• Title/Summary/Keyword: Traffic Flow

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Simulation Experiments for Ubiquitous Traffic Flow Management (유비쿼터스 환경에서 최적교통관리를 위한 시뮬레이션 평가)

  • Park, Eun-Mi;Go, Myeong-Seok
    • Journal of Korean Society of Transportation
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    • v.27 no.3
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    • pp.71-77
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    • 2009
  • The ubiquitous transportation system environments make it possible to collect each vehicle's position and velocity data and to perform more sophisticated traffic flow management at individual vehicle or platoon level through V2V and V2I communications. The VISSIM simulation experiments were performed to address the issues in developing the preventive congestion management algorithm proposed in the companion paper. Traffic flow stability measures were developed based on the platoon profile, which enables us to explicitly consider traffic flow stability in traffic flow management. Traffic flow management strategies according to the traffic flow states were proposed: Maintain the equilibrium speed for free flow state, maintain the traffic flow stability by platoon control for critical state, and surpress the shock wave propagation for congested state. And finally potential benefit of the proposed traffic flow management scheme was evaluated based on the simulation experiment results. It is considered that extensive field experiments should be performed to confirm the simulated results.

TRAFFIC FLOW MODELS WITH NONLOCAL LOOKING AHEAD-BEHIND DYNAMICS

  • Lee, Yongki
    • Journal of the Korean Mathematical Society
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    • v.57 no.4
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    • pp.987-1004
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    • 2020
  • Motivated by the traffic flow model with Arrhenius looka-head relaxation dynamics introduced in [25], this paper proposes a traffic flow model with look ahead relaxation-behind intensification by inserting look behind intensification dynamics to the flux. Finite time shock formation conditions in the proposed model with various types of interaction potentials are identified. Several numerical experiments are performed in order to demonstrate the performance of the modified model. It is observed that, comparing to other well-known macroscopic traffic flow models, the model equipped with look ahead relaxation-behind intensification has both enhanced dispersive and smoothing effects.

Analysis of Characteristics of the Dynamic Flow-Density Relation and its Application to Traffic Flow Models (동적 교통량-밀도 관계의 특성 분석과 교통류 모형으로의 응용)

  • Kim, Young-Ho;Lee, Si-Bok
    • Journal of Korean Society of Transportation
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    • v.22 no.3
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    • pp.179-201
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    • 2004
  • Online traffic flow modeling is attracting more attention due to intelligent transport systems and technologies. The flow-density relation plays an important role in traffic flow modeling and provides a basic way to illustrate traffic flow behavior under different traffic flow and traffic density conditions. Until now the research effort has focused mainly on the shape of the relation. The time series of the relation has not been identified clearly, even though the time series of the relation reflects the upstream/downstream traffic conditions and should be considered in the traffic flow modeling. In this paper the flow-density relation is analyzed dynamically and interpreted as a states diagram. The dynamic flow-density relation is quantified by applying fuzzy logic. The quantified dynamic flow-density relation builds the basis for online application of a macroscopic traffic flow model. The new approach to online modeling of traffic flow applying the dynamic flow-density relation alleviates parameter calibration problems stemming from the static flow-density relation.

Traffic Flow Sensing Using Wireless Signals

  • Duan, Xuting;Jiang, Hang;Tian, Daxin;Zhou, Jianshan;Zhou, Gang;E, Wenjuan;Sun, Yafu;Xia, Shudong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.10
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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.

On Visualization of Trajectory Data for Traffic Flow Simulation of Urban-scale (도시 스케일의 교통 흐름 시뮬레이션을 위한 궤적 데이터 시각화)

  • Choi, Namshik;Onuean, Athita;Jung, Hanmin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • pp.582-585
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    • 2018
  • As traffic volume increases and road networks become more complicated, identifying for accurate traffic flow and driving smooth traffic flow are a concern of many countries. There are various analytical techniques and studies which desire to study about effective traffic flow. However, the necessary activity is finding the traffic flow pattern through data visualization including location information. In this paper aim to study a real-world urban traffic trajectory and visualize a pattern of traffic flow with a simulation tool. Our experiment is installing the sensor module in 40 taxis and our dataset is generated along 24 hours and unscheduled routes. After pre-processing data, we improved an open source traffic visualize tools to suitable for our experiment. Then we simulate our vehicle trajectory data with a dots animation over a period of time, which allows clearly view a traffic flow simulation and a understand the direction of movement of the vehicle or route pattern. In addition we further propose some novel timelines to show spatial-temporal features to improve an urban environment due to the traffic flow.

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Hybrid CSA optimization with seasonal RVR in traffic flow forecasting

  • Shen, Zhangguo;Wang, Wanliang;Shen, Qing;Li, Zechao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.10
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    • pp.4887-4907
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    • 2017
  • Accurate traffic flow forecasting is critical to the development and implementation of city intelligent transportation systems. Therefore, it is one of the most important components in the research of urban traffic scheduling. However, traffic flow forecasting involves a rather complex nonlinear data pattern, particularly during workday peak periods, and a lot of research has shown that traffic flow data reveals a seasonal trend. This paper proposes a new traffic flow forecasting model that combines seasonal relevance vector regression with the hybrid chaotic simulated annealing method (SRVRCSA). Additionally, a numerical example of traffic flow data from The Transportation Data Research Laboratory is used to elucidate the forecasting performance of the proposed SRVRCSA model. The forecasting results indicate that the proposed model yields more accurate forecasting results than the seasonal auto regressive integrated moving average (SARIMA), the double seasonal Holt-Winters exponential smoothing (DSHWES), and the relevance vector regression with hybrid Chaotic Simulated Annealing method (RVRCSA) models. The forecasting performance of RVRCSA with different kernel functions is also studied.

A Calibration of the fundamental Diagram on the Type of Expressway (고속도로 유형별 교통류 모형 정산)

  • Yoon, Jae-Yong;Lee, Eui-Eun;Kim, Hyunmyung;Han, Dong-Hee;Lee, Dong-Youn;Lee, Choong-Shik
    • International Journal of Highway Engineering
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    • v.16 no.4
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    • pp.119-126
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    • 2014
  • PURPOSES: Used in transportation planning and traffic engineering, almost traffic simulation tools have input variable values optimized by overseas traffic flow attribution because they are almost developed in overseas country. Thus, model calibration appropriated for internal traffic flow attribution is needed to improve reliability of simulation method. METHODS : In this study, the traffic flow model calibration is based on expressways. For model calibration, it needs to define each expressway link according to attribution, thus it is classified by design speed, geometric conditions and number of lanes. And modified greenshield model is used as traffic flow model. RESULTS : The result of the traffic model calibration indicates that internal congested density is lower than overseas. And the result of analysis according to the link attribution indicates that the more design speed and number of lanes increase, the lower the minimum speed, the higher the congested density. CONCLUSIONS: In the traffic simulation tool developed in overseas, the traffic flow is different as design speed and number of lanes, but road segment don't affect traffic flow. Therefore, these results need to apply reasonably to internal traffic simulation method.

The Analysis of Traffic Flow Characteristics on Moving Bottleneck (연속류 시설의 이동병목구간에서 지체산정방법 -모의실험을 통한 교통류의 평균지체분석-)

  • Kim, Won-Kyu;Jeong, Myeong-Kyu;Kim, Byung-Jong;Seo, Eun-Chae;Kim, Song-Ju
    • Journal of The Institute of Information and Telecommunication Facilities Engineering
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    • v.8 no.4
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    • pp.170-181
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    • 2009
  • When a slow-moving vehicle occupies one of the lanes of a multi-lane highway, it often causes queuing behind, unlike one is caused by an actual stoppage on that lane. This happens when the traffic flow rate upstream from the slow vehicle exceeds a certain critical value. This phenomena is called as the Moving Bottleneck, defined by Gazis and Herman (1992), Newell (1998) [3], and Munoz and Daganzo (2002), who conducted the flow estimates of upstream and downstream and considered slow-moving vehicle speed and the flow ratio exceeding slow vehicle and the microscopic traffic flow characteristics of moving bottleneck. But, a study of delay on moving bottleneck was not conducted until now. So this study provides a average delay time model related to upstream flow and the speed of slow vehicle. We have chosen the two-lane highway and homogeneous traffic flow. A slow-moving vehicle occupies one of the two lanes. Average delay time value is a result of AIMSUN[9], the microscopic traffic flow simulator. We developed a multiple regression model based on that value. Average delay time has a high value when the speed of slow vehicle is decreased and traffic flow is increased. Conclusively, the model is formulated by the negative exponential function.

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Methodology for Real-time Detection of Changes in Dynamic Traffic Flow Using Turning Point Analysis (Turning Point Analysis를 이용한 실시간 교통량 변화 검지 방법론 개발)

  • KIM, Hyungjoo;JANG, Kitae;KWON, Oh Hoon
    • Journal of Korean Society of Transportation
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    • v.34 no.3
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    • pp.278-290
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    • 2016
  • Maximum traffic flow rate is an important performance measure of operational status in transport networks, and has been considered as a key parameter for transportation operation since a bottleneck in congestion decreases maximum traffic flow rate. Although previous studies for traffic flow analysis have been widely conducted, a detection method for changes in dynamic traffic flow has been still veiled. This paper explores the dynamic traffic flow detection that can be utilized for various traffic operational strategies. Turning point analysis (TPA), as a statistical method, is applied to detect the changes in traffic flow rate. In TPA, Bayesian approach is employed and vehicle arrival is assumed to follow Poisson distribution. To examine the performance of the TPA method, traffic flow data from Jayuro urban expressway were obtained and applied. We propose a novel methodology to detect turning points of dynamic traffic flow in real time using TPA. The results showed that the turning points identified in real-time detected the changes in traffic flow rate. We expect that the proposed methodology has wide application in traffic operation systems such as ramp-metering and variable lane control.

An Ensemble Cascading Extremely Randomized Trees Framework for Short-Term Traffic Flow Prediction

  • Zhang, Fan;Bai, Jing;Li, Xiaoyu;Pei, Changxing;Havyarimana, Vincent
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.4
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    • pp.1975-1988
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    • 2019
  • Short-term traffic flow prediction plays an important role in intelligent transportation systems (ITS) in areas such as transportation management, traffic control and guidance. For short-term traffic flow regression predictions, the main challenge stems from the non-stationary property of traffic flow data. In this paper, we design an ensemble cascading prediction framework based on extremely randomized trees (extra-trees) using a boosting technique called EET to predict the short-term traffic flow under non-stationary environments. Extra-trees is a tree-based ensemble method. It essentially consists of strongly randomizing both the attribute and cut-point choices while splitting a tree node. This mechanism reduces the variance of the model and is, therefore, more suitable for traffic flow regression prediction in non-stationary environments. Moreover, the extra-trees algorithm uses boosting ensemble technique averaging to improve the predictive accuracy and control overfitting. To the best of our knowledge, this is the first time that extra-trees have been used as fundamental building blocks in boosting committee machines. The proposed approach involves predicting 5 min in advance using real-time traffic flow data in the context of inherently considering temporal and spatial correlations. Experiments demonstrate that the proposed method achieves higher accuracy and lower variance and computational complexity when compared to the existing methods.