• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.113-124
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• 2009

This paper suggests a new approach for providing information for driver safety at signalized intersections. Particularly dangerous situations at signalized intersections such as red-light violations, accelerating through yellow intervals, red-light running, and stopping abruptly due to the dilemma zone problem are considered in this study. This paper presents the development of a dangerous vehicle determination algorithm by collecting real-time vehicle speeds and times from multiple point detectors when the vehicles are traveling during phase-change. For an evaluation of this algorithm, VISSIM is used to perform a real-time multiple detection situation by changing the input data such as various inflow-volume, design speed change, driver perception, and response time. As a result the correct-classification rate is approximately 98.5% and the prediction rate of the algorithm is approximately 88.5%. This paper shows the sensitivity results by changing the input data. This result showed that the new approach can be used to improve safety for signalized intersections.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.3
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• pp.59-71
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• 2018

This study was initiated to develop an optimal signal control algorithm for coordinated signalized intersections using individual vehicle's information which can be collected in a format of prove vehicle data (PVD) via V2I (Vehicle to Infrastructure) communication environment. For developing this signal optimization algorithm, three modules were developed for phase group length computation, split distribution, and phase sequence assignment. The simulation analysis using the microscopic simulation model, Vissim, was conducted for evaluating the effectiveness of the developed algorithm. The analysis result represented that the performance of the developed algorithm is far superior to that of the fixed coordinated signal control method which is the most common signal control method for coordinated signalized intersections in Korea.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4D
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• pp.351-360
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• 2010

In 2010, the number of registered vehicles reached almost at 17.48 millions in Korea. This dramatic increase of vehicles influenced to increase the number of traffic accidents which is one of the serious social problems and also to soar the personal and economic losses in Korea. Through this research, an enhanced intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network will be developed in order to obtain the important data for developing the countermeasures of traffic accidents and eventually to reduce the traffic accidents in Korea. Firstly, this research has investigated the influencing factors of road geometric features on the traffic volume of each approaching for the intersections where traffic accidents and congestions frequently take place and, a linear regression model of traffic accidents and traffic conflicts were developed by examining the relationship between traffic accidents and traffic conflicts through the statistical significance tests. Secondly, this research also developed an intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network through applying the intersection traffic volume, the road geometric features and the specific variables of traffic conflicts. Lastly, this research found out that the developed model is better than the existed forecasting models in terms of the reliability and accuracy by comparing the actual number of traffic accidents and the predicted number of accidents from the developed model. In conclusion, it is expect that the cost/effectiveness of any traffic safety improvement projects can be maximized if this developed intersection hazard prediction model by combining Genetic Algorithm and Artificial Neural Network use practically at field in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.182-195
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• 2023

Recently, research on traffic signal control using artificial intelligence algorithms has been receiving attention, and many traffic signal control models are being studied. However, most studies either focused on independent intersections or are theoretical studies that calculate signal cycle length according to changes in traffic volume. Therefore, this study was conducted on a signalized intersection - roundabout in Gajwa-ro. The Particle Swarm Optimization - Bacterial Foraging Optimization (PSO-BFO) algorithm was proposed, which is developed from the GA and PSO algorithms for minimizing congestion at two intersections. As a result, optimum cycle length was determined to be 158 seconds. The Verkehr In Stadten - SIMulationsmodell (VISSIM) results showed that there was 3.4% increased capacity, 8.2% reduced delay and 8.3% reduced number of stops at the Gajwa-ro signalized intersection. Additionally, at the roundabout, a 9.2% increase in capacity, a 7.1% reduction in delay, and a 27.2% decrease in the number of stops was observed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.6
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• pp.62-70
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• 2016

Increased bus traffic leads inefficiency at near-side bus stops in median exclusive bus lane because buses are waiting for a signal does not have a vehicle arrived. This study suggests a method for estimating a proper spacing between bus stops and signalized intersection to prevent the inefficiency. We modified the Poisson model for a proper spacing by using both dwell time and waiting time of signal instead of using dwell time only. The waiting time of signal changes by spacing and it was measured using micro simulation program. The iterative algorithm using the change of waiting time of signal was also suggested. By applying the proposed method, measure waiting time by simulation and iterative algorithm, the spacing of near-side bus stops, proper spacing is suggested according to flow rate level.

• 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.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.97-111
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• 2009

Image-based traffic information collection systems have entered widespread adoption and use in many countries since these systems are not only capable of replacing existing loop-based detectors which have limitations in management and administration, but are also capable of providing and managing a wide variety of traffic related information. In addition, these systems are expanding rapidly in terms of purpose and scope of use. Currently, the utilization of image processing technology in the field of traffic accident management is limited to installing surveillance cameras on locations where traffic accidents are expected to occur and digitalizing of recorded data. Accurately recording the sequence of situations around a traffic accident in a signal intersection and then objectively and clearly analyzing how such accident occurred is more urgent and important than anything else in resolving a traffic accident. Therefore, in this research, we intend to present a technology capable of overcoming problems in which advanced existing technologies exhibited limitations in handling real-time due to large data capacity such as object separation of vehicles and tracking, which pose difficulties due to environmental diversities and changes at a signal intersection with complex traffic situations, as pointed out by many past researches while presenting and implementing an active and environmentally adaptive methodology capable of effectively reducing false detection situations which frequently occur even with the Gaussian complex model analytical method which has been considered the best among well-known environmental obstacle reduction methods. To prove that the technology developed by this research has performance advantage over existing automatic traffic accident recording systems, a test was performed by entering image data from an actually operating crossroad online in real-time. The test results were compared with the performance of other existing technologies.

• Journal of the Korean Society of Industry Convergence
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• v.4 no.1
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• pp.41-49
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• 2001

This study developed signal optimization algorithm by analyzing vehicle arrival patterns. The major principle of signal optimization is dissipate all queueing vehicle in 1cycle and assign delay time uniformly for all approaches. For this, this study used optimal green time and surplus green time. Optimal green time calculated by estimated traffic volume from vehicle arrival model. Surplus green time defined as the gap of optimal green time and queue dissipated time. And alternative cycle has minimum surplus green time was selected as the optimal cycle. Finally, total delay and average delay per vehicle can be calculated by using queueing theory.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.3
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• pp.12-19
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• 2010

In road network, especially in urban area, inefficiency of travel time is caused by signal control and turn maneuver at intersection and this inefficiency has substantial effects on travel time. When searching for the shortest path, this inefficiency which is caused by turn maneuver must be considered. Therefore, travel time, vehicle volume and delay for each link were calculated by using simulation package, PARAMICS V5.2 for adaptation of turn penalty at 16 intersections of Gangnam-gu. Turn penalty was calculated respectively for each intersection. Within the same intersection, turn penalty differs by each approaching road and turn direction so the delay was calculated for each approaching road and turn direction. Shortest path dealing with 16 intersections searched by Dijkstra algorithm using travel time as cost, considering random turn penalty, and algorithm considering calculated turn penalty was compared and analyzed. The result shows that by considering turn penalty searching the shortest path can decrease the travel time can be decreased. Also, searching the shortest path which considers turn penalty can represent reality appropriately and the shortest path considering turn penalty can be utilized as an alternative.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.2
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• pp.113-127
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• 2018

This study develops a fusion priority signal control algorithm to pass without delay in emergency events. Fusion priority signal control is method combined center control with local control. The center control method 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. However, since the traffic information (speed, position) of the real-time emergency vehicle is not used, the intersection arrival time predicted by center control and actual arrival time of the emergency vehicle may be different from each other. In the case, it is possible to experience a delay caused by the signal. Local control method operate priority signal use the real-time information of EV, but there is a limitation that queue elimination time can not be reflected. In this study, fusion(center+local) control algorithm is proposed to compensate the disadvantages of center and local control also maximizing its advantages. Proposed algorithm is expected to decrease delay time of EV in emergency situation.