• International Journal of Highway Engineering
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• v.18 no.2
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• pp.91-101
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• 2016

PURPOSES : The aim of this study was to compare the performance of the QUEENSOD method and the gravity model in estimating Origin-Destination (O/D) tables for a large-sized microscopic traffic simulation network. METHODS : In this study, an expressway network was simulated using the microscopic traffic simulation model, VISSIM. The gravity model and QUEENSOD method were used to estimate the O/D pairs between internal and between external zones. RESULTS: After obtaining estimations of the O/D table by using both the gravity model and the QUEENSOD method, the value of the root mean square error (RMSE) for O/D pairs between internal zones were compared. For the gravity model and the QUEENSOD method, the RMSE obtained were 386.0 and 241.2, respectively. The O/D tables estimated using both methods were then entered into the VISSIM networks and calibrated with measured travel time. The resulting estimated travel times were then compared. For the gravity model and the QUEENSOD method, the estimated travel times showed 1.16% and 0.45% deviation from the surveyed travel time, respectively. CONCLUSIONS : In building a large-sized microscopic traffic simulation network, an O/D matrix is essential in order to produce reliable analysis results. When link counts from diverse ITS facilities are available, the QUEENSOD method outperforms the gravity model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.54-63
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• 2023

Pedestrian traffic needs to be accurately quantified to predict effectively pedestrian traffic accidents, however, pedestrian traffic is more difficult to measure than vehicle traffic. In this study, we suggest the time-and cost-effective application of mobile closed-circuit television (CCTV) using a smartphone as an alternative that can collect and analyze real-time data with little. In the present investigation, the pedestrian-vehicle conflict that can develop into an accident was defined as the pedestrian accident exposure. After installing mobile CCTV in 40 sections of Dongseong-ro, Daegu, the pedestrian accident exposure was estimated through negative binomial regression analysis using the collected data. The results of the analysis showed statistically significant changes in the pedestrian accident exposure variables. Based on the present results, a pedestrian accident exposure estimation model was developed which can be used in sections where pedestrian accidents may occur.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1A
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• pp.143-153
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• 2006

In design of bridges, estimation of actions and loadings is very important for the safety and maintenance of bridges. In general, effect of traffic loading on the bridge can be modeled as live load (including impact load) and fatigue load. For estimation of traffic loading, it is important to get reliable and comprehensive truck statistical data such as the traffic and weight information. To get statistical data, Bridge Weigh-In-Motion (BWIM), which measures the truck weights without stopping the traffic, is need to be developed. In this study, BWIM system with various functions is developed first. Then this system is used to get comprehensive truck data. Traffic loadings including fatigue and live loading are formulated from the truck data acquired from the bridges. Objectives of this study are to develop the BWIM system, to apply the system in test bridge in Highway, and to formulate the live and fatigue loading for bridge design.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.763-769
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• 2006

Gravity Model estimates target year's distributed trips using three variables like as origin zone's trip production, destination zone's trip attraction and traffic impedance between origin zone centroid and destination zone centroid. Estimating inner zone trip by gravity model is impossible because traffic impedance of inner zone has "0" value. So till today, for estimating inner zone trips, other methods like growth factor model are used. This study proposed inner zone trip estimation method that calculates inner zone's traffic impedance using established gravity model and estimates inner zone trips by putting calculated traffic impedance into the gravity model. 1988 year's surveyed O-D as basic year's O-D, proposed method's and existing methods(growth factor method and regression model)'s estimated results of 1992 year's and 2004 year's were compared with each year's real O-D by $x^2$, RMSE, Correlation coefficient. And resulted that the proposed method is superior than other existing methods.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.430-439
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• 2016

Estimation and analysis of traffic jams plays a vital role in an intelligent transportation system and advances safety in the transportation system as well as mobility and optimization of environmental impact. For these reasons, many researchers currently mainly focus on the brilliant machine learning-based prediction approaches for traffic prediction systems. This paper primarily addresses the analysis and comparison of prediction accuracy between two machine learning algorithms: Naïve Bayes and K-Nearest Neighbor (K-NN). Based on the fact that optimized estimation accuracy of these methods mainly depends on a large amount of recounted data and that they require much time to compute the same function heuristically for each action, we propose an approach that applies multi-threading to these heuristic methods. It is obvious that the greater the amount of historical data, the more processing time is necessary. For a real-time system, operational response time is vital, and the proposed system also focuses on the time complexity cost as well as computational complexity. It is experimentally confirmed that K-NN does much better than Naïve Bayes, not only in prediction accuracy but also in processing time. Multi-threading-based K-NN could compute four times faster than classical K-NN, whereas multi-threading-based Naïve Bayes could process only twice as fast as classical Bayes.

• Proceedings of the KOR-KST Conference
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• 1998.10a
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• pp.236-244
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• 1998

When the capacity and traffic operation at signalized intersections are analyzed in Korea, the unprotected left-turn saturation flow rate, which is an important parameter for the analysis, is estimated form the USHCM model. thus, exact analysis of the left-turn is not possible because of the difference of traffic environments between two contries. In order to improve this problem, it is undertaken in this study to develop techniques for the estimation of unprotected left-turn saturation flows based on Korean drivers' data. As study intersections, signalized or unsignalized intersections on the 6, 4 and 2 lane streets are selected. the data for the saturation flow measurement and gap-acceptance behavior analysis are inputed in a notebook computer on the sites. The critical acceptance gaps of the 6, 4, and 2 lane streets are analyzed to be 6.0 secs, 4.6 secs, and 4.3 secs respectively. the average minimum headway of the left-turn vehicle was observed to be 2.6 secs. As the model to estimate unportected left-turn saturation flows, the drew model is recommended for 6 and 4 lane streets, and a graph is suggested for the 2-lane street. As the values of the parameters of the Drew model, the 2.6 secs of this study is recommended for the average minimum headway of the left-turn. But, the critical acceptance gap varies according to the approach speed of opposing traffic and driver population, it requires field survey to measure the gap of an intersection; however, the values of the gaps studied in this study may be used for the general intersections in urban area in Korean.

• Journal of Korean Society of Transportation
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• v.23 no.7 s.85
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• pp.125-136
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• 2005

The goal of this paper is to develop freeway Origin-Destination (OD) demand estimation model using VDS and AVI data. The formulation of methodology proposed in this paper includes traffic flow technique to be able to remove the bi-level problem and optimal solution algorithm using a kalman filter algorithm. The proposed dynamic OD estimation model use ilk and off-ramp volumes collected from VDS and partial OD collected from AVI data to raise the accuracy of dynamic OD estimation. The proposed model is evaluated by using the real-time data of SOHAEAN freeway, South Korea. The result of the proposed dynamic OD estimation model based on VDS and AVI data is better than that of based on VDS data. The more AVI systems are equipped at on and off-ramp, the more excellent result of estimation accuracy is expected.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.131-142
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• 2001

Previous OD matrix estimation methods from link traffic counts have focused on the formulation of mathematical model and its solution algorithm. Thereby those methods have assumed that true or real OD is similar to the target OD and paid little attention to the properties of the change of OD structure. Although it is general situation that each OD pair increases or decreases due to significant land use and to large time variation between target OD with real OD, those methods have set unrealistic assumptions that target OD increases or decreases uniformly and that the OD structure does not change. Therefore those methods have showed poor performance of OD estimation in general situation. To cope with the problem. this paper suggests a new concept of OD matrix structure and shows the shortcomings of previous method′s dependancy on target OD matrix. We divide "OD trips" into "OD scale" and "OD structure". Where OD scale is a quantitative magnitude of OD trips and "OD structure" is ordinal OD scale. This paper use the same solution algorithm developed by Baek et al. (2000) for analysing the OD structure. Results of numerical examples show that the performance of the method is better than that of previous methods, while the previous methods have better performance in estimation only when OD trips increase or decrease. In addition to, if OD structure does not change, the results show that the error of estimation is low relatively regardless of the large difference of trips between target OD and real OD. This paper also shows that the model performance on OD structure and on OD trips is low as the number of origins that OD structure is changed increase. From the results we suggest that the change of OD structure can be more important information than the difference between target OD and real OD in OD estimation steps.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.6
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• pp.1339-1345
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• 2015

Korean government annually estimates and reports the traffic safety index to evaluate the traffic safety of 228 Gu Gun. However, since the traffic safety index is derived from the spatially macroscopic perspective based on collected relative data, there are a couple of problems such as inability to investigate the individual traffic accidents on the spot, insecurity of accuracy and reliability of traffic safety index estimation method, and absence of establishing temporal relationship of traffic accidents. Thus, this study investigated temporal traffic safety in macroscopic manner for Gu Gun in Busan depending on the installation of the traffic safety facility (i.e., urban median), employing meta analysis. As a result, all Gu Gun in Busan except Saha, Buk, Dong, and Busanjin experienced more traffic accidents after installing the urban median, indicating that there are more rooms for improvement of macroscopic traffic safety evaluation.

• ETRI Journal
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• v.37 no.1
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• pp.11-20
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• 2015

This paper deals with optimal power allocation for channel estimation of orthogonal frequency-division multiplexing uplinks in time-varying channels. In the existing literature, the estimation of time-varying channel response in an uplink environment can be accomplished by estimating the corresponding channel parameters. Accordingly, the optimal power allocation studied in the literature has been in terms of minimizing the mean square error of the channel estimation. However, the final goal for channel estimation is to enable the application of coherent detection, which usually means high spectral efficiency. Therefore, it is more meaningful to optimize the power allocation in terms of capacity. In this paper, we investigate capacity with imperfect channel estimation. By exploiting the derived capacity expression, an optimal power allocation strategy is developed. With this developed power allocation strategy, improved performance can be observed, as demonstrated by the numerical results.