• Journal of IKEEE
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• v.23 no.4
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• pp.1381-1386
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• 2019

As traffic congestion in cities becomes more serious, intelligent traffic control is actively being researched. Reinforcement learning is the most actively used algorithm for traffic signal control, and recently Deep reinforcement learning has attracted attention of researchers. Extended versions of deep reinforcement learning have been emerged as deep reinforcement learning algorithm showed high performance in various fields. However, most of the existing traffic signal control were studied in a single intersection environment, and there is a limitation that the method at a single intersection does not consider the traffic conditions of the entire city. In this paper, we propose a cooperative traffic control at multi-intersection environment. The traffic signal control algorithm is based on a combination of extended versions of deep reinforcement learning and we considers traffic conditions of adjacent intersections. In the experiment, we compare the proposed algorithm with the existing deep reinforcement learning algorithm, and further demonstrate the high performance of our model with and without cooperative method.

• Journal of Korean Society of Transportation
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• v.21 no.2
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• pp.83-94
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• 2003

Many cities, recently, have convertedoptimized fixed-time control to adaptive traffic system in the control of their signalized traffic network. The expected benefit from the adaptive traffic system is its ability to constantly modify signal timing to most effectively accommodate changed traffic conditions. While the potential benefits from this control structure may be significant, few studies have compared the effect of implementing this method of signal control against other alternative signal control strategies, because it is too difficult to evaluate the efficiency of the real-time adaptive system. The objectives of this research are : to develop a microscopic simulator and to compare the effect at isolated intersections, corridors, and networks between the fixed signal timing plan and adaptive traffic signal system. This simulator will have allowed more sophisticated analysis techniques for the study of traffic control. Also, this research using this simulator evaluated a real-time traffic responsive signal system used in Seoul Korea

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.66-66
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• 2000

In this parer, we introduce an algorithm to control flows of the traffic in multi-intersections. It is pointed out that the main problem in traffic control is how to resolve the congested situations for the particular time-durations and directions. The heavy load to a certain direction usually leads the intersection to congested situations, and the adjacent intersections are affected. We control and analyze the traffic flow of multi-intersections consisting of five intersections, in which four intersections are linked to the four directions of the central one. The entrance of vehicles of each direction is described using the concept of probability. We compare the performance of the pretimed signal controls to the traffic adaptive signal controller using a Petri Net simulation tool, Exspect.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.251-257
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• 2003

In this paper, we wish to construct a optimal traffic cycle using wire remote control. if police vehicle or ambulance suddenly enter the traffic Intersection, it will increase the traffic accident. In this paper, wireless traffic light use the radio traffic control signal and research about the hardware manufacture to check special detectors on urgency vehicles may safety and rapidly enter traffic intersection. Also, this paper present a traffic signal control conditions that analyzes different traffic intersection flows in cases of saturated flows, where the real traffic volume demand is large and the capacity constraints of bottlenecks have significant effects on the flow patterns. Through computer simulation this wireless traffic light has been proven to be much more safety and efficient than fixed traffic signal light which does not consider emergency vehicles for safety escort.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.671-680
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• 2016

This research suggested a new real-time traffic signal control algorithm using fusion data of the travel time and the occupancy rate. This research applied the travel time data of traffic information system to traffic signal operation, and developed the signal control process using the degree of saturation that was estimated from the travel time data. This algorithm estimates a queue length from the travel time based on a deterministic delay model, and includes the process to change from the queue length to the degree of saturation. In addition, this model can calculate the traffic signal timings using fusion data of the travel time and the occupancy rate based on the saturation degree. The micro simulation analysis was conducted for effectiveness evaluation. We checked that the average delay decreased by up to 27 percent. In addition, we checked that this signal control algorithm could respond to a traffic condition of oversaturation and detector breakdown effectively and usefully. This research has important contribution to apply the traffic information system to traffic signal operation sectors.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.735-738
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• 1997

The traffic congestion caused by the exploding increase of vehicles became one of the severest social problems. Among the various approaches to solve this problem, controlling the length of traffic signals appropriately according to the individual traffic situation would be the most plausible and cost-effective method. To design a traffic signal controller which has such a property as adaptive decision-making process, we adopt fuzzy logic control method(fuzzy traffic signal controller), Moreover, using genetic algorithms we obtain an optimized fuzzy traffic signal controller (GA-fuzzy traffic signal controller). To evaluate and validate the proposed fuzzy and GA-fuzzy traffic signal controller, simulation results are presented.

• Journal of the Korea Society for Simulation
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• v.14 no.3
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• pp.79-90
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• 2005

There are plenty of optimization models for the signal-system of a single intersection and area traffic. Some of those models are adopted for the real traffic signal control system. The simulators for a single crossroad have been developed, so that we could evaluate optimization models and traffic control systems. However, the simulators for the area traffic are still being developed. Therefore, there are many limitations in the analysis and evaluation for area traffic control system. The area traffic is consisted of several intersections which are very complicated and many traffic strategies are adopted for the control system. This paper features an effective area traffic control system based on the High Lever Architecture(HLA). In this paper, we discuss the design of HLA-based area traffic control simulation. We describe technical motivations for the HLA, the key elements of the architecture and how they are minimum and essential to the goal of reuse and interoperability. A distributed simulation with HLA/RTI provides stable and satisfactory experimental results. Moreover, the prototype traffic control system provides reliable accomplishment compared to the NETSIM and TRANSYT-7F models.

• Journal of information and communication convergence engineering
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• v.11 no.1
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• pp.30-44
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• 2013

Traffic congestion has become a serious problem with the recent exponential increase in the number of vehicles. In urban areas, almost all traffic congestion occurs at intersections. One of the ways to solve this problem is road expansion, but it is difficult to realize in urban areas because of the high cost and long construction period. In such cases, traffic signal control is a reasonable method for reducing traffic jams. In an actual situation, the traffic flow changes randomly and its randomness makes the control of traffic signals difficult. A prediction of traffic jams is, therefore, necessary and effective for reducing traffic jams. In addition, an autonomous distributed (stand-alone) point control of each traffic light individually is better than the wide and/or line control of traffic lights from the perspective of real-time control. This paper describes a stochastic optimum control of crossroads and multi-way traffic signals. First, a stochastic model of traffic flows and traffic jams is constructed by using a Bayesian network. Secondly, the probabilistic distributions of the traffic flows are estimated by using a cellular automaton, and then the probabilistic distributions of traffic jams are predicted. Thirdly, optimum traffic signals of crossroads and multi-way intersection are searched by using a modified particle swarm optimization algorithm to realize real-time traffic control. Finally, simulations are carried out to confirm the effectiveness of the real-time stochastic optimum control of traffic signals.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.5
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• pp.84-92
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• 2006

Freeway Corridors consist of urban freeways and parallel arterials that drivers can use alternatively. Ramp metering in freeways and signal control in arterials are contemporary traffic control methods that have been developed and applied in order to improve traffic conditions of freeway corridors. However, most of the existing studies have focused on either optimal ramp metering in freeways, or progression signal strategies between arterial intersections. There have been no traffic control systems in Korea that integrates the freeway ramp metering and arterial signal control. The effective control strategies for freeway operations may cause negative effects on arterial traffic. On the other hand, traffic congestion and bottleneck phenomenon of arterials due to the increasing peak-hour travel demand and ineffective signal operation may generate an accessibility problem to freeway ramps. Thus, the main function of the freeway which is the through-traffic process has not been successful. The purpose of this study is to develop an integrated control model that connects freeway ramp metering systems and signal control systems in arterial intersections. And Optimization of integrated control model which consists of ramp metering and signal control is another purpose. Optimization results are verified by comparison with the results from MATDYMO.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.1
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• pp.8-15
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• 2007

Freeway corridors consist of urban freeways and parallel arterials that drivers can use alternatively. Ramp metering in freeways and signal control in arterials are contemporary traffic control methods that have been developed and applied in order to improve traffic conditions of freeway corridors. However, most of the existing studies have focused on either optimal ramp metering in freeways, or progression signal strategies between arterial intersections. There have been no traffic control systems in Korea that integrates the freeway ramp metering and arterial signal control. The effective control strategies for freeway operations may cause negative effects on arterial traffic. On the other hand, traffic congestion and bottleneck phenomenon of arterials due to the increasing peak-hour travel demand and ineffective signal operation may generate an accessibility problem to freeway ramps. Thus, the main function of the freeway which is the through-traffic process has not been successful. The purpose of this study is to develop an integrated control model that connects freeway ramp metering systems and signal control systems in arterial intersections. And Optimization of integrated control model which consists of ramp metering and signal control is another purpose. The design of experiment, neural network, and simulated annealing are used for optimization.