• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.3
• /
• pp.51-61
• /
• 2023

Travel demand estimation of E-Scooter is the start point of solving the regional demand-supply imbalance problem and plays pivotal role in a linked transportation system such as Mobility-as-a-Service (a.k.a. MaaS). Most focuses on developing trip generation model of shared E-Scooter but it is no study on selection of an appropriate zone scale when it comes to estimating travel demand of E-Scooter. This paper aimed for selecting an optimal TAZ scale for developing trip distribution model for shared E-Scooter. The TAZ scale candidates were selected in 250m, 500m, 750m, 1,000m square grid. The shared E-Scooter usage historical data were utilized for calculating trip distance and time, and then applying to developing gravity model. Mean Squared Error (MSE) is applied for the verification step to select the best suitable gravity model by TAZ scale. As a result, 250m of TAZ scale is the best for describing practical trip distribution of shared E-Scooter among the candidates.

• 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

• Journal of Korean Society of Transportation
• /
• v.18 no.5
• /
• pp.83-97
• /
• 2000

The traffic management schemes through traffic signal control and information provision could be effective when the link-level data and trip-level data were used simultaneously in analysis Procedures. But, because the trip-level data. such as origin, destination and departure time, can not be obtained through the existing surveillance systems directly. It is needed to estimate it using the link-level data which can be obtained easily. Therefore the objective of this study is to develop the model to estimate O-D demand using only the link flows in highway network as a real time. The methodological approaches in this study are kalman filer, least-square method and normalized least-square method. The kalman filter is developed in the basis of the bayesian update. The normalized least-square method is developed in the basis of the least-square method and the natural constraint equation. These three models were experimented using two kinds of simulated data. The one has two abrupt changing Patterns in traffic flow rates The other is a 24 hours data that has three Peak times in a day Among these models, kalman filer has Produced more accurate and adaptive results than others. Therefore it is seemed that this model could be used in traffic demand management. control, travel time forecasting and dynamic assignment, and so forth.

• Journal of Korean Society of Transportation
• /
• v.20 no.2
• /
• pp.27-38
• /
• 2002

This study estimates the social cost of the traffic congestion of the Express highway from Seoul to Pusan during the New Year holiday in 1999. Considering inelastic demand and the hyper congestion, we show the congestion cost can be estimated as externalities caused by traffics which exceed the road capacity. Due to the congestion, it is estimated that it took about 12.40 hours more from Seoul to Pusan. The congestion is also estimated to have caused fuel cost of 0.6 billion won. time cost of 43.6 billion won and environmental cost of 0.5 billion won. The total cost reached up to 44.8 billion won.

• 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.32 no.4
• /
• pp.347-356
• /
• 2014

Passenger cars occupy about 74% among registered vehicles in Korea and the ratio of transportation mode sharing is approximately 60% in the passenger transport part. However, there is no statistics related to travel characteristics of passenger cars, and official statistics are estimated from O/D travel data. Thus, National Transportation DataBase Center in KOTI has attempted to construct various statistical data through Korea Vehicle Use Survey. Based on these data, Analysis of Variance (ANOVA) was conducted to investigate the differences in travel characteristics of each analysis group. As a result, all of the explanatory variables(weekday vs. weekend, metropolitan area vs. non-metropolitan area, male vs. female, commute time vs. other time, routine purpose vs. non-routine purpose) were found to be different across households. In addition, travel distances per trip of weekday, metropolitan area, male, commute time, and non-routine purpose are longer than the opposite variables. Also, the trip distances of small size(1 to 2 persons) households are shorter compared to large size(more than 5 persons) households.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.12 no.1
• /
• pp.147-157
• /
• 2013

This study developed the transit transfer mode choice model aimed Daegu transit users using multinomial logit model. Dependent variables of estimating multinomial logit model were transit transfer modes such as bus to bus, bus to subway, subway to subway, bus to others, and subway to others, and explanatory variables which affect transit transfer mode choice were sex, age, occupation, handicap, transfer area, purpose of travel and travel time. Also probability regarding explanatory variables was estimated using multinomial logit model and limit marginal analysis was carried out according to explanatory variables(cost, time). In the results, indicating goodness of fit is very reasonable as ${\rho}^2$=0.354. According to the result of marginal analysis for the selection of probability, when travel time is increased, users of bus to bus and bus to subway prefer to use subway to subway. Furthermore users of bus to bus and bus to subway prefer to use bus to others and subway to others when travel cost is increased in the result of marginal analysis for the selection of probability.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.31 no.2D
• /
• pp.193-201
• /
• 2011

The provision of traffic information plays an important role in increasing social benefit not only by saving travel time for individuals but also by improving the efficiency of road operation. VMS(Variable Message Sign) helps on-wheel drivers easily understand the road situation, and also provides real-time traffic information to people on the streets. However, it has not been sufficiently studied on how traffic information based on VMS influences on the drivers' selection of route. This study investigated how drivers use VMS traffic information and how they are satisfied with it. Then, the model of drivers' route selection was specified with the types of traffic information and the expected travel time to examine the influence on the selection of drivers' route. The model was estimated and analyzed in three types according to the condition of detour roads, and the rate of route change and the degree of sensitivity was calculated from the estimation. The results of analysis are as follows. the $1^{st}$ type model showed the 10% of route change for the travel time saving of 5minutes, and the 81.6% of route change for the travel time saving of 20minutes. The $2^{nd}$ type led to the range of route change from 14.2% to 92.7% over the 5 through 20 minutes of travel time saving. The $3^{rd}$ model resulted in the 99.1% of route change. The sensitivity of route change showed the highest for the travel time saving of 11 minutes with the $1^{st}$ type model, 9 minutes with the $2^{nd}$ type model, and 5 minutes with the $3^{rd}$ type model respectively.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.3
• /
• pp.249-257
• /
• 2017

Filtering the data for travel time records obtained from DSRC probes is essential for a better estimation of the link travel time. This study addresses the major deficiency in the performance of TRANSGUIDE in removing anomalous data. This algorithm is unable to handle unstable traffic flow conditions for certain time intervals, where fluctuations are observed. In this regard, this study proposes an algorithm that is capable of overcoming the weaknesses of TRANSGUIDE. If TRANSGUIDE fails to validate sufficient number of observations inside one time interval, another process specifies a new validity range based on the median absolute deviation (MAD), a common statistical approach. The proposed algorithm suggests the parameters, ${\alpha}$ and ${\beta}$, to consider the maximum allowed outlier within a one-time interval to respond to certain traffic flow conditions. The parameter estimation relies on historical data because it needs to be updated frequently. To test the proposed algorithm, the DSRC probe travel time data were collected from a multilane highway road section. Calibration of the model was performed by statistical data analysis through using cumulative relative frequency. The qualitative evaluation shows satisfactory performance. The proposed model overcomes the deficiency associated with the rapid change in travel time.

• 한국공간정보시스템학회:학술대회논문집
• /
• 1999.06a
• /
• pp.181-189
• /
• 1999

21세기 무한경쟁시대에서 국가경쟁력을 확보하기 위하여 현재 도로교통상황을 추정하고, 화물차의 공차(空車)를 줄이고, 차량운행상태를 관리할 필요성이 부각되었다. 본 연구에서는 실시간 교통정보산출 및 활용을 위하여 국가수치기본도에 GPS을 응용하는 기법을 제시하였다. 구체적으로는 GIS기능 중 하나인 공간결합(Spatial Join)기능을 활용하여 Map Matching, 통행시간추정 및 차량운행 관리기법 등을 제시하였다. 최종적으로는 제시된 기법을 서울시 강남구 지역일대에 시범적으로 적용시켜 보았다.