선택한 단어 수는 입니다.
최소 단어 이상 선택하여야 합니다.
최소 단어 이상 선택하여야 합니다.
선택한 단어 수는 30입니다.
최대 10 단어까지만 선택 가능합니다.
최대 10 단어까지만 선택 가능합니다.
제안 방법
- First, in this study, the CTFM is applied instead of the others detection methods of incidents, which enables estimating 30-seconds of cumulative traffic flows, in each of the incident and steady traffic flow, reflecting the dynamic changes in the traffic volume caused by shock waves. Also, the estimated outcomes could be the traffic flows of higher actual data and the statistical feasibility.
- In order to collect the actual data, we used the Freeway Traffic Management System(FTMS) data within OASIS of the Korea Expressway Corporation. First, the data regarding accidents with trucks around Anseong, Gyeongbu Expressway(326km away from endpoint Busan) were collected to identify the conditions related to the accident, spots of accidents and time points. The data came from a time around 9 am, on Thursday 18th of September, 2003, based on the accident data.
- In this study, it is assumed that the CTFM, suggested by Newell, is applied on the Cumulative Traffic Flow, which reflects the characteristics of dynamic traffic flows in the actual traffic environment, based on the data provided by the Korea Expressway Corporation's FTMS. In order to verify the feasibility of the assumed cumulative traffic flow, the errors in the Cumulative Traffic Flow were statistically analyzed and, based on the verification of heteroscedasticity of errors in cumulative traffic flows that was revealed from the central detector application between the steady flow and the incident-involved traffic flow, the study suggests a method of detecting all traffic flows involving the incidents, which differ statistically from the steady flows. The results of this study can be summarized as follows.
- In this study, it is assumed that the CTFM, suggested by Newell, is applied on the Cumulative Traffic Flow, which reflects the characteristics of dynamic traffic flows in the actual traffic environment, based on the data provided by the Korea Expressway Corporation's FTMS.
- Such result helped the authors to prove the statistical suitability of the NTSM. Second, based on the estimation Cumulative Traffic Flow as a variable to determine an incident, it was able to generally explore the traffic flow as an incident variable under the unexpected incidents, based on the changes in statistical errors in cumulative traffic flows. Based on the analytic results, the maximum error (8%) occurred around 11 o'clock, 2-3 hours after the accident.
- In order to derive the possible successive studies, first, there is a necessity for the calculation and settling based on continued studies and on-site data, for establishing an appropriate critical value to detect an incident accurately. Second, the boundary of the incidents on some of the closed zones on the Gyeongbu Expressway has caused difficulties in extracting the optimum data and the basic assumptions in this study to assume the traffic volumes. Thus there is a necessary for a continuous verification of the models pertaining to various incidents in broader range of time and space conditions, as well as the environmental variables.
- The Newell's 3-detector Simplification Method(NTSM) justified by Daganzo(1997) is applied in this study for detecting unexpected incidents. The applied method of detecting incidents in this study has variables, such as, the cumulative traffic flow with relatively less errors than the other attributes of traffic flows, and it enables to get prepared for detector data errors, which occur easily in high-density and highly occupied traffic flows, and provides the mathematical approach techniques. This presents the clear theoretical backgrounds and covers the flow of shock waves in the calculation process, providing an advantage of reflecting the actual network of the environment of dynamic traffic flows.
- Figure 4 differs for its axis of ordinates is composed of vehicles, while Figure 5 and 6's axis or ordinates are composed of percent values. The index idea for this study is to measure the difference in normal flow and accident flow by a certain unit(1 hour for this study) after measuring the percent unit of the error rate for accumulation traffic.
대상 데이터
- The data came from a time around 9 am, on Thursday 18th of September, 2003, based on the accident data. The analytic space covers 362.3-371.8km(approximately, 10km) from Busan, with reference to the highway distance in a time range from 8 am to 15 pm, including the moment of accident. The time range of steady traffic flows subject to a comparative analysis was between 8 AM and 15 PM, on Thursday, 25th of September, 2003, the same weekday and time range.
데이터처리
- The statistical values for the verification of suitability of the estimated and actually measured cumulative traffic values of the center were applied, based on the NTSM, Mean Percentage Square Error(MPSE), Root Mean Square Error(RMSE) and Theil's Inequality Coefficient.
이론/모형
- In order to detect such unexpected incidents, this study aims to describe the 3-detector simplification model, proven by Daganzo(1997), in a statistical model and to verify the statistical appropriacy thereof. The Newell's 3-detector Simplification Method(NTSM) justified by Daganzo(1997) is applied in this study for detecting unexpected incidents.
- The 3-detector simplification model used in this study was derived from an idea on the difference in density of traffics in an outbreak situation and a steady flow, which ultimately influence the relationship between traffic and density, having an impact on the traffic of the central detector of the 3-detector. Once an outbreak situation occurs, the shock wave will cause a fluctuation of density, resulting in a large error in measured accumulative traffic compared to the predicted.
- The Newell's 3-detector Simplification Method(NTSM) justified by Daganzo(1997) is applied in this study for detecting unexpected incidents.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.