• Title/Summary/Keyword: Waiting vehicle

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A study on the Spacing between Near-side Bus Stops and Signalized Intersection in Median Exclusive Bus Lane (중앙버스전용차로 근측정류장과 신호교차로의 이격거리 산정에 관한 연구)

  • Choi, Yoon-Young;Kang, Wonmo;Ha, Dongik;Kho, Seung-Young
    • 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.

Forecasting of Real Time Traffic Situation using Neural Network and Sensor Database Management System (신경망과데이터베이스 관리시스템을 이용한 실시간 교통상황 예보)

  • Jin, Hyun-Soo
    • Proceedings of the KAIS Fall Conference
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    • 2008.05a
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    • pp.248-250
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    • 2008
  • This paper proposes a prediction method to prevent traffic accident and reduce to vehicle waiting time using neural network. Computer simulation results proved reducing average vehicle waiting time which proposed coordinating green time better than electro-sensitive traffic light system dose not consider coordinating green time. Moreover, we present neural network approach for traffic accident prediction with unnormalized (actual or original collected) data. This approach is not consider the maximum value of data and possible use the network without normalizing but the predictive accuracy is better. Also, the unnormalized method shows better predictive accuracy than the normalized method given by maximum value. Therefore, we can make the best use of this model in software reliability prediction using unnormalized data. Computer simulation results proved reducing traffic accident waiting time which proposed neural network better than conventional system dosen't consider neural network.

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Models for Determining the Vehicle and Pedestrian Volumes for the installation of Pedestrian Pushbuttons (보행자 작동신호기 설치기준 정립을 위한 적정 차량 및 보행자 교통량 추정모형)

  • YOON, Seung Sup;YANG, Jae Ho;KIM, Nam Seok
    • Journal of Korean Society of Transportation
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    • v.33 no.5
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    • pp.488-496
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    • 2015
  • The main reason to install pedestrian pushbuttons is improving traffic operations. The current guideline for the installation of signal systems with pedestrian pushbuttons is car-oriented. It is difficult to clearly understand the guideline because there isn't an in-depth study to compare the pros and cons of the pedestrian- and vehicle-oriented methods in terms of waiting time. Thus, this study aims to estimate the waiting times of pedestrians and vehicles. The two delay times are compared considering the hypothetical circumstances such as geometry, pedestrian crossing time, pedestrian/vehicle counts and arrival distribution. The results show that when the pedestrian traffic volume exceeds 97 ped/h in the case of a two-lane road (one lane in each direction) the pushbutton system is effective and beneficial to pedestrians. It means that the total waiting time of pedestrians is less than the one of vehicles. Additional four scenarios are designed and tested by varying the number of lanes and design speeds. In conclusion, the pushbutton signal is more beneficial for pedestrians when the number of pedestrians is less than or equal to 85, 70, and 70 ped/h for the three-lane scenario, the four-lane with the design speed of 80km/h scenario, and the four-lane with the design speed of 100km/h, respectively.

A Study of Vehicle Operation Policy in Warehouse (창고에서의 이송장비 운영정책에 관한 연구)

  • Lee, Hue-On;Chae, Jun-Jae;Lee, Moon-Su
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.34 no.1
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    • pp.1-8
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    • 2011
  • Controlling industrial vehicle operated by human in warehouse was not simple since the information transfer for controlling the vehicle was not easy. However, as the technology for the WMS (Warehouse Management System) has been advanced and the PDA (Personal Digital Assistant) has come into wide use in a workplace, the control of man-operated vehicle became less difficult as do to AGVS (Automated Guided Vehicle System). This study examines the ways to improve the efficiency of warehouse operation through introducing rule of task assignment for the vehicles, particularly forklift. This study, basically, refer to AGV operation policy because a great number of studies for AGV dispatching rule have been done and the mechanism for the controlling vehicles is very similar. The workers in field prefer to simple dispatching rules such as Shortest Retrieval Time First (SRTF), Shortest Travel Time First (STTF), and Longest Waiting Time First (LWTF). However, these rules have potential disadvantage. Thus, several rules made up by combining rules mentioned above are introduced and these new rules use threshold value or evaluation formula. The effectiveness of these new rules are tested by simulation and the results are compared. This study proposes favorable dispatching rules for forklift in warehouse for the efficiency of the vehicle operation and stability of service level.

A Multi-attribute Dispatching Rule Using A Neural Network for An Automated Guided Vehicle (신경망을 이용한 무인운반차의 다요소배송규칙)

  • 정병호
    • Journal of the Korea Society for Simulation
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    • v.9 no.3
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    • pp.77-89
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    • 2000
  • This paper suggests a multi-attribute dispatching rule for an automated guided vehicle(AGV). The attributes to be considered are the number of queues in outgoing buffers of workstations, distance between an idle AGV and a workstation with a job waiting for the service of vehicle, and the number of queues in input buffers of the destination workstation of a job. The suggested rule is based on the simple additive weighting method using a normalized score for each attribute. A neural network approach is applied to obtain an appropriate weight vector of attributes based on the current status of the manufacturing system. Backpropagation algorithm is used to train the neural network model. The proposed dispatching rules and some single attribute rules are compared and analyzed by simulation technique. A number of simulation runs are executed under different experimental conditions to compare the several performance measures of the suggested rules and some existing single attribute dispatching rules each other.

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Optimal Traffic Information (최적교통정보)

  • 홍유식;최명복;박종국
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2002.12a
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    • pp.399-405
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    • 2002
  • Now days, it is based on GIS and GPS, it can search for the shortest path and estimation of arrival time by using the internet and cell phone to driver. But, even though good car navigation system does not create which is the shortest path when there average vehicle speed is 10 -20 Km. Therefore In order to reduce vehicle waiting time and average vehicle speed, we suggest optimal green time algorithm using fuzzy adaptive control , where there are different traffic intersection length and lane. In this paper, it will be able to forecast the optimal traffic Information, estimation of destination arrival time, under construction road, and dangerous road using internet.

Forecasting of Real Time Traffic Situation by Fuzzy and Intelligent Software Programmable Logic Controller (퍼지 및 지능적 PLC에 의한 실시간 교통상황 예보 시스템)

  • 홍유식;조영임
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.41 no.4
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    • pp.73-83
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    • 2004
  • With increasing numbers of vehicles on restricted roads, It happens that we have much wasted time and decreased average car speed. This paper proposes a new concept of coordinating green time which controls 10 traffic intersection systems. For instance, if we have a baseball game at 8 pm today, traffic volume toward the baseball game at 8 pm today, franc volume toward the baseball game will be increased 1 hour or 1 hour and 30 minutes before the baseball game. At that time we can not predict optimal green time Even though there have smart electro-sensitive 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 md neural network as a preprocessing. Also, we developed an Intelligent PLC(Programmable Logic Controller) for real time traffic forecasting as a postprocesing about unexpectable conditions. Computer simulation results proved reducing average vehicle waiting time which proposed coordinating green time better than electro-sensitive franc light system does not consider coordinating green time.

Development of Gap Acceptance Models for Permitted Left Turn Intersections (비보호좌회전에서의 간격수락 행태모형 개발)

  • Lee, Chung Won;Lee, Dong Min;Hwang, Soon Cheon
    • International Journal of Highway Engineering
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    • v.18 no.5
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    • pp.95-103
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    • 2016
  • PURPOSES : Permitted left turn is a turning maneuver in which a vehicle turns left using a gap between oncoming vehicles, called gap acceptance, and it enables for more efficient traffic operation at intersections. In Korea, the permitted left turn has not been a common maneuver at signalized or un-signalized intersections. However, many experts and the Police Agency tried to apply this effective turning maneuver at intersections in Korea since 2010. Though the investigation of gap acceptance is significantly important in understanding a driver's behavior at intersections, there have not been many studies about this topic, specifically a study to develop probability models of gap acceptance behavior. METHODS : In this study, the probability model of gap acceptance behavior for a permitted left turn was developed based on observational field studies. To develop the model, seven variables were analyzed including gap, waiting time, traffic volume, conflict-flow vehicle type, left-turning vehicle type, the number of lane, and time. RESULTS : In the final model, gap and left-turning vehicle type were found to be significant influencing factors. CONCLUSIONS : Through this model development, it was concluded that as the gap size increased, the probability of gap acceptance was higher. Moreover, when a left-turning vehicle was a passenger car, the probability of gap acceptance was higher than compared to large size buses or freight cars.

A Study on the Safety for Pedestrians Waiting for Signal (보행신호를 대기하는 보행자의 안전에 관한 연구)

  • Kim, Hansol;Baek, Seryong;Choi, Yongsoon;Yoon, Junkyu;Lim, Jonghan
    • Journal of Auto-vehicle Safety Association
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    • v.13 no.3
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    • pp.41-46
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    • 2021
  • The number of big traffic accident cases of pedestrian death appeared to be minor, however compared to death rate in car to car accidents is very high and quite a few of the pedestrian death rates among all traffic accidents are counted to be almost 40%. Previous pedestrian safety studies were mostly aimed at reducing the degree of pedestrian injuries from a vehicle to pedestrian collision, and less at preventing a collision itself. This research was conducted with a method of using road facilities to prevent vehicles from rushing into the sidewalk. This research used one of the collision analyzing programs, called PC-Crash to simulate the vehicle rushing into the sidewalk. Based on the program, it could derive an optimal safe zone location where the pedestrian can wait for the pedestrian light safely. Also, changing road facilities such as pedestrian light pillars or signal controllers can widen 440% compared to the present safe zone. Accordingly, researchers have to consider a method to analyze and apply pedestrian safe zones along with road facilities location when designing a road.

Traffic Congestion Management on Urban Roads using Vehicular Ad-hoc Network-based V2V and V2I Communications (차량 애드혹 네트워크 기반 V2V와 V2I 통신을 사용한 시내 도로에서의 교통 체증 관리)

  • Ryu, Minwoo;Cha, Si-Ho
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.18 no.2
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    • pp.9-16
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    • 2022
  • The nodes constituting the vehicle ad hoc network (VANET) are vehicles moving along the road and road side units (RSUs) installed around the road. The vehicle ad hoc network is used to collect the status, speed, and location information of vehicles driving on the road, and to communicate with vehicles, vehicles, and RSUs. Today, as the number of vehicles continues to increase, urban roads are suffering from traffic jams, which cause various problems such as time, fuel, and the environment. In this paper, we propose a method to solve traffic congestion problems on urban roads and demonstrate that the method can be applied to solve traffic congestion problems through performance evaluation using two typical protocols of vehicle ad hoc networks, AODV and GPSR. The performance evaluation used ns-2 simulator, and the average number of traffic jams and the waiting time due to the average traffic congestion were measured. Through this, we demonstrate that the vehicle ad hoc-based traffic congestion management technique proposed in this paper can be applied to urban roads in smart cities.