• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.3
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• pp.110-119
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• 2017

This study develops a passive traffic signal priority control algorithm for emergency vehicles. The passive priority control estimates and applies signal times for each signalized intersection on the emergency vehicle's route when an emergency call is received. As signals are controlled before the emergency vehicle leaves for its destination, it is possible to clear the queues at each intersection more effectively. Most of the previous studies applied preemption, which ends green time of cross streets when the emergency vehicle arrives at each intersection. This study applies green extension and early green in order not to shift the order of phases, and guarantees minimum green time for each phase. Simulation results show that the delay of emergency vehicles decreases when the signals are controlled. It is expected that delays can be decreased further by integrating the active priority control with the passive priority control algorithm presented in this study.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.3
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• pp.679-690
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• 2015

The need to remove the cause of traffic accidents by improving the engineering system for a vehicle and the road in order to minimize the accident hazard. This is likely to cause traffic accident continue to take a large and significant social cost and time to improve the reliability and efficiency of this generally poor road, thereby generating a lot of damage to the national traffic accident caused by improper environmental factors. In order to minimize damage from traffic accidents, the cause of accidents must be eliminated through technological improvements of vehicles and road systems. Generally, it is highly probable that traffic accident occurs more often on roads that lack safety measures, and can only be improved with tremendous time and costs. In particular, traffic accidents at intersections are on the rise due to inappropriate environmental factors, and are causing great losses for the nation as a whole. This study aims to present safety countermeasures against the cause of accidents by developing an intersection Traffic safety evaluation model. It will also diagnose vulnerable traffic points through BPA (Back -propagation algorithm) among artificial neural networks recently investigated in the area of artificial intelligence. Furthermore, it aims to pursue a more efficient traffic safety improvement project in terms of operating signalized intersections and establishing traffic safety policies. As a result of conducting this study, the mean square error approximate between the predicted values and actual measured values of traffic accidents derived from the BPA is estimated to be 3.89. It appeared that the BPA appeared to have excellent traffic safety evaluating abilities compared to the multiple regression model. In other words, The BPA can be effectively utilized in diagnosing and practical establishing transportation policy in the safety of actual signalized intersections.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.147-154
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• 2004

The purpose of this paper is to improve the existing phase split algorithm considering the minimum green time in COSMOS. In the case of a signalized intersection where two wide and narrow streets intersect each other, the time required for the pedestrian crossing is frequently longer than the time alloted to the through traffic on a minor street. In order to meet the minimum green time requirement for the pedestrian less time in alloted automatically to the left-turn traffic, creating heavy congestion on the left-turn approach. To solve this problem, this study suggests a new algorithm which shares the barrier using minimum green time and shares the burden with signal phases alloted to the crossing street traffic on the basis of the equal ratio of the degree of saturation, while maintaining the minimum green time requirement. The new algorithm was compared with the existing algorithm by using a microscopic simulation model for COSMOS evaluation developed at Ajou University. The simulation results show that the new algorithm produces better performance than the existing one.

• Journal of Korean Society of Transportation
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• v.22 no.2 s.73
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• pp.109-119
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• 2004

In COSMOS, an area for signal coordination is divided into subareas composed of several signalized intersections that share a common cycle time. Each subarea contains only one critical intersection having heavy traffic load. Subarea is a basic unit of control. The performance of COSMOS is highly dependent on the linkage rule between adjacent subareas. The purpose of this study is to provide an appropriate subarea linkage rule in COSMOS. This study developed a control strategy for Critical Intersection and Sub Area linkage. Critical Intersections calculate the Offset Pattern both East-West Axis and North-South Axis, and the coordination direction either East-West Axis or North-South Axis. Subarea can be combined with other one in all directions. The performance of the suggested linkage rule was evaluated on the real network in Gangnam-Gu. The result was that travel time was reduced by the suggested linkage rule.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.7-16
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• 2004

The homogeneous road section is defined as one consisted of similar traffic characteristics focused on demand and supply. The criteria, in the aspect of demand, are the diverging rate and the ratio of green time to cycle time at signalized intersection, and distance between the signalized intersections. The criteria, in that or supply, are the traffic patterns such as traffic volume and its speed. In this study, the effective method to generate valuable data, pointing out the problems of removal method of obscure data, is proposed using data collected from Gonjiam IC to Jangji IC on the national highway No.3. Travel times are collected with licence matching method and traffic volume and speed are collected from detectors. Futhermore, the method of selecting homogeneous road section is proposed considering demand and supply aspect simultaneously. This method using outlier filtering algorithm can be applied to generate the travel time forecasting model and to revise the obscured of missing data transmitting from detectors. The point and link data collected at the same time on the rational highway can be used as a basis predicting the travel time and revising the obscured data in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.101-111
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• 2017

This study propose a method to predict the bus arrival time by considering the signal delay time which is an element which can not be considered in the current bus arrival prediction information generation algorithm. In order to consider the signal delay time, travel time is divided into three components: service time, cruising travel time, and signal delay time. Signal delay time was estimated using intersection arrival time and TOD. The results show that most of the errors that occurred in predicting the arrival time are within about 30 seconds. Some of the estimates have large errors due to the nature of this methodology that uses the estimated value of the intersection arrival time rather than the observation value. It is also difficult to predict the arrival time of the express buses using this method. Future studies such as improving this through real-time location information will greatly improve the accuracy of the methodology.

• Journal of Korean Society of Transportation
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• v.31 no.5
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• pp.60-70
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• 2013

This study aims to develop a truck priority on left-turn algorithm that can reduce greenhouse gas emissions by reducing heavy duty truck's stops at signalized intersection. The signal priority is granted for a left-turn phase, because heavy duty trucks can deteriorate left-turn traffic flow due to the low acceleration or deceleration rate and large turn radius. Truck priority allows to provide the stable speed control for heavy duty truck, and reduces emissions at the signal intersection. Also, two signal recovery strategies are compared for various traffic conditions. This study analyzes the effectiveness of truck priority such as greenhouse gas emissions and fuel consumption reduction, and total travel time saving using the PARAMICS and Comprehensive Modal Emissions Model (CMEM). The results show that signal priority for heavy duty trucks has an effect on reducing greenhouse gas emissions and fuel consumptions at non-peak hour. Also, it shows decreasing total travel time due to reducing truck stops.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.1 s.2
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• pp.25-40
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• 2003

The purpose of this thesis is development of detection algorithm for stop-line detector. Detail detection area is set in basing detection area($1.8{\times}4.0m$) and traffic information(volume, occupancy, nonoccupancy) is collected by passive infrared detector at designing detection area. The basis detection area($1.8{\times}4.0m$) is named existing PIR and detection area applied on development algorithm is named proposal PIR. The proposal PIR is collected data such volume, occupancy, nonoccupancy, speed and lane change, but this thesis is limited to evaluate for volume, occupancy and nonoccupancy The procedure and each step of being developed algorithm is described in the next (1) The detection area of proposal PIR is made up of 2 of $1.8{\times}0.6m$ size(the detection area is named 1 and 3) and 1 of $1.8{\times}1.78m$ size(the detection area is named 2) (2) The image detection area is set on monitor to analyze outdoor photographing data then video frame analysis has been done by analyzer. (3) The occupancy, nonoccupancy and speed data of vehicle have been collected with the detection area 1 and 3 and lane change has been collected with combination of detection area 1, 2 and 3 The MAD and MAPE have been utilized to being compared with volume, occupancy and nonoccupancy for the field application and evaluation of a algorithm As the result, the proposal PIR data have been identified superior to the existing PIR data and the effect has been improved its information(volume, occupancy and nonoccupancy)