• 한국도로학회논문집
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• 제18권1호
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• pp.99-107
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• 2016

PURPOSES : This study was initiated to estimate expressway traffic congestion costs by using Vehicle Detection System (VDS) data. METHODS : The overall methodology for estimating expressway traffic congestion costs is based on the methodology used in a study conducted by a study team from the Korea Transport Institute (KOTI). However, this study uses VDS data, including conzone speeds and volumes, instead of the volume delay function for estimating travel times. RESULTS : The expressway traffic congestion costs estimated in this study are generally lower than those observed in KOTI's method. The expressway lines that ranked highest for traffic congestion costs are the Seoul Ring Expressway, Gyeongbu Expressway, and the Youngdong Expressway. Those lines account for 64.54% of the entire expressway traffic congestion costs. In addition, this study estimates the daily traffic congestion costs. The traffic congestion cost on Saturdays is the highest. CONCLUSIONS : This study can be thought of as a new trial to estimate expressway traffic congestion costs by using actual traffic data collected from an entire expressway system in order to overcome the limitations of associated studies. In the future, the methodology for estimating traffic congestion cost is expected to be improved by utilizing associated big-data gathered from other ITS facilities and car navigation systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권10호
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• pp.3858-3874
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• 2021

As an essential part of the urban transportation system, precise perception of the traffic flow parameters at the traffic signal intersection ensures traffic safety and fully improves the intersection's capacity. Traditional detection methods of road traffic flow parameter can be divided into the micro and the macro. The microscopic detection methods include geomagnetic induction coil technology, aerial detection technology based on the unmanned aerial vehicles (UAV) and camera video detection technology based on the fixed scene. The macroscopic detection methods include floating car data analysis technology. All the above methods have their advantages and disadvantages. Recently, indoor location methods based on wireless signals have attracted wide attention due to their applicability and low cost. This paper extends the wireless signal indoor location method to the outdoor intersection scene for traffic flow parameter estimation. In this paper, the detection scene is constructed at the intersection based on the received signal strength indication (RSSI) ranging technology extracted from the wireless signal. We extracted the RSSI data from the wireless signals sent to the road side unit (RSU) by the vehicle nodes, calibrated the RSSI ranging model, and finally obtained the traffic flow parameters of the intersection entrance road. We measured the average speed of traffic flow through multiple simulation experiments, the trajectory of traffic flow, and the spatiotemporal map at a single intersection inlet. Finally, we obtained the queue length of the inlet lane at the intersection. The simulation results of the experiment show that the RSSI ranging positioning method based on wireless signals can accurately estimate the traffic flow parameters at the intersection, which also provides a foundation for accurately estimating the traffic flow state in the future era of the Internet of Vehicles.

• 제어로봇시스템학회논문지
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• 제19권2호
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• pp.125-130
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• 2013

Compared to OWR (One-Way Ranging) method that requires precise network time synchronization, TWR (Two-Way Ranging) method has advantages in building an indoor WPAN (Wireless Personal Area Network) location system with lower cost. However, clock offsets of nodes in WPAN system should be eliminated or compensated to improve location accuracy of the TWR method. Because conventional clock offset elimination methods requires multiple TWR transactions to reduce clock offset, they produce network traffic burden instead. This paper presents a clock offset estimation method that can reduce clock offset error with a single TWR transaction. After relative clock offsets of sensor nodes are estimated, clock offsets of mobile tags are estimated using a single TWR communication. Simulation results show that location accuracy of the proposed method is almost similar to the conventional clock offset elimination method, while its network traffic is about a half of the conventional method.

• ETRI Journal
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• 제30권2호
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• pp.194-204
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• 2008

The online collection of coarse-grained traffic information, such as the total number of flows, is gaining in importance due to a wide range of applications, such as congestion control and network security. In this paper, we focus on an active queue management scheme called SRED since it estimates the number of active flows and uses the quantity to indicate the level of congestion. However, SRED has several limitations, such as instability in estimating the number of active flows and underestimation of active flows in the presence of non-responsive traffic. We present a Markov model to examine the capability of SRED in estimating the number of flows. We show how the SRED cache hit rate can be used to quantify the number of active flows. We then propose a modified SRED scheme, called hash-based two-level caching (HaTCh), which uses hashing and a two-level caching mechanism to accurately estimate the number of active flows under various workloads. Simulation results indicate that the proposed scheme provides a more accurate estimation of the number of active flows than SRED, stabilizes the estimation with respect to workload fluctuations, and prevents performance degradation by efficiently isolating non-responsive flows.

• 한국측량학회지
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• 제36권5호
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• pp.335-341
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• 2018

The KDE (Kernel Density Estimation) technique in GIS (Geographic Information System) has been widely used as a method for determining whether a phenomenon occurring in space forms clusters. Most human-generated events such as traffic accidents and retail stores are distributed according to a road network. Even if events on forward and rear roads have short Euclidean distances, network distances may increase and the correlation between them may be low. Therefore, the NKDE (Network-based KDE) technique has been proposed and applied to the urban space where a road network has been developed. KDE is being studied in the field of business GIS, but there is a limit to the microscopic analysis of economic activity along a road. In this study, the NKDE technique is applied to the analysis of urban phenomena such as the density of shops rather than traffic accidents that occur on roads. The results of the NKDE technique are also compared to pedestrian networks and road centerline networks. The results show that applying NKDE to microscopic trade area analysis can yield relatively accurate results. In addition, it was found that pedestrian network data that can consider the movement of actual pedestrians are necessary for accurate trade area analysis using NKDE.

• 한국멀티미디어학회논문지
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• 제19권8호
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• pp.1377-1385
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• 2016

Conventional X-band marine radar has been used as one of the effective tools for collecting and retrieving ocean surface information parameters for three decades. Several wave information extracting algorithms have been designed in such a way that they can be utilized for efficiently estimating sea surface wave parameters such as current velocities, wave direction, significant wave heights in VTS (Vessel Traffic Service). However, their performances are still restricted. For the purpose of overcoming the performance limits, in this paper, first the conventional algorithms are analyzed and their performances are compared, and then a new control algorithm is proposed. Furthermore, we try to improve the estimation performances of typical wave parameters including wave directions and significant wave heights by introducing linear regression model in the process of computing wave information extraction. Through several simulations with the X-band radar images, it is shown that the proposed method is very effective in estimating the wave information compared to the real measured buoy data.

• 한국ITS학회 논문지
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• 제7권5호
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• pp.180-183
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• 2008

본 논문은 교통망에서 관측 링크 교통량, 미관측 링크의 이용자평형 정보를 이용하여 O-D행렬을 수학적으로 생성하는 모형을 제시하고 있다. 교통량이 관측되지 않은 링크로부터 이용자 평형 상태에서 추출 가능한 정보를 바탕으로 일련의 논리적 연산을 거쳐 실제교통량에 근접하는 서브알고리듬을 유추하여 O-D행렬 추정의 정확도와 연산의 일관성을 제고하였다. 이를 위해 이용자평형상태에서 새로운 정리(Theorem)와 보조정리(Lemma)를 유도하여 적용하였다. 모형의 시험은 3개의 초기 O-D 행렬과 3개의 미관측 링크 교통량 시나리오를 각각의 모형에 적용하여 그 결과를 비교하였다. 적용 결과 본 논문에서 제시된 모형은 기존의 이용자균형 접근방식의 모형emf에 비해 추정된 O-D값의 실제 값과의 차이(O-D Trip RMSE)가 현저히 감소되는 것을 확인하였다.

• 교통기술과정책
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• 제12권5호
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• pp.13-18
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• 2015

• 대한교통학회:학술대회논문집
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• 대한교통학회 2007년도 제57회 학술발표회논문집
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• pp.960-968
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• 2007

• 대한교통학회:학술대회논문집
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• 대한교통학회 2007년도 제57회 학술발표회논문집
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• pp.277-286
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• 2007