• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.161-165
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• 2005

In order to produce an optimal traffic cycle. We must first check how many waiting cars are at the lower intersection, because waiting queue is bigger than the length of upper traffic intersection. Start up delay time and vehicle waiting time occurs. To reduce vehicle waiting time, in this paper, we present an optimal green time algorithm using fuzzy neural network. Through computer simulation has been proven to be improved average vehicle speed than fixed traffic signal light which do not consider different intersection conditions.

• KIEAE Journal
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• v.14 no.4
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• pp.27-33
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• 2014

This study analyzed the electric vehicle recharging station status with recharging time limitation due to long waiting time, and figured out the user status by user interviews. And then this study verified the validity of hypothesis in terms of environmental design perspective and suggested layout of recharging station model. 21 recharging stations in Korea and station operation cases of 7 countries were examined. Except for the USA, the reality of electric vehicle recharging station today is the 1st proving stage focusing on the infrastructure construction of electric vehicle recharging station. It focuses on performance of recharging facility, use efficiency and operation environment of electric vehicle. About the effective waiting time of the user to use it should be studied. The current conditions of recharging station are as follows: Lack of independent recharging space, lack of facility that reduces external effect of recharging space, and lack of lounge for users during the waiting time. These three are essential factors constructing a suggesting model after basic layout, which needs proper measurement on the long recharging time and long waiting time. The essential factors are applied to electric vehicle recharging station layout so that users might use 'digital refresh" i.e. lounge and information contents service during the waiting time which provides convenience of recharging and emotional space with users. Such upgrade recharging station environmental model might resolve the burden of long recharging time which may contribute to the popularization of electric vehicles.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.105-111
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• 2003

This paper is researching the storing of 40 different kinds of conditions. Such as, car speed, delay in starting time and the volume of cars in traffic. Through the use of a central nervous networking system or AI, using 10 different intersecting roads. We will improve the green traffic light. And allow more cars to easily flow through the intersections. Now days, with increasing many vehicles on restricted roads, the conventional traffic light creates prove startup-delay time and end-lag-time. The conventional traffic light loses the function of optimal cycle. And so, 30-45% of conventional traffic cycle is not matched to the present traffic cycle. In this paper proposes electro sensitive traffic light using fuzzy look up table method which will reduce the average vehicle waiting time and improve average vehicle speed. Computer simulation results prove that reducing the average vehicle waiting time which proposed considering passing vehicle length for optimal traffic cycle is better than fixed signal method which dosen't consider vehicle length.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.4
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• pp.330-337
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• 2000

This paper proposes a new concept of coordinating green this which controls 10 traffic intersection systems. For instance, if we have a baseballs game at 8 pm today, traffic volume toward the baseball game at 8 pm today, traffic volume toward the baseball game will be incr eased 1 hour or 1 hour 30 minutes before the baseball game. at that time we can not pred ict optimal green time Even though there have smart elctrosensitive traffic light system. Therefore, in this paper to improve average vehicle speed and reduce average vehicle waiting time, we created optimal green time using fuzzy rules and neural network. Computer simulation results proved reducing average vehicle waiting time proposed coordinating green time better than electro-sensitive traffic light system. Therefore, in this paper to improvevehicle speed and reduce average vehicle waiting time, we created optiual green time fuzzy rules and neural network. Computer simulation results proved reducing average vehicle waiting time which proposed coordinating green time better than electro-sensitive traffic light system dosen't consider coordinating green time.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.3
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• pp.256-263
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• 2002

This paper addresses a planning problem in a pickup-delivery transportation' system under dynamic vehicle dispatching. We present a procedure to determine a fleet size in which stochastic characteristics of vehicle travels are considered. Statistical approach and queueing theory are applied to estimate vehicle travel time and vehicle waiting time, based on which an appropriate fleet size is determined. Simulation experiments are performed to verify the proposed procedure.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.279-282
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• 2001

This paper is concerned with Vehicle Routing Problem to minimize the total delivery waiting time of customers. The delivery waiting time is the time taken to travel from the depot to the customer, which is important for the delivery of the perishing products or foods requiring freshness. We construct a mixed integer linear programming formulation of this problem, and CR(Clustering first Routing second) heuristic and SPH(set partitioning heuristic) are suggested. the results of computational experiments showed that these heuristics find successfully favorable solutions, in much shorter time than optimal.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.1
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• pp.59-64
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• 2020

Scheduling of electric vehicles and optimizing for charging waiting time have been critical. Meanwhile, it is challengeable to exploit the fluctuating data from electric vehicles in real-time. We introduce an optimal routing algorithm and a simulator with electric vehicles obeying the Poisson distribution of the observed information about time, space and energy-demand. Electric vehicle routing is updated in every cycle even it is already set. Also, we suggest an electric vehicle routing algorithm for minimizing total trip time, considering a threshold of the waiting time. Total trip time and charging waiting time are decreased 34.3% and 86.4% respectively, compared to the previous algorithm. It can be applied to the information service of charging stations and utilized as a reservation service.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.8
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• pp.88-100
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• 1997

This paper proposes a new concept for an optimal traffic signal cycle method which will reduce the average vehicle waiting time and improve average vehicle speed. Electro sensitive traffic system can extend the traffic cycle when there ar emany vehicles in the road or it can reduce the traffic consider vehicle length, so it can cause oveflow and reduce average vechicel waiting time at the intersection, we propose on optimal traffic cycle with fuzzy ruels and neural network. Computer simulation results prove that reducing the average vehicle waiting time which proposed considering passing vehicle's length for the optimal traffic cycle better than fixe dsignal method dosen't consider vehicle length.

• Journal of information and communication convergence engineering
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• v.18 no.3
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• pp.147-154
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• 2020

In this study, we created a system that can determine the number of vehicles entering and departing a charging station in real time for solving waiting time problems during refueling. Accordingly, we use the You Only Look Once object detection algorithm to detect and count the number of vehicles in the charging station and send the data to the Firebase Realtime Database. The result is shown using an Android application that provides a map function with the Kakao Maps API at the user interface side. Our system has an accuracy of 91% and an average response time of 3.1 s. Therefore, this system can be used by drivers to determine the availability of a charging station and to identify the charging station with the least waiting time for charging their vehicle.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.591-595
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• 1998

This paper proposes a new concept of optimal shortest path algorithm which reduce average vehicle wating time and improve average vehicle speed, Electro sensitive traffic system can extend the traffic cycle when three are many vehicles on the road or it can reduce the traffic cycle when there are small vehicles on the road. But electro sensitive traffic light system doesn't control that kind of function when the average vehicle speed is 10km -20km. Therefore, in this paper to reduce vehicle waiting time we developed design of traffic cycle software tool that can arrive destinination as soon as possible using optimal shortest pass algorithm. Computer simulation result proved 10%-32% reducing average vehicle wating time and average vehicle speed which can select shortest route using built in G.P.S. vehicle is better than not being able to select shortest route function.