and lateral maneuvering modes in comparison with RNN and LSTM as 1.54% and 0.47%, respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.162-177
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• 2020

The perception of traffic environment based on various sensors in autonomous driving system has a direct relationship with driving safety. Recently, as the perception model based on deep neural network is used due to the development of machine learning/in-depth neural network technology, a the perception model training and high quality of a training dataset are required. However, there are several realistic difficulties to collect data on all situations that may occur in self-driving. The performance of the perception model may be deteriorated due to the difference between the overseas and domestic traffic environments, and data on bad weather where the sensors can not operate normally can not guarantee the qualitative part. Therefore, it is necessary to build a virtual road environment in the simulator rather than the actual road to collect the traning data. In this paper, a training dataset collection process is suggested by diversifying the weather, illumination, sensor position, type and counts of vehicles in the simulator environment that simulates the domestic road situation according to the domestic situation. In order to achieve better performance, the authors changed the domain of image to be closer to due diligence and diversified. And the performance evaluation was conducted on the test data collected in the actual road environment, and the performance was similar to that of the model learned only by the actual environmental data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.3
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• pp.38-49
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• 2015

Seoul has 424 traffic fatalities in 2010 and 227 of them related to pedestrian crashes. In addition, it revealed that 40% of pedestrian fatalities occurred during jaywalking. Through the effective methods preventing jaywalking can save lots of people, and it can reduce social costs pertinent to pedestrian crashes. Therefore, this study is to suggest the methods preventing jaywalking through conducting literature reviews, human factors with pedestrian and vehicle characteristics, as well as geometric features of accident site or spot. Firstly, in order for examining the contributing factors of accident, this research conducts statistical analysis on pedestrian accidents specifically in jaywalking. Secondly, the analysis on human factors about pedestrian and drivers revealed that drivers with high speed play pivotal roles in pedestrian fatalities. Thirdly, Road and environment factors showed both expected and contradictory results through analyzing total numbers of lane or dry/icy pavement conditions. Consequently, this study can be used to prevent and alleviate pedestrian accidents as well as expected to be applied to future researches about pedestrian safety facilities.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.6
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• pp.108-117
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• 2011

Seoul metropolitan government has been operating traffic signal control system with the name of COSMOS since 2001. COSMOS uses the degrees of saturation and congestion which are calculated by installing loop detectors. At present, inductive loop detector is generally used for detecting vehicles but it is inconvenient and costly for maintenance since it is buried on the road. In addition, the estimated queue length might be influenced in case of error occurred in measuring speed, because it only uses the speed of vehicles passing by the detector. A traffic signal control algorithm which enables smooth traffic flow at intersection is proposed. The proposed algorithm assigns vehicles to the group of each lane and calculates traffic volume and congestion degree using traffic information of each group using VANETs(Vehicular Ad-hoc Networks) inter-vehicle communication. It does not demand additional devices installation such as cameras, sensors or image processing units. In this paper, the algorithm we suggest is verified for AJWT(Average Junction Waiting Time) and TQL(Total Queue Length) under single intersection model based on GLD(Green Light District) Simulator. And the result is better than Random control method and Best first control method. In case real-time control method with VANETs is generalized, this research that suggests the technology of traffic control in signalized intersections using wireless communication will be highly useful.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.3
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• pp.96-106
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• 2014

Necessarily traffic policies have been biased in car than pedestrian, so pedestrian's environment is getting worse. Result of this situation our accident rate is high as 36.4%, compared to OECD member countries with average rate of 17.8%(in 2009). Increasing interest for pedestrians environment improvement, and it make an effort to build environment to guarantee walk and safety of pedestrians. Analysis on the binary logistic regression(BLR) was used. The dependent variable is occurring from the road width of less than 9m accident, and independent variable extracted can be obtained from the traffic accident data. Traffic accident on roads having width of less than 9 meters affecting variables is when the driver is straight, when the driver is female, when the pedestrian is walk driveway, and so on. To prevent it, efforts is demanded to protect handicapped, to build safe pedestrians environment using C-ITS and to decrease speed of going straight vehicle on roads having width of less than 9 meters.

• 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.