• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.3
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• pp.90-99
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• 2020

The "Low Emission Zone" (LEZ) system restricts entry of vehicles with high air pollutants into city centers. Implementation of the system improves air environment around the world. Since 2012, operating restrictions have been applied to all of Seoul's metropolitan areas and some other metropolitan areas in the state. Beginning in December 2019, entry of 5th class vehicles to the central green transport zone of Seoul has been restricted. In this study we examine the status of operational restrictions in this zone, and predict the amount of traffic reduction expected when numbers of target vehicles are expanded in the future, we use data for each vehicle's emission grade: by region and 'Origin-Destination Traffic Volume'. After estimating the amount of traffic entering Seoul's 25 autonomous districts, by emission class, we propose a target region that may have a significant effect if target areas for automobile operation restrictions expand in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.3
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• pp.85-93
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• 2016

According to Traffic Accident Statistics, the fatalities of accident while crossing is over represented. So, more active safety countermeasure should be considered to reduce the frequency and degree of severity of pedestrian-crossing involved accidents. The study analyses the safety effects of the Crossing Safety Assistant System which is composed of Led-embedded crosswalk lightings, text displayer and audio waning device for the safety consciousness both pedestrian and vehicles at crosswalk area. Operating speed of vehicles is reduced with statistical significance, and the level of vigilance expressed by pedestrian head movement to check out the vehicle existence is improved.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.112-123
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• 2018

The C-ARS(Cooperative Automated Roadway System) refers to a road infrastructure system that links automated vehicles with road infrastructure and communicates with each other via V2X communication to support automated vehicles. The purpose of this study is to suggest a performance evaluation method of C-ARS service. This study exemplifies the 'Work zone information service' among I2V service that provide information to automated vehicles in road infrastructure. First, we define the requirements and service scope needed to check the use case analysis and service performance of the service, and propose an evaluation system for performance evaluation of these services. In addition, the evaluation system was used to verify the feasibility of evaluation through the field test of 'Work zone information service'.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.441-447
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• 2012

This paper presents a design technique of a Takagi-Sugeno (T-S) fuzzy-model-based $H_{\infty}$ controller for autonomous underwater vehicles (AUVs). The design procedure aims to render the stabilizing controller which satisfies performance of the diving control for AUVs in the presence of the disturbance. A nonlinear AUV is modeled by the T-S fuzzy system through the sector nonlinearity. By using Lyapunov function, the sufficient conditions are derived to guarantee the performance of robust depth control in the format of linear matrix inequality (LMI). To succeed for diving control of AUV, we add the constraints on the diving and pitch angles in the LMI conditions. Through the simulation, we confirm the effectiveness of the proposed methodology.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.4
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• pp.87-94
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• 2013

This study estimated the changes in delays and speeds of vehicles in exclusive bus lane and road when the High Occupancy Vehicles(HOV) use the median bus lane. Synchro simulation tool was used to optimize the traffic signal time on the network and VISSIM was applied to simulate various scenarios. Here, drivers behavior parameters in VISSIM was optimized using Simultaneous Perturbation Stochastic Approximation(SPSA) algorithm in order to represent real traffic condition. Based on the simulation results, the delay in Doan daero was decreased when the volume of HOV in current condition runs on the median bus lane, whereas delay in Doan dongro was increased in all scenarios. The changes in bus speed was not sharply decreased for both study sites, even though the number of HOV increased to 10%. Thus, it could be allowed that the HOV use the median bus lane in Doan dongro and Doan daero. Future research tasks include studying about changes in delay when the HOV use the curb bus lane.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4228-4247
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• 2018

Many methods have been developed for the vehicles to create clusters in vehicular ad hoc networks (VANETs). Usually, nodes are vehicles in the VANETs, and they are dynamic in nature. Clusters of vehicles are made for making the communication between the network nodes. Cluster Heads (CHs) are selected in each cluster for managing the whole cluster. This CH maintains the communication in the same cluster and with outside the other cluster. The lifetime of the cluster should be longer for increasing the performance of the network. Meanwhile, lesser the CH's in the network also lead to efficient communication in the VANETs. In this paper, a novel algorithm for clustering which is based on the social behavior of Gray Wolf Optimization (GWO) for VANET named as Intelligent Clustering using Gray Wolf Optimization (ICGWO) is proposed. This clustering based algorithm provides the optimized solution for smooth and robust communication in the VANETs. The key parameters of proposed algorithm are grid size, load balance factor (LBF), the speed of the nodes, directions and transmission range. The ICGWO is compared with the well-known meta-heuristics, Multi-Objective Particle Swarm Optimization (MOPSO) and Comprehensive Learning Particle Swarm Optimization (CLPSO) for clustering in VANETs. Experiments are performed by varying the key parameters of the ICGWO, for measuring the effectiveness of the proposed algorithm. These parameters include grid sizes, transmission ranges, and a number of nodes. The effectiveness of the proposed algorithm is evaluated in terms of optimization of number of cluster with respect to transmission range, grid size and number of nodes. ICGWO selects the 10% of the nodes as CHs where as CLPSO and MOPSO selects the 13% and 14% respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.4
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• pp.107-121
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• 2017

This study conducted a 3-stage survey and simulation experiment to identify the impact of vehicle platoons on car-following behavior of manually-driven vehicles. Vehicle maneuvering data obtained from driving simulations was statistically analyzed based on three measures including average speed, acceleration noise, and offset to represent the deviation of lateral movements. Results indicate that MV drivers tended to have psychological burden while driving in automated vehicle platooning environments, which resulted in different vehicle maneuvers. It is expected that the outcome of this study would be useful fundamentals in developing various traffic operations strategies for managing mixed traffic stream consisting of MVs and autonomous vehicles.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5135-5142
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• 2011

A flexible mechanism is proposed in this paper to improve the dynamic response performance of a traffic flow control system in an urban area. The roads, vehicles, and traffic control systems are all modeled as intelligent systems, wherein a wireless communication network is used as the medium of communication between the vehicles and the roads. The necessary sensor networks are installed in the roads and on the roadside upon which reinforcement learning is adopted as the core algorithm for this mechanism. A traffic policy can be planned online according to the updated situations on the roads, based on all the information from the vehicles and the roads. This improves the flexibility of traffic flow and offers a much more efficient use of the roads over a traditional traffic control system. The optimum intersection signals can be learned automatically online. An intersection control system is studied as an example of the mechanism using Q-learning based algorithm, and simulation results showed that the proposed mechanism can improve the traffic efficiency and the waiting time at the signal light by more than 30% in various conditions compare to the traditional signaling system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.6
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• pp.103-110
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• 2012

In Vehicle Safety Communication (VSC), noted as a representative application of VANET technologies, emergency warning messages (EWM) are broadcast over vehicles in response to an emergency situation. However, as the number of vehicles increases, the so-called Broadcast Storm Problem often occurs due to a huge number of redundant EWM transmitted. Though many approaches in the literature have been proposed to solve the problem, most of them require the preliminary phase for setting up or refreshing neighbor relationship through exchanging beacon messages with nearby vehicles, thereby further increasing the traffic load. In this paper, we propose Longest Leaping Relay (LLR) scheme which can efficiently solve the Broadcast Storm Problem without any preliminary phase for setting up neighbor relationship. Through computer simulations, we compared the performance of the proposed scheme with competitive schemes and verified the proposed scheme outperforms the existing schemes.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.75-82
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• 2021

The number of traffic accidents is about 230,000, and due to non-recurring congestion and high driving speed, the number of deaths per traffic accident on freeways is more than twice compared to other roads. Currently, traffic information is provided based on nodes and links using the centerline of the road, but it does not provide detailed speed information. Recently, installing sensors for vehicles to monitor obstacles and measure location is becoming common not only for autonomous vehicles but also for ordinary vehicles as well. The analysis using large-capacity location-based data from such sensors enables real time service according to processing speed. This study presents an mapping method for individual vehicle data analysis based on space. The processing speed of large-capacity data was increased by using method which applied a quaternary notation basis partition method that splits into two directions of longitude and latitude respectively. As the space partition was processed, the average speed was similar, but the speed standard deviation gradually decreased, and decrease range became smaller after 9th partition.