• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.14-28
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• 2018

Thanks to technical improvement on the vehicle to vehicle communication and the intelligent transportation system, gradual introduction of the autonomous vehicles is expected soon in the market. The study analyzes the autonomous vehicles' impacts on the network efficiencies. In order to measure the network efficiencies, the study applies the sequential procedures that combines the microscopic and macroscopic simulations. The microscopic simulation attends to the capacity changes due to the autonomous vehicles' proportions on the roadway while the macroscopic simulation utilizes the simulation results in order to identify the network-wide improvement. As expected, the autonomous vehicles efficiently utilizes the existing capacity of the roadway than the human driving does. Particularly, the maximum capacity improvements are expected by the 190.5% on the expressway. The significant capacity change is observed when the autonomous vehicles' proportions are about 80% or more. These improvements are translated into the macroscopic model, which also yields overall network efficiency improvement by the autonomous vehicles' penetration. However, the study identifies that the market debut of the autonomous vehicles does not promise the free flow condition, which implies the possible needs of the system optimal routing scheme for the era of the autonomous vehicles.

• Journal of Korean Society of Transportation
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• v.34 no.2
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• pp.146-157
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• 2016

The objective of this study is to actualize a statistical model of the 3-detector simplification model, which was proposed to detect outbreak situations by Daganzo in 1997 and to verify the statistical appropriacy thereof. This study presents the calculation process of the 3-detector simplification model and realizes the process using a statistics program. Firstly, the model was applied using data on detector of the main highways on which there is no entrances or exits. Moreover, in order to statistically verify the 3-detector simplification model, accumulative traffics for 30 seconds period, which reflects the dynamic changes of traffics due to shock wave, were estimated for outbreak traffics and steady flow, and the error of acquired data was statistically compared with that of the actual accumulative traffics. As a result, the error ratio between steady and incident cumulative flows has reached its maximum after 2-3 hours from an accident. Moreover, the incident traffic flows by accidents and the stade flows are heterogeneous in terms of their dispersion and means.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.2
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• pp.167-175
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• 2020

The Two-fluid Model, proposed by Herman and Prigogine in 1979, is a macroscopic model for describing network operability in urban networks. Since the Two-fluid Model parameters change according to the traffic flow characteristics, it is necessary to identify the cause of flow change when analyzing the operability using the parameters. This study compared the crash risk according to rainfall using the Two-fluid Model parameters, and explained that the driving behavior affects the operability of the urban network. The results of the parameters estimation showed poor network operation under rainfall condition. The factors of drivers' crash risk perception model were calculated, and driving behavior was analyzed due to crash risk according to rainfall. In both the morning and evening, drivers tended to slow down their speeds to reduce the crash risk, because the risk on rainy days could be high when the speed was the same as on a sunny days. However, the crash risk was still higher on rainy days than sunny. In the future, it is necessary to analyze the relationship between the network operation and the crash risk in various networks and to improve both.

• Asian Journal of Innovation and Policy
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• v.11 no.1
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• pp.110-147
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• 2022

Many megacities are exposed to natural hazards such as earthquakes, and when located in coastal regions, are also vulnerable to hurricanes and tsunamis. The physical infrastructures of transportation systems in megacities have become so complicated that very few organizations can understand their response to extreme events such as earthquakes and can effectively mitigate subsequent economic downfalls. The technological advances made in recent years to support these complex systems have not grown as fast as the rapid demand on these systems burdened by population shift toward megacities. The objective of this paper is to examine the risks imposed on and recoveries of transportation systems in megacities as the result of extreme events such as an earthquake. First, the physical damage to transportation infrastructure, loss of the transportation system performance, and the corresponding economic loss from disruptions to passenger and freight traffic is evaluated. Then, traffic flows are re-routed to reduce vehicles' delay due to earthquakes using a microscopic traffic flow simulator with an optimization model and macroscopic terminal simulator. Finally, the economic impact of the earthquake is estimated nationwide. Southern California is regarded as the region of study. The results demonstrate the effectiveness of the integrated model and provide what and how to prepare innovative resilience policies of urban infrastructure for a natural disaster occurrence.

• Geomechanics and Engineering
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• v.35 no.5
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• pp.475-486
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• 2023

Ballast particles have an irregular shape and are discrete in nature. Due to the discrete nature of ballast, it exhibits complex mechanical behaviour under loading conditions. The discrete element method (DEM) can model the behaviour of discrete particles under a multitude of loading conditions. DEM is used in this paper to simulate a series of three-dimensional direct shear tests in order to investigate the shear behaviour of railway ballast and its interaction at the microscopic level. Particle flow code in three dimension (PFC3D) models the irregular shape of ballast particles as clump particles. To investigate the influence of particle size distribution (PSD), real PSD of Indian railway ballast specification IRS:GE:1:2004, China high-speed rail (HSR) and French rail specifications are generated. PFC3D built-in linear contact model is used to simulate the interaction of ballast particles under various normal stresses, shearing rate and shear box sizes. The results indicate how shear resistance and volumetric changes in ballast assembly are affected by normal stress, shearing rate, PSD and shear box size. In addition to macroscopic behaviour, DEM represents the microscopic behaviour of ballast particles in the form of particle displacement at different stages of the shearing process.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.1
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• pp.53-61
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• 1996

A clear understanding of the surface formation mechanism due to cutting is very important to help produce a good quality surface. Much of the roughness along the length of a bar being cut in a lathe can be explained in terms of macroscopic tool shape and feed rate. However, the roughness along the direction of cutting requires a different explanation. The formation of surface roughness is a problem in flow and fracture of materials in the vicinity of the tool edge. On a microscopic scale the cutting edge is rounded because it is impossible to grind a perfectly sharp cutting edge. Even if a perfectly sharp cutting edge were obtained it would soon become dull as a result of rapid breakdown and wear of the cutting edge. A research project is proposed in which in the main object is to model the surface formation mechanism due to cutting. The tool was assumed to be dull, that is, its edge has a finite radius. In order to study the effect of the radius of cutting edge on the surface formation, tools having different cutting edges were used. For orthogonal cutting experiment, cast iron and glass were chosen as brittle materials. Plowing forces acting in the cutting edge were estimated and its effect on the surface roughness was studied by observing the machined surface using optical microscope.

• Journal of Korean Society of Transportation
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• v.22 no.4 s.75
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• pp.147-158
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• 2004

A class of SWP(Stochastic Wane Propagation) models microscopically mimics individual vehicles' stochastic behavior and traffic jam propagation with simplified car-following models based on CA(Cellular Automata) theory and macroscopically captures dynamic traffic flow relationships based on statistical physics. SWP model, a program-oriented model using both discrete time-space and integer data structure, can simulate a huge road network with high-speed computing time. However, the model has shortcomings to both the capturing of low speed within a jam microscopically and that of the density and back propagation speed of traffic congestion macroscopically because of the generation of spontaneous jam through unrealistic collision avoidance. In this paper, two additional rules are integrated into the NaSch model. The one is SMR(Stopping Maneuver Rule) to mimic vehicles' stopping process more realistically in the tail of traffic jams. the other is LAR(Low Acceleration Rule) for the explanation of low speed characteristics within traffic jams. Therefore, the CA car-following model with the two rules prevents the lockup condition within a heavily traffic density capturing both the stopping maneuver behavior in the tail of traffic jam and the low acceleration behavior within jam microscopically, and generates more various macroscopic traffic flow mechanism than NaSch model's with the explanation of propagation speed and density of traffic jam.

• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.149-158
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• 2002

For the purpose of preciously describing real time traffic pattern in urban road network, dynamic network loading(DNL) models able to simulate traffic behavior are required. A number of different methods are available, including macroscopic, microscopic dynamic network models, as well as analytical model. Equivalency minimization problem and Variation inequality problem are the analytical models, which include explicit mathematical travel cost function for describing traffic behaviors on the network. While microscopic simulation models move vehicles according to behavioral car-following and cell-transmission. However, DNL models embedding such travel time function have some limitations ; analytical model has lacking of describing traffic characteristics such as relations between flow and speed, between speed and density Microscopic simulation models are the most detailed and realistic, but they are difficult to calibrate and may not be the most practical tools for large-scale networks. To cope with such problems, this paper develops a new DNL model appropriate for dynamic traffic assignment(DTA), The model is combined with vertical queue model representing vehicles as vertical queues at the end of links. In order to compare and to assess the model, we use a contrived example network. From the numerical results, we found that the DNL model presented in the paper were able to describe traffic characteristics with reasonable amount of computing time. The model also showed good relationship between travel time and traffic flow and expressed the feature of backward turn at near capacity.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.9
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• pp.932-940
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• 2011

This paper presents an integrated analysis of supply chain and financing decisions of multi-national corporation. We construct a model in which multiple currency storage units are installed to manage the currency flows associated with multi-national supply chain activities such as raw material procurement, process operation, inventory control, transportation and finished product sales. Core contribution of this study is to quantitatively investigate the influence of macroscopic economic factors such as exchange rates and taxes on operational decisions. The supply chain is modeled by the Process-Storage Network with recycle streams. The objective function of the optimization is minimizing the opportunity costs of annualized capital investments and currency/material inventories minus the benefit to stockholders interpreted by home currency. The major constraints of the optimization are that the material and currency storage units must not be depleted. A production and inventory analysis formulation, the periodic square wave (PSW) model, provides useful expressions for the upper/lower bounds and average levels of the currency and material inventory holdups. The expressions for the Kuhn-Tucker conditions of the optimization problem are reduced to a subproblem and analytical lot sizing equations. The procurement, production, transportation and financial transaction lot sizes can be determined by analytical expressions after the average flow rates are already known. We show that, when corporate income tax is taken into consideration, the optimal production lot and storage sizes are smaller than is the case when such factors are not considered typically by 20 %.