• Journal of the Society of Disaster Information
• /
• v.15 no.4
• /
• pp.548-559
• /
• 2019

Purpose: Analysis method of V2I data driven motorway service area usage behavior to cope with manpower survey. Method: Segmentation of traveling state group and boundary using the distribution characteristics of traveling speed data of individual vehicles. Result: As a result of the verification, the use rate of resting places in lunchtime surged, and the boundary between the distribution status of the traffic speed data was clearly or unclear. Conclusion: The effect of the cost reduction is big because it can cope with the use of rest area survey by manpower and there is no limit in the time and space range of investigation. The dynamic utilization rate of each time sequence, such as a service area/drowsiness shelter/simple service area, with a V2I system, can be calculated. Identify illegal parking on highway section. Identify the unexpected situation in the road section. Identify the real-time service area utilization rate and congestion information.

• Journal of Korean Society of Transportation
• /
• v.26 no.4
• /
• pp.241-250
• /
• 2008

With the ever-growing amount of traffic, there is an increasing need for good quality travel time information. Various existing outlier filtering and missing data imputation algorithms using AVI data for interrupted and uninterrupted traffic flow have been proposed. This paper is devoted to development of an outlier filtering and missing data imputation algorithm by using Toll Collection System (TCS) data. TCS travel time data collected from August to September 2007 were employed. Travel time data from TCS are made out of records of every passing vehicle; these data have potential for providing real-time travel time information. However, the authors found that as the distance between entry tollgates and exit tollgates increases, the variance of travel time also increases. Also, time gaps appeared in the case of long distances between tollgates. Finally, the authors propose a new method for making representative values after removal of abnormal and "noise" data and after analyzing existing methods. The proposed algorithm is effective.

• Journal of Korean Society of Transportation
• /
• v.34 no.2
• /
• pp.107-122
• /
• 2016

This study aims to develop a framework to estimate mobile source emissions with the macroscopic travel demand model including enhanced estimates of intra-zonal travel emissions using Space Syntax analysis. It is acknowledged that "the land-use and transportation interaction model explains the influence of urban structure on accessibility and mobility pattern". Based upon this theory, the estimation model of intra-zonal travel emissions is presented with the models of total travel distance, total travel demand, and average travel speed of intra-zonal trips. Thess statistical models include several spatial indices derived from the Space Syntax analysis. It explains that urban spatial structure is a critical factor for intra-zonal travel emissions, which is lower in compact zone with smaller portion of land area, lower sprawl indicator, and more grid-type of road network. Also the suggested framework is applied in the evaluation of the effectiveness of bicycle lane project in Suwon, Korea. The estimated emissions including intra-zonal travel is as double as the results only with inter-zonal demands, which shows better performance of the suggested framework for more realistic outcomes. This framework is applicable to the estimation of mobile source emissions in nation-wide and the assessment of transportation-environment policies in regional level.

• Journal of Korean Society of Transportation
• /
• v.23 no.7 s.85
• /
• pp.165-179
• /
• 2005

The object of this study is a development of a stochastic user equilibrium transit assignment algorithm for multiple user classes considering stochastic characteristics and heterogeneous attributes of passengers. The existing transit assignment algorithms have limits to attain realistic results because they assume a characteristic of passengers to be equal. Although one group with transit information and the other group without it have different trip patterns, the past studies could not explain the differences. For overcoming the problems, we use following methods. First, we apply a stochastic transit assignment model to obtain the difference of the perceived travel cost between passengers and apply a multiple user class assignment model to obtain the heterogeneous qualify of groups to get realistic results. Second, we assume that person trips have influence on the travel cost function in the development of model. Third, we use a C-logit model for solving IIA(independence of irrelevant alternatives) problems. According to repetition assigned trips and equivalent path cost have difference by each group and each path. The result comes close to stochastic user equilibrium and converging speed is very fast. The algorithm of this study is expected to make good use of evaluation tools in the transit policies by applying heterogeneous attributes and OD data.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.8 no.2
• /
• pp.14-26
• /
• 2009

This study presented a novel method to estimate travel times under incident conditions. Predictive travel time information was defined and evaluated with the proposed method. The proposed method utilized individual vehicle speeds obtained from global positioning systems (GPS) and inter-vehicle communications(IVC) for more reliable real-time travel times. Individual vehicle trajectory data were extracted from microscopic traffic simulations using AIMSUN. Market penetration rates (MPR) and IVC ranges were explored with the accuracy of travel times. Relationship among travel time accuracy, IVC ranges, and MPR were further identified using regression analyses. The outcomes of this study would be useful to derive functional requirements associated with traffic information systems under forthcoming ubiquitous transportation environment

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.32 no.6D
• /
• pp.679-686
• /
• 2012

KTX step 1 April 2004, after the opening, the second phase of the project was opened in November 2010. High-speed rail after the opening and continue to increase the demand of high-speed rail, Have the speed of competitive advantage compared too the means of transportation. The opening of these high-speed rail has led to changes of the move, the company's position, and the spatial structure of the population of reorganization, such as the social, economic, transportation. In this study, survey data using the High Speed Rail Station EMME/2 of the program to take advantage of the 2-Dimentional Blancing trip distribution to investigate the passage through the trip distribution by the estimation of the parameters of the model to estimate the distribution of the means of access and high-speed rail station to reproduce and Analysis of the results by means of access parameters (${\theta}$) autos 0.0395, buses 0.0390, subway 0.0650, taxi 0.0415, the frequency distribution (Trip Length Frequency Distribution: TLFD) were analyzed survey data value model with the results of comparing $R^2$ cars analysis and model values similar survey data 0.909 bus 0.923, subway 0.745 to 0.922, taxi, F test P value analysis is smaller than 0.05 at the 95% confidence level as a note that was judged to have been. Trip frequency distribution analysis, but in the future, set the unit to 5km-trip frequency distribution middle zone Units from small zone units (administrative district) segmentation research is needed, and can reflect the trip distance 0~5 km interval combined function to take advantage of the gravity model and the 3-Dimentional Blancing applied research is needed to be considered.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.13 no.1
• /
• pp.1-14
• /
• 2014

The expansion of the physical road in response to changes in social conditions and policy of the country has reached the limit. In order to alleviate congestion on the existing road to reconsider the effectiveness of this method should be asking. Currently, how to collect traffic information for management of the intersection is limited to point detection systems. Intelligent Transport Systems (ITS) was the traffic information collection system of point detection method such as through video and loop detector in the past. However, intelligent transportation systems of the next generation(C-ITS) has evolved rapidly in real time interval detection system of collecting various systems between the pedestrian, road, and car. Therefore, this study is designed to evaluate the development of an algorithm for queue length based real-time traffic signal control methodology. Four coordinates estimate on time-space diagram using the travel time each individual vehicle collected via the interval detector. Using the coordinate value estimated during the cycle for estimating the velocity of the shock wave the queue is created. Using the queue length is estimated, and determine the signal timing the total queue length is minimized at intersection. Therefore, in this study, it was confirmed that the calculation of the signal timing of the intersection queue is minimized.

• Journal of Korean Society of Transportation
• /
• v.35 no.3
• /
• pp.220-233
• /
• 2017

Traffic volumes are fundamental data widely used in various traffic analysis, such as origin-and-destination establishment, total traveled kilometer distance calculation, congestion evaluation, and so on. The low number of links collecting the traffic-volume data in a large urban highway network has weakened the quality of the analyses in practice. This study proposes a method to estimate the traffic volume data on a highway link where no collection device is available by introducing a spatial statistic technique with (1) the traffic-volume data from TOPIS, and National Transport Information Center in the Ministry of Land, Infrastructure, and (2) the navigation data from private navigation. Two different component models were prepared for the interrupted and the uninterrupted flows respectively, due to their different traffic-flow characteristics: the piecewise constant function and the regression kriging. The comparison of the traffic volumes estimated by the proposed method against the ones counted in the field showed that the level of error includes 6.26% in MAPE and 5,410 in RMSE, and thus the prediction error is 20.3% in MAPE.

• Journal of Korean Society of Transportation
• /
• v.22 no.7 s.78
• /
• pp.7-16
• /
• 2004

The homogeneous road section is defined as one consisted of similar traffic characteristics focused on demand and supply. The criteria, in the aspect of demand, are the diverging rate and the ratio of green time to cycle time at signalized intersection, and distance between the signalized intersections. The criteria, in that or supply, are the traffic patterns such as traffic volume and its speed. In this study, the effective method to generate valuable data, pointing out the problems of removal method of obscure data, is proposed using data collected from Gonjiam IC to Jangji IC on the national highway No.3. Travel times are collected with licence matching method and traffic volume and speed are collected from detectors. Futhermore, the method of selecting homogeneous road section is proposed considering demand and supply aspect simultaneously. This method using outlier filtering algorithm can be applied to generate the travel time forecasting model and to revise the obscured of missing data transmitting from detectors. The point and link data collected at the same time on the rational highway can be used as a basis predicting the travel time and revising the obscured data in the future.

• Journal of Korean Society of Transportation
• /
• v.24 no.3 s.89
• /
• pp.29-37
• /
• 2006

As a recurrent congestion of urban freeway occurs in almost same time and section, it is possible to manage the congestion effectively by the expectation and advance correspondence. In the existing traffic management system. we have used pattern data to manage a recurrent congestion. But it is not applicable to an urban freeway which kas various traffic circumstance. In this study, the probability by travel speed using a statistical distribution method will be used to predict the probability of recurrent congestion. It is expected that we can get the point of time and the duration of recurrent congestion, and we can devise an effective advance correspondence and a transportation operation.