• Journal of Korean Society of Transportation
• /
• v.26 no.1
• /
• pp.215-223
• /
• 2008

Due partly to lack of actual lane-changing data and partly to few studies on simulation functions to consider the lane-changing behavior, it may result in significant difference between simulation-based and real conditions. The objectives of this study are to estimate the set of mandatory lane-changing models and to analyze their features, depending on the merge control strategies under the lane-closed work zone operations. To achieve them, first, the elaborated calibration is required to simulate the mandatory lane-changing behaviors with the actual field data. Second, one can estimate their models with the logistic regression models, to obtain traffic variables as well as the lane-changing frequencies under the various levels of work zone traffic conditions. As a result, one can state that the well-calibrated simulation has the potential to properly reflect the target mandatory lane-changing behaviors. In addition, it should be mentioned that the set of proposed models is not practicable but preliminary result needed to identify the relations between the actual traffic conditions and lane-changing maneuvers and to develop their practical models for the actual applications.

• Journal of Korean Society of Transportation
• /
• v.18 no.5
• /
• pp.83-97
• /
• 2000

The traffic management schemes through traffic signal control and information provision could be effective when the link-level data and trip-level data were used simultaneously in analysis Procedures. But, because the trip-level data. such as origin, destination and departure time, can not be obtained through the existing surveillance systems directly. It is needed to estimate it using the link-level data which can be obtained easily. Therefore the objective of this study is to develop the model to estimate O-D demand using only the link flows in highway network as a real time. The methodological approaches in this study are kalman filer, least-square method and normalized least-square method. The kalman filter is developed in the basis of the bayesian update. The normalized least-square method is developed in the basis of the least-square method and the natural constraint equation. These three models were experimented using two kinds of simulated data. The one has two abrupt changing Patterns in traffic flow rates The other is a 24 hours data that has three Peak times in a day Among these models, kalman filer has Produced more accurate and adaptive results than others. Therefore it is seemed that this model could be used in traffic demand management. control, travel time forecasting and dynamic assignment, and so forth.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.17 no.6
• /
• pp.121-132
• /
• 2018

Weather is an important factor affecting roadway transportation in many aspects such as traffic flow, driver 's driving patterns, and crashes. This study focuses on the relationship between weather and road surface condition and develops a model to estimate the road surface condition using machine learning. A road surface sensor was attached to the probe vehicle to collect road surface condition classified into three categories as 'dry', 'moist' and 'wet'. Road geometry information (curvature, gradient), traffic information (link speed), weather information (rainfall, humidity, temperature, wind speed) are utilized as variables to estimate the road surface condition. A variety of machine learning algorithms examined for predicting the road surface condition, and a two - stage classification model based on 'Random forest' which has the highest accuracy was constructed. 14 days of data were used to train the model and 2 days of data were used to test the accuracy of the model. As a result, a road surface state prediction model with 81.74% accuracy was constructed. The result of this study shows the possibility of estimating the road surface condition using the existing weather and traffic information without installing new equipment or sensors.

• The Journal of the Korea Contents Association
• /
• v.10 no.3
• /
• pp.44-52
• /
• 2010

The most popular world wide web traffic in the Internet uses TCP as the transport layer protocol. Since TCP utilizes the single path, it can not communicate with the correspondent host during the link-down. On the other hand, SCTP can still communicate with the other SCTP entity by using alternate path even while the primary path is down. Most of previous studies have conducted the performance comparison research between TCP and SCTP by using typical file transfer. Since web traffic with self-similarity is characterized by the packet inter-arrival times and shape parameter affecting the size of web file in the Pareto distribution, it is necessary to perform the experiments considering these parameters. This paper aims to compare the throughput between TCP and SCTP while varying parameters reflecting the web traffic characteristics in link-down environment. Experimental results for web traffic using NS-2 simulator show that the throughput of SCTP using multi-homing is better than that of TCP. Simulation also shows that TCP is more affected than SCTP by mean inter-arrival and shape parameters with regard to the web traffic. These results can be applied to estimate the performance variation of web traffic due to the duration of link-down.

• Journal of Korean Society of Transportation
• /
• v.26 no.4
• /
• pp.99-110
• /
• 2008

It is commonly estimated that there is a much higher potential for accidents at a crossroads than along a single road due to its plethora of conflicting points. According to the 2006 figures by the National Police Agency, the number of traffic accidents at crossroads is greatly increasing compared to that along single roads. Among others, crossroads installed with traffic signals have more varied influential factors for traffic accidents and leave much more room for improvement than ones without traffic signals; thus, it is expected that a noticeable effect could be achieved in safety if proper counter-measures against the hazards at a crossroads were taken together with an estimate of causes for accidents This research managed to develop models for accident forecasts and accident intensity by applying data on accident history and site inspection of crossroads, targeting four selected downtown crossroads installed with traffic signals. The research was done by roughly dividing the process into four stages: first, analyze the accident model examined before; second, select variables affecting traffic accidents; third, develop a model for traffic accident forecasting by using a statistics-based methodology; and fourth, carry out the verification process of the models.

• Journal of Korean Society of Transportation
• /
• v.30 no.6
• /
• pp.71-80
• /
• 2012

This research suggested a real-time traffic signal control algorithm using individual vehicle travel times on an isolated signal intersection. To collect IDs and passing times from individual vehicles, space-based surveillance systems such as DSRC were adopted. This research developed models to estimate arrival flow rates, delays, and the change rate in delay, by using individual vehicle's travel time data. This real-time signal control algorithm could determine optimal traffic signal timings that minimize intersection delay, based on a linear programming. A micro simulation analysis using CORSIM and RUN TIME EXTENSION verified saturated intersection conditions, and determined the optimal traffic signal timings that minimize intersection delay. In addition, the performance of algorithm varying according to market penetration was examined. In spite of limited results from a specific scenario, this algorithm turned out to be effective as long as the probe rate exceeds 40 percent. Recently, space-based traffic surveillance systems are being installed by various projects, such as Hi-pass, Advanced Transportation Management System (ATMS) and Urban Transportation Information System (UTIS) in Korea. This research has an important significance in that the propose algorithm is a new methodology that accepts the space-based traffic surveillance system in real-time signal operations.

• International Journal of Highway Engineering
• /
• v.19 no.6
• /
• pp.191-199
• /
• 2017

PURPOSES : The objective of this study is to develop a methodology to estimate the minimum required separation distance (MRSD) between a vehicle and a bicycle when overtaking. METHODS : Three steps have been conducted to develop a methodology to estimate MSRD. First, a literature review has been conducted on the measurement of MSRD, and how it may be applied in Korea. Second, two assumptions have been made to develop a methodology to estimate the MSRD. The first assumption is that the maximum separation distance between a vehicle and a bicycle can be observed when they are at the same location longitudinally. In addition, it is assumed that the separation distance is invalid when the contra-flow exists. Finally, three cameras were installed at a height of 10 m to record the vehicle-bicycle interaction. Moreover, the vehicle trajectories as well as the separation distance were coded and analyzed. Through the hypothesis test and the interval estimation, the sample mean was tested and the confidence interval was estimated. RESULTS : 141 records of separation distance data were collected, and the hypothesis test demonstrated that the MSRD in Korea is significantly higher than other countries. In addition, the confidence interval of the population mean of MSRD is from 1.51 m to 1.65 m with 95% level of confidence. CONCLUSIONS : It is expected that the proposed methodology to estimate MSRD would be beneficial in studying road safety of vehicles and bicycles. Also, the proposed MSRD is expected to be designated in the act of road and transportation.

• Journal of the Ergonomics Society of Korea
• /
• v.31 no.2
• /
• pp.371-377
• /
• 2012

Objective: The aim of this study is to investigate effect of driver's cognitive distraction on driver's physiological state and driving performance, and then to determine parameters appropriate for detecting the cognitive distraction. Background: Driver distraction is a major cause of traffic accidents and poses a serious threat to traffic safety due to ever increasing use of in-vehicle information systems and mobile phones during driving. Cognitive distraction, among four different types of distractions, prevents a driver from processing traffic information correctly and adapting to change in surround vehicle behavior in time. However, the cognitive distraction is more difficult to detect because it normally does not involve significant change in driver behavior. Method: A full-scale driving simulator was used to create virtual driving environment and situations. Participants in the experiment drove the driving simulator in three different conditions: attentive driving with no secondary task, driving and conducting secondary task of adding numbers, and driving and conducting secondary task of conversing with an experimenter. Parameters related with driver's physiological state and driving performance were measured and analyzed for their change. Results: The experiment results show that driver's cognitive distraction, induced by secondary task of addition and conversation during driving, increased driver's cognitive workload, and indeed brought change in driver's physiological state and degraded driving performance. Conclusion: The galvanic skin response, pupil size, steering reversal rate, and driver reaction time are shown to be statistically significant for detecting cognitive distraction. The appropriate combination of these parameters will be used to detect the cognitive distraction and estimate risk of traffic accidents in real-time for a driver distraction warning system.

• Journal of Korean Society of Transportation
• /
• v.23 no.6 s.84
• /
• pp.19-30
• /
• 2005

The objective of this research is to keep track of path travel time using methods of collecting traffic data. Users of traffic information are looking for extensive information on path travel time, which is referred to as the time taken for traveling from the origin to the destination. However, all the information available is the average path travel times, which is a simple sum of the average link travel times. The average path travel time services are not up to the expectation of traffic information consumers. To improve provide more accurate path travel time services, this research makes a number of different estimates of various path travel times on one path, assuming it will be under the same condition, and provides a range of estimates with their probabilities to the consumers, who are looking for detailed information. To estimate the distribution of the path travel times as a combination of link travel times. this research analyzes the relation between the link travel time and path travel time. Based on the result of the estimation. this research develops the algorithm that combines the distribution of link travel time and estimates the path travel time based on the link travel times. This algorithm was tested and proven to be highly reliable for estimating the path traffic time.

• Journal of Korean Society of Transportation
• /
• v.19 no.5
• /
• pp.61-70
• /
• 2001

The origin and destination(O-D) matrix is one of the most important elements in transportation planning process. Traditionally, transport planners survey the O-D movements in order to estimate the O-D matrix. Even though the cost of the O-D survey requires high amounts of resources, the accuracy is relatively low. Therefore, many researchers have studied the estimation of the O-D matrix for automobile from traffic counts. however, there is a little attention for the application on the transit O-D matrix estimation from traffic counts. The objective of this study is therefore the estimation of the transit O-D matrix from traffic counts using Gradient method. which is verified by the reliability analysis using a contrived small example network.