• Journal of Korea Spatial Information System Society
• /
• v.10 no.3
• /
• pp.31-43
• /
• 2008

Travel time prediction is an indispensable to many advanced traveler information systems(ATIS) and intelligent transportation systems(ITS). In this paper we propose a method to predict travel time using $Na{\ddot{i}}ve$ Bayesian classification method which has exhibited high accuracy and processing speed when applied to classily large amounts of data. Our proposed prediction algorithm is also scalable to road networks with arbitrary travel routes. For a given route, we consider time-varying average segment velocity to perform more accuracy of travel time prediction. We compare the proposed method with the existing prediction algorithms like link-based prediction algorithm [1] and Micro T* algorithm [2]. It is shown from the performance comparison that the proposed predictor can reduce MARE (mean absolute relative error) significantly, compared with the existing predictors.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.34 no.1
• /
• pp.243-250
• /
• 2014

Modern roundabouts referred to as relatively safer and more efficient traffic facility than the signalized intersections have been recently deployed and operated and accordingly more research efforts to improve its safety and efficiency have been made so far. This paper introduces a new traffic information system named as Smart Roundabout coupled with Connected Vehicle technique like Vehicle-to-Roadside communication, which has not been attempted before and evaluates its performance with a microscopic simulation model, VISSIM. The proposed system functions to collect driving information of circulating vehicles in the roundabout such as location, speed, critical headway, etc. and help approaching vehicles decide whether to enter the roundabout with an on-board equipment instrumented in the individual vehicle on the basis of calculated gap acceptance of interest. This new system is expected to secure more safety and increase the capacity of the modern roundabout.

• Journal of Korean Society for Geospatial Information Science
• /
• v.1 no.2 s.2
• /
• pp.167-175
• /
• 1993

This article contains three objectives. First it is to revise unnecessary procedures of a transportation models and transform results of a model into an image. Second objectives is to develop an operational structures which automatically input all data needed from arc-node topology to link-node topology of transportation network. By solving the network discrepancy, time and money for constructing to transportation can be saved. In addition, the rate of errors that my caused during data input process can be reduced. Conclusively, it is found that the integration package may provide user friendliness and reduce the rate of errors. The package can extract informations such as distance between zones and nodes, lane numbers, and hierarchy from arc-node topology for executing SDI. Another advantage of integration is the ability of spatial analysis. The integrated package may provide adequate arrangements of traffic facilities and checking systems of the shortest path. Finally, the database function of GIS package provides various information about study area for transportation analysis.

• The Journal of the Korea Contents Association
• /
• v.6 no.1
• /
• pp.114-125
• /
• 2006

Since wireless Internet services and small mobile communication devices come into wide use as well as the use of GPS is rapidly growing, researches on moving object, whose location information shifts sequently in accordance with time interval, are being carried out actively. Especially, the researches on vehicle moving object are applied to Advanced traveler information system, vehicle tracking system, and distribution transport system. These systems are very useful in searching previous positions, predicted future positions, the optimum course, and the shortest course of a vehicle by managing historical data of the vehicle movement. In addition, vehicle historical data are used for distribution transport plan and vehicle allocation. Vehicle historical data are stored at regular intervals, which can have a pattern. For example, a vehicle going repeatedly around a specific section follows a route very similar to another. If historical data of the vehicle with a repeated route course are stored at regular intervals, many redundant data occur, which result in much waste of storage. Therefore this thesis suggest a vehicle historical data store scheme for vehicles with a repeated route course using similar trajectory which efficiently store vehicle historical data.

• Journal of Korean Society of Transportation
• /
• v.19 no.4
• /
• pp.85-96
• /
• 2001

This paper discusses the problem of finding the Origin-Destination(O-D) shortest path in urban road networks that have variable special qualifies such as time windows for passing as well as geometrical special qualities such as U-turn and left-turn prohibition. The focus of this paper is motivated by the problem of finding minimum travel time paths for an advanced traveler information system (ATIS) in the context of intelligent transportation system(ITS) application. The transportation network with variable and geometrical special qualities is a more realistic representation of the urban road network in the real word. But, the traditional and existing shortest path algorithms can not search practical shortest path that variable special quality is reflected. This paper presents a shortest path algorithm which can search reasonable shortest path information for the urban ATIS application within a real time. The algorithm is based on genetic algorithm(GA). The high performance of the proposed algorithm is demonstrated by computer simulations.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.37 no.6
• /
• pp.1033-1041
• /
• 2017

Path travel time based on departure time (PTTDP) is key information in advanced traveler information systems (ATIS). Despite the necessity, forecasting PTTDP is still one of challenges which should be successfully conquered in the forecasting area of intelligent transportation systems (ITS). To address this problem effectively, a methodology to dynamically predict PTTDP between motorway interchanges is proposed in this paper. The method was developed based on the relationships between traffic demands at motorway tollgates and PTTDPs between TGs in the motorway network. Two different data were used as the input of the model: traffic demand data and path travel time data are collected by toll collection system (TCS) and dedicated short range communication (DSRC), respectively. The proposed model was developed based on k-nearest neighbor, one of data mining techniques, in order for the real applications of motorway information systems. In a feasible test with real-world data, the proposed method performed effectively by means of prediction reliability and computational running time to the level of real application of current ATIS.

• Journal of Korean Society of Transportation
• /
• v.20 no.4
• /
• pp.51-61
• /
• 2002

In this dissertation, We demonstrated the Travel Time forecasting model in the freeway of multi-section with regard of drives' attitude. Recently, the forecasted travel time that is furnished based on expected travel time data and advanced experiment isn't being able to reflect the time-lag phenomenon specially in case of long distance trip, so drivers don't believe any more forecasted travel time. And that's why the effects of ATIS(Advanced Traveler Information System) are reduced. Therefore, in this dissertation to forecast the travel time of the freeway of multi-section reflecting the time-lag phenomenon & the delay of tollgate, we used traffic volume data & TCS data that are collected by Korea Highway Cooperation. Also keep the data of mixed unusual to applicate real system. The applied model for forecasting is consisted of feed-forward structure which has three input units & two output units and the back-propagation is utilized as studying method. Furthermore, the optimal alternative was chosen through the twelve alternative ideas which is composed of the unit number of hidden-layer & repeating number which affect studying speed & forecasting capability. In order to compare the forecasting capability of developed ANN model. the algorithm which are currently used as an information source for freeway travel time. During the comparison with reference model, MSE, MARE, MAE & T-test were executed, as the result, the model which utilized the artificial neural network performed more superior forecasting capability among the comparison index. Moreover, the calculated through the particularity of data structure which was used in this experiment.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.2D
• /
• pp.199-207
• /
• 2009

We tried to show the course of UTIS vitalization, promoting to introduce as part of the advanced traveler information system through analysis using traffic information gap model of service and structural equation modeling being used by drivers. The summary of the research is as follows. 1. We could find out the service matters needed to improve and what should be prior that make drivers' use increase through establishing the gap model of service. 2. We could establish the structural equation modeling through using traffic information use satisfaction rate, entire traffic information satisfaction rate as the observation variables. You can say it is the fruit of this research that it was confirmed the entire satisfaction rate of traffic information influenced extension, convenience, accuracy, economical efficiency in order. We could also arrange the base to determine the order of services for vitalization of UTIS in the future through grasping the priority of each service functions classified by factors. 3. It is confirmed that many drivers want multimedia function, driving support function and various functions for the personal convenience in situations except driving, which enable the drivers to enjoy leisures and interests rather than economical functions during driving due to the recent social and economic changes.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.1 no.1
• /
• pp.41-51
• /
• 2002

As Advanced Traveler Information System(ATIS) is the kernel of the Intelligent Transportation System, it is very important how to manage data from traffic information collectors on a road and have at borough grip of the travel time's change quickly and exactly for doing its part. Link travel time can be obtained by two method. One is measured by area detection systems and the other is estimated by point detection systems. Measured travel time by area detection systems has the limitation for real time information because it Is calculated by the probe which has already passed through the link. Estimated travel time by point detection systems is calculated by the data on the same time of each. section, this is, it use the characteristic of the various cars of each section to estimate travel time. For this reason, it has the difference with real travel time. In this study, Artificial Neural Networks is used for estimating link travel time concerned about the relationship with vehicle detector data and link travel time. The method of estimating link travel time are classified according to the kind of input data and the Absolute value of error between the estimated and the real are distributed within 5$\~$15minute over 90 percent with the result of testing the method using the vehicle detector data and AVI data of Namsan Tunnel $\#$1. It also reduces Time lag of the information offered time and draws late delay generation and dissolution.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.7 no.1
• /
• pp.10-21
• /
• 2008

User travel behavior is based on the existence of complete traffic information in deterministic user optimal principle by Wardrop(1952). According to deterministic user optimal principle, users choose the optimal route from origin to destination and they change their routes arbitrarily in order to minimize travel cost. In this principle, users only consider travel time as a factor to take their routes. However, user behavior is not determined by only travel time in actuality. Namely, the models that reflect only travel time as a route choice factor could give irrational travel behavior results. Therefore, the model is necessary that considers various factors including travel time, transportation networks structure and traffic information. In this research, more realistic deterministic optimal traffic assignment model is proposed in the way of route recognizance behavior. This model assumes that when users decide their routes, they consider many factors such as travel time, road condition and traffic information. In addition, route recognizance attributes is reflected in this suggested model by forward searching method and backward searching method with numerical formulas and algorithms.