• Proceedings of the KAIS Fall Conference
• /
• 2003.11a
• /
• pp.236-242
• /
• 2003

ATM ABR service controls network traffic using feedback information on the network congestion situation in order to guarantee the demanded service qualities and the available cell rates. In this paper we apply the control method using queue length prediction to the formation of feedback information for more efficient ABR traffic control. If backward node receive the longer delayed feedback information on the impending congestion, the switch can be already congested from the uncontrolled arriving traffic and the fluctuation of queue length can be inefficiently high in the continuing time intervals. The feedback control method proposed in this paper predicts the queue length in the switch using the slope of queue length prediction function and queue length changes in time-series. The predicted congestion information is backward to the node. NLMS and neural network are used as the predictive control functions, and they are compared from performance on the queue length prediction. Simulation results show the efficiency of the proposed method compared to the feedback control method without the prediction. Therefore, we conclude that the efficient congestion and stability of the queue length controls are possible using the prediction scheme that can resolve the problems caused from the longer delays of the feedback information.

• Safety and Health at Work
• /
• v.10 no.2
• /
• pp.213-218
• /
• 2019

Background: Motorcycles are one of the important members of commercial transportation because of the convenient use during congested traffic conditions and the ease of parking in narrow streets. This study investigates the characteristics of crashes and traffic signal violations caused by motorcycle couriers. Methods: From the national compensation data, this study analyzed the traffic crashes caused by 671 motorcycle couriers. Results: Among 671 injured couriers, 50.6% were aged less than 40 years, 49.2% run in a small business of <5 employees, and 47.2% had work experience of <6 months. Motorcycle crashes occurred mainly due to "rider overturned alone" (67.5%), in the daytime (73.5%), or on cloudy or clear days (77.2%). However, the violation rate caused by motorcycle couriers was high in couriers in a small business of <5 employees (13.9%), with work experience of <6 months (13.9%), on cloudy or clear days (12.4%), on an intersection (29.8%), in the type of "crash with a vehicle" (31.2%), or in a death accident (35.7%) Conclusion: The findings of this study can be used as a baseline in devising policies for preventing crashes of motorcycle couriers.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.4 no.1 s.6
• /
• pp.43-56
• /
• 2005

This research has examined a time series analysis(TSA) of an every hour traffic information such as occupancy, a traffic flow, and a speed, a statistical model of a surveyed data on the traffic fundamental diagram and an expand aspect of a traffic jam by many Parts of the traffic flow. Based on the detected data from traffic accidents on the Cheonan-Nonsan high way and events when the road volume decreases dramatically like traffic accidents it can be estimated from the change of occupancy right after accidents. When it comes to a traffic jam like events the changing gap of the occupancy and the mean speed is gentle, in addition to a quickness and an accuracy of a detection by the time series analyse of simple traffic index is weak. When it is a stable flow a relationship between the occupancy and a flow is a linear, which explain a very high reliability. In contrast, a platoon form presented by a wide deviation about an ideal speed of drivers is difficult to express by a statical model in a relationship between the speed and occupancy, In this case the speed drops shifty at 6$\~$8$\%$ occupancy. In case of an unstable flow, it is difficult to adopt a statistical model because the formation-clearance Process of a traffic jam is analyzed in each parts. Taken the formation-clearance process of a traffic jam by 2 parts division into consideration the flow having an accident is transferred to a stopped flow and the occupancy increases dramatically. When the flow recovers from a sloped flow to a free flow the occupancy which has increased dramatically decrease gradually and then traffic flow increases according as the result analyzed traffic flow by the multi regime as time series. When it is on the traffic jam the traffic flow transfers from an impeded free flow to a congested flow and then a jammed flow which is complicated more than on the accidents and the gap of traffic volume in each traffic conditions about a same occupancy is generated huge. This research presents a need of a multi-regime division when analyzing a traffic flow and for the future it needs a fixed quantity division and model about each traffic regimes.

• Journal of Korean Society of Transportation
• /
• v.29 no.1
• /
• pp.71-79
• /
• 2011

Traditionally, a dynamic network model is considered as a tool for solving real-time traffic problems. One of useful and practical ways of using such models is to use it to produce and disseminate forecast travel time information so that the travelers can switch their routes from congested to less-congested or uncongested, which can enhance the performance of the network. This approach seems to be promising when the traffic congestion is severe, especially when sudden incidents happen. A consideration that should be given in implementing this method is that travel time information may affect the future traffic condition itself, creating undesirable side effects such as the over-reaction problem. Furthermore incorrect forecast travel time can make the information unreliable. In this paper, a network-wide travel time prediction model under incidents is developed. The model assumes that all drivers have access to detailed traffic information through personalized in-vehicle devices such as car navigation systems. Drivers are assumed to make their own travel choice based on the travel time information provided. A route-based stochastic variational inequality is formulated, which is used as a basic model for the travel time prediction. A diversion function is introduced to account for the motorists' willingness to divert. An inverse function of the diversion curve is derived to develop a variational inequality formulation for the travel time prediction model. Computational results illustrate the characteristics of the proposed model.

• Proceedings of the IEEK Conference
• /
• 2000.11a
• /
• pp.221-224
• /
• 2000

The issue of supporting TCP traffic over ATM networks is currently one of the most important issues in the field of data networks. One important part of this issue is congestion control. In general, congestion control uses method such as packet drop to relieve network resource when the network is congested so as to maintain high throughput and low delay. In addition, congestion control is required to ensure fair sharing of resources among all users during congestion. In this paper we propose a new congestion control method using WRED & per-VC accounting mechanism. This packet discard scheme is proposed with the goal to provide both good performance in terms of throughput and fairness in terms of bandwidth exploitation of the output link among all virtual circuits.

• Journal of Korean Society of Transportation
• /
• v.13 no.4
• /
• pp.79-103
• /
• 1995

The elasticity of a model is considered most important. Without showing the proper elasticity any model cannot provide useful information for decision making. This paper demonstrates a macro model which can generate dynamic transport informations every 15 minutes. Without the Wardrop principles and the monotonicity assumptions for the link travel time and link volume relationship, the basic elements of this new modeling approache are composed of link density simulation, stochastic incremental route choice, departure time choice, destination choice and mode choice. The elasticity of the proposed model is examined based on elasticity equations and simulation results. Also the transferability from a mega city like Seoul to a big city like Daejon is demonstrated for the choice model. The issues centering around the dynamic relations among density(k), speed(u), and flow rate(v) are also discussed for the modeling of highly congested situations.

• Journal of Korean Society of Transportation
• /
• v.8 no.1
• /
• pp.5-15
• /
• 1990

As a result of the lack of methodology for the determination of navigational channel capacity and the consequence lack of effective management of traffic, navigational channels are often grossly underutilized or highly congested. The traditional rule of first-come-first-served admission of vessels to channels is not efficient as it assumes equal time intervals between entrance of consecutive vessels. A new vessel traffic management system is developed in this research and methodologies to measure the improvement in the channel capacity are developed. Methodology to measure the channel performances for three queue disciplines are developed. The effects of changes in major factors on the channel capacity model such as channel length, fleet mix and arrival rate, as well as changes in strategy are analyzed. Under given channel conditions, best strategy are recommended. Also, a method for effective stochastic channel capacity simulation was developed. The results of analysis and as ertions are compared with the results of simulation runs to prove their applicability.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.1 no.1
• /
• pp.8-13
• /
• 2006

In mobile ad hoc networks, most of on demand routing protocols such as DSR and AODV do not deal with traffic load during the route discovery procedure. To achieve load balancing in networks, many protocols have been proposed. However, existing load balancing schemes do not consider the remaining available buffer size of the interface queue, which still results in buffer overflows by congestion in a certain node which has the least available buffer size in the route. To solve this problem, we propose a load balancing protocol called Dynamic Congestion Aware Routing Protocol (DCAR) which monitors the remaining buffer length of all nodes in routes and excludes a certain congested node during the route discovery procedure. We also propose two buffer threshold values to select an optimal route selection metric between the traffic load and the minimum hop count. Through simulation study, we compare DCAR with other on demand routing protocols and show that the proposed protocol is more efficient when a network is heavily loaded.

• Proceedings of the KIEE Conference
• /
• 1988.07a
• /
• pp.265-268
• /
• 1988

Several routing algorithms use the link lengths that reflect the traffic conditions on the links to route messages. The idea is to assign a large length to a congested link so that they will tend not to use it as part of a routing path. When these lengths depend on current traffic conditions, dynamic behavior such as stability, convergence and the speed of convergence are of interest. But it sometimes induces the possibility of violent oscillation. This paper is the one that analyze these issues systematically.

• International Journal of Computer Science & Network Security
• /
• v.22 no.3
• /
• pp.1-8
• /
• 2022

Supporting real-time flows with delay and throughput constraints is an important challenge for future wireless networks. In this paper, we develop an optimal scheduling scheme to optimally choose the packets to transmit. The optimal transmission strategy is based on an observable Markov decision process. The novelty of the work focuses on a priority-based probabilistic packet scheduling strategy for efficient packet transmission. This helps in providing guaranteed services to real time traffic in Heterogeneous Wireless Networks. The proposed scheduling mechanism is able to optimize the desired performance. The proposed scheduler improves the overall end-to-end delay, decreases the packet loss ratio, and reduces blocking probability even in the case of congested network.