• Journal of Korean Society for Geospatial Information Science
• /
• v.4 no.2 s.8
• /
• pp.91-98
• /
• 1996

Transportation impact assessment which can take precaution for the traffic problem to control a plan on to expand traffic facilities through these results analyzed with the business for making a big problem of traffic is a very important course on the traffic management system as well as the traffic plan and it is necessary to collect and to edit and to analyze a great deal of data fully in object zone. So it is worth while to treat the collected data on to computer. Therefore Geographic Information System will give a remarkable result to Traffic Influence Evaluation everywhere. GIS not only can join the graphic or attribute data correctly and fast, but can achieve it prominent function for intention decision means. Then total system for Landuse of surrounding district, development-plan state, traffic-facility state, traffic-development public plan state and traffic demand is animated on Traffic Influence Evolution.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10a
• /
• pp.32-35
• /
• 1996

Traffic signal cycle optimization is one of the most efficient ways for reducing fuel consumption and improving vehicle waiting time of highsaturated traffic conditions. But most research focused on lowsaturated traffic conditions. Only a few studies have researched traffic control for highsaturated traffic conditions. In this paper reviews the problem of conventional traffic signal system and creates optimal traffic cycle of at the bottom traffic intersection using 27 fuzzy rules. Moreover, to prevent spillback, it can adapt control even though upper traffic intersection has a different saturation rate, road length, road slope and road width.

• Proceedings of the KIEE Conference
• /
• 1997.07b
• /
• pp.735-738
• /
• 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 KIISE
• /
• v.42 no.1
• /
• pp.114-121
• /
• 2015

Large-scale wireless sensor networks are constructed by using a large number of sensor nodes that are non-uniformly deployed over a wide area. As a result, the data collected by the sensor nodes are similar to that from one another since a high density of the sensor nodes may cause an overlap. As a result of the characteristics of the traffic, data is collected from a plurality of sensor nodes by a sink node, and when the sensor nodes transmit their collected data to the sink node, the sensor nodes around the sink node have a higher amount of traffic than the sensor nodes far away from the sink node. Thus, the former sensor encounter bottlenecks due to traffic congestion and have an energy hole problem more often than the latter ones, increasing energy consumption. This paper proposes a congestion control scheme that considers traffic flows in order to control traffic congestion of the sensor nodes that are non-uniformly deployed over a large-scale wireless sensor network.

• Journal of Korean Society of Transportation
• /
• v.28 no.5
• /
• pp.107-116
• /
• 2010

The vehicle travel time between locations in a downtown is greatly influenced by both complex road conditions and traffic situation that changes real time according to various external variables. The customer's demands also stochastically change by time period. Most vehicle routing problems suggest a vehicle route considering travel distance, average vehicle speed, and deterministic demand; however, they do not consider the dynamic external environment, including items such as traffic conditions and stochastic demand. A realistic vehicle routing problem which considers traffic (smooth, delaying, and stagnating) and stochastic demands is suggested in this study. A mathematical programming model and hybrid genetic algorithm are suggested to minimize the total travel time. By comparing the results considering traffic and stochastic demands, the suggested algorithm gives a better solution than existing algorithms.

• Journal of Korean Society for Geospatial Information Science
• /
• v.3 no.1 s.5
• /
• pp.91-104
• /
• 1995

The spatial aggregation of data, in transportation and other planning processes, is an important theoretical consideration because the results of any analysis are not entirely independent of the delineation of zones. Moreover, using a different spatial aggregation may lead to different, and sometimes contradictory conclusions. Two criteria have been considered as important in designing zone systems. They are scale and aggregation. The scale problem arises because of uncertainty about the number of zones needed for a study and the aggregation problem arises because of uncertainty about how the data are to be aggregated to from a given scale problem. In a transportation study, especially in the design of traffic analysis zone(TAZ), the scale problem is directly related to the number dof zones and the aggregation problem involves spatial clustering, meeting the general requirements of forming the zones system such as equal traffic generation, convexity, and the consistency with the political boundary. In this study, first, the comparative study of delineating spatial units has been given. Second, a FORTRAN-based heuristic algorithm for designing TAZ based on socio-economic data has been developed and applied to the Korean peninsula containing 132 micro parcels. The vector type ARC/INFO GIS topological data mosel has been used to provise the adjacency information between parcels. The results, however, leave some to be desired in order to overcome such problems as non-convexity of the agglomerated TAZ system and/or uneven traffic phenomenon for each TAZ.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.3 no.4
• /
• pp.344-365
• /
• 2009

The performance of a tracking system is greatly increased if multiple types of sensors are combined to achieve the objective of the tracking instead of relying on single type of sensor. To conduct the multi-modal tracking, we have previously developed a multi-modal sensor-based tracking model where acoustic sensors mainly track the objects and visual sensors compensate the tracking errors [1]. In this paper, we find a network synchronization problem appearing in the developed tracking system. The problem is caused by the different location and traffic characteristics of multi-modal sensors and non-synchronized arrival of the captured sensor data at a processing server. To effectively deliver the sensor data, we propose a time-based packet aggregation algorithm where the acoustic sensor data are aggregated based on the sampling time and sent to the server. The delivered acoustic sensor data is then compensated by visual images to correct the tracking errors and such a compensation process improves the tracking accuracy in ideal case. However, in real situations, the tracking improvement from visual compensation can be severely degraded due to the aforementioned network synchronization problem, the impact of which is analyzed by simulations in this paper. To resolve the network synchronization problem, we differentiate the service level of sensor traffic based on Weight Round Robin (WRR) scheduling at the routers. The weighting factor allocated to each queue is calculated by a proposed Delay-based Weight Allocation (DWA) algorithm. From the simulations, we show the traffic differentiation model can mitigate the non-synchronization of sensor data. Finally, we analyze expected traffic behaviors of the tracking system in terms of acoustic sampling interval and visual image size.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.26 no.4
• /
• pp.99-108
• /
• 2001

In the ring loading problem with demand splitting, traffic demands are given for each pall of nodes in an undirected ring network and a flow is routed in either of the two directions, clockwise and counter-clockwise. The load of a link is the sum of the flows routed through the link and the objective of the problem is to minimize the maximum load on the ring. The fastest a1gorithm to date is Myung, Kim and Tcha＇s a1gorithm that runs in Ο(n｜K｜) time where n is the number of nodes and K is the index set of the origin-destination pairs of nodes having flow traffic demands. Here we develop an a1gorithm for the ring loading problem with demand splitting that improves the rerouting step of Myung, Kim and Tcha＇s a1gorithm arid runs in Ο(min{n｜K｜, n$^2$}) time.

• Journal of the Korean Mathematical Society
• /
• v.35 no.3
• /
• pp.727-740
• /
• 1998

Controlling traffic lights at a bottleneck, in [5] a time of open passage is called optimal, if it minimizes the first moment of the asymptotic distribution of the queue length. The discussion of the first moment as function of the time of open passage is based on an analysis of the behavior of a fixed point when varying control parameters and delivers theoretical and computational aspects of the traffic problem.

• Proceedings of the Korea Contents Association Conference
• /
• 2004.11a
• /
• pp.501-504
• /
• 2004

Straight traffic signal information is understanded by roation traffic signal.Ten traffic rotation street flew system saturated without forseed quantaty of traffic vehicle and length oftraffic street.Optimul traffic signal forcasting is needed departmemtstore sale season. for solution of this problem, at least before 10 hour traffic quantity reported policy department.For traffic forcasting of traffic jamed building pushed vehicle, neural network method is adapted Single traffic network is more needed to through traffic signal compared of traffic network. traffic network system is first analysed for artificial traffic network system and networked traffic systen is constructed by ubiquatous.