• Journal of Korean Society of Transportation
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• v.34 no.1
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• pp.15-28
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• 2016

The purpose of this study is to prepare countermeasures for aggressive driving and road rage which have recently become a hot issue by analysing mechanism of how the driving behavior determinants(personal anger and aggression) and dangerous driving behavior factors(aggressive driving behavior and over-speeding driving behavior, drunk driving behavior, inattentive driving behavior, and inexperience driving behavior) affect aggressive driving and road rage. From the survey conducted by seven branches of the Road Traffic Authority with 351 people who were traffic offenders and drivers who caused car accidents, this study obtained three results as follows. First, seriousness of aggressive driving and road rage and requirements as types of customized educations, proper length of time for education, and contents of education can be understood. Second, specific relation and mechanism between the driving behavior determinants and dangerous driving behavior factors with respect to aggressive driving and road rage can be clearly identified, which helps to set order of priority and weighting of measures for reducing aggressive driving and road rage. Third, countermeasures can be categorized as corporate measures or customized measures through mechanism analysis model of aggressive driving and road rage.

• International Journal of Highway Engineering
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• v.17 no.2
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• pp.79-87
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• 2015

PURPOSES: According to accident statistics for road built in 2004, the ratio of accidents on frozen roads to normal roads is 0.9%, whereas the fatality ratio is 2.7%. The risk of accidents on frozen roads is very high. Measures taken every year to prevent traffic accidents of frozen roads in the winter season are still insufficient. Additionally, measures have been established mainly on rural roads. Therefore, for urban roads, analyses and measures to prevent accidents are lacking. In this study, data on accidents on frozen roads was used to search for the causes behind these accidents and measures to reduce accidents have been recommended. METHODS: In this study, collected data from the TAMS (Traffic Accident Management System), which were collected by the Seoul National Police Agency was used. The data were divided into vehicle, people, and condition of road. The analytical model used here was the Logistic Regression Model, which is frequently used for traffic safety and accident analysis. This study uses the odds ratio analysis to search for variables related to frozen road traffic accidents in each category. A total of 18 out of 47 variables were found to be the causes of accidents. RESULTS: From the results of the comparative analysis of 18 variables, the category of the condition of the road was found to be the most critical. Contrary to expectations, more accidents occurred in clear weather than in other conditions. Accidents on bridges occurred frequently, and its odds ratio was the highest compared with other road types. When BPT is operated, the probability of accidents on frozen roads is lower than in general conditions, and accidents occurred frequently on roads with less than four lanes. CONCLUSIONS : Based on the results of this study, suggestions for reducing the risk of future domestic road accidents in freezing conditions are indicated as follows. First, it is necessary to perform a technical review of the urban road traffic accidents caused by frozen roads. Second, it is necessary to establish criteria for the study of the road environment based on the major causes of road accidents on frozen roads. Third, improvements in urban road environmental factors should be made.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.32-35
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• 1996

Traffic signal cycle optimization is one of the most efficient ways for reducing fuel consumption and improving vehicle waiting time of highsaturated traffic conditions. But most research focused on lowsaturated traffic conditions. Only a few studies have researched traffic control for highsaturated traffic conditions. In this paper reviews the problem of conventional traffic signal system and creates optimal traffic cycle of at the bottom traffic intersection using 27 fuzzy rules. Moreover, to prevent spillback, it can adapt control even though upper traffic intersection has a different saturation rate, road length, road slope and road width.

• Journal of Korean Society for Geospatial Information Science
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• v.5 no.2 s.10
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• pp.131-144
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• 1997

Traffic jam densified day by day is phenomenon to occur lack of the road capacity in comparison with traffic density, but lack of the road cannot be concluded by main cause of traffic ism. Because the central function of a city would be concentrated upon the downtown and traffic demand would not be evenly distributed by the classification of an hour. Therefore, this study based on the fact that each driver will select the route generating traffic delay very low when path choice from origin to destination in travel plan estimating the quality of passage could be maintained the speed he want will approach to a characteristic grasp of a road, traffic, driver changing every moment by traffic-demand of road increased as a geometrical series with analysis a classification of a street, a intersection along the path on traffic density and highway capacity analysis the path using GIS techniques about complex street network, also will get the path of actual optimum for traffic delay trend creating under various condition the classification per a hour, a day of week and an incident through network such as analysis for traffic generation zone adjacent about street, intersection, afterward will expect the result increasing efficiency of the road-use through a good distribution of traffic by optimum-path choice, accordingly will prepare the scientific, objective, appropriate basis to decide the reasonable time of a road-widen and expansion through section analysis along a rate of traffic volume vs. road capacity.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.35.4-35
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• 2001

Image detection system for road traffic data analysis is a real time detection system using image processing techniques to get the real-time traffic information which is used for traffic control and analysis. One of the most important functions in this system is to match the coordinates of real world and that of image on video camera. When there in no way to know the exact position of camera and it´s height from the object. If some points on the road of real world are known it is possible to calculate the coordinates of real world from image.

• International Journal of Automotive Technology
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• v.7 no.1
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• pp.25-34
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• 2006

For decades, simulation technique has been well validated in areas such as computer and communication systems. Recently, the technique has been much used in the area of transportation and traffic forecasting. Several methods have been proposed for investigating complex traffic flows. However, the dynamics of vehicles and diversities of driver characteristics have never been considered sufficiently in these methods, although they are considered important factors in traffic flow analysis. In this paper, we propose a traffic simulation tool called Multi-Agent for Traffic Simulation with Vehicle Dynamics Model (MATDYMO). Road transport consultants, traffic engineers and urban traffic control center managers are expected to use MATDYMO to efficiently simulate traffic flow. MATDYMO has four sub systems: the road management system, the vehicle motion control system, the driver management system, and the integration control system. The road management system simulates traffic flow for various traffic environments (e.g., multi-lane roads, nodes, virtual lanes, and signals); the vehicle motion control system constructs the vehicle agent by using various vehicle dynamic models; the driver management system constructs the driver agent capable of having different driving styles; and lastly, the integrated control system regulates the MATDYMO as a whole and observes the agents running in the system. The vehicle motion control system and driver management system are described in the companion paper. An interrupted and uninterrupted flow model were simulated, and the simulation results were verified by comparing them with the results from a commercial software, TRANSYT-7F. The simulation result of the uninterrupted flow model showed that the driver agent displayed human-like behavior ranging from slow and careful driving to fast and aggressive driving. The simulation of the interrupted flow model was implemented as two cases. The first case analyzed traffic flow as the traffic signals changed at different intervals and as the turning traffic volume changed. Second case analyzed the traffic flow as the traffic signals changed at different intervals and as the road length changed. The simulation results of the interrupted flow model showed that the close relationship between traffic state change and traffic signal interval.

• Korean System Dynamics Review
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• v.12 no.1
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• pp.75-87
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• 2011

Congestion problems can be approached from the viewpoint of system dynamics theory. The relationship between road capacity and congestion can be explained by the 'relative control' archetype among four system archetypes suggested by Wolstenholme. There is a balancing feedback loop between road capacity and road congestion. However, there is another balancing loop between road congestion and car traffic volume, which keeps disrupting the equilibrium of the former loop. A system dynamics model, which is based on a partial adjustment model of induced traffic in the literature, is built to simulate three road building scenarios: 'Expanding investment', 'Balancing investment' and 'Frozen road investment' scenarios. The 'Expanding investment' scenario manages to drop congestion levels by 9% over 30 years, however, causing much higher emissions of $CO_2$ than other scenarios. The trade-off relationship between congestion levels and environmental costs must be taken into consideration for road investment policies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.841-854
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• 2020

The paper explains the method to process, analyze and predict traffic patterns in Los Angeles county using Big Data and Machine Learning. The dataset is used from a popular navigating platform in the USA, which tracks information on the road using connected users' devices and also collects reports shared by the users through the app. The dataset mainly consists of information about traffic jams and traffic incidents reported by users, such as road closure, hazards, accidents. The major contribution of this paper is to give a clear view of how the large-scale road traffic data can be stored and processed using the Big Data system - Hadoop and its ecosystem (Hive). In addition, analysis is explained with the help of visuals using Business Intelligence and prediction with classification machine learning model on the sampled traffic data is presented using Azure ML. The process of modeling, as well as results, are interpreted using metrics: accuracy, precision and recall.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.8
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• pp.581-588
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• 2002

Precise highway traffic noise simulation and reduction require the accurate data for sound power levels omitted by vehicles, varied to road surface, traffic speed, vehicle types and makers, different from countries to countries. In this study, we have elaboratively measured Korea highway traffic noise and parameters affecting noise levels at the nearside carriageway edge. From numerical simulation using the measured results for highway traffic noise, we propose not only two correction factors to enhance the accuracy of Korea highway traffic sound power estimation using ASJ Model-1998 but also its typical power spectrum according to road surface type. The measured and predicted highway traffic noise levels using the proposed sound power show little difference within 1 dB.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.3
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• pp.14-24
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• 2006

There are many problems and limits in equipments being used for traffic-volume analysis in the country. And traffic-volume information acquired through existing equipments is not provided in real-time. In the case of urban, there are limits on guarantee of trust on comprehending a appropriate road-volume because of difficulty on analyzing traffic-volume density and time series. And it is difficult to applicate in deciding a road policy as existing equipments don't provide the control information of traffic-flow. Therefore, it is necessary to build a road-flow policy rapidly and accurately through the road-flow information that analyze post-processed statistics data using traffic-flow investigation based on real time. In this study, we developed TICS(Traffic Information Collection System) based on GPS which could transmit traffic information transformed from car location information to traffic control center. And we developed TCS(Traffic Control System) based on Web GIS, which could manage and analyze transmitted traffic information, and it could offer handled road-flow information to Web-site in realtime.