• Journal of Communications and Networks
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• v.15 no.2
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• pp.173-178
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• 2013

It is a concern that eco-driving vehicles, because their driving behavior differs from other vehicles due to e.g. e-start, may inhibit smooth traffic flow. Therefore, it is necessary to study the cooperative eco-driving done by a vehicle group, putting "vehicle-to-vehicle communication" and "road-to-vehicle communication" into perspective. Based on these factors, this study aimed to: 1) Analyze fuel consumption rates and driving behaviors of more than one vehicle following an Eco-Driving vehicle. 2) Examine the effect of information on the fuel consumption rate of the preceding vehicles on the following vehicles. As a result, the following findings were obtained: 1) By providing information to multiple following vehicles, the fuel consumption rate of the second vehicle was not lowered, while that of the third one was. 2) It is possible that, when information on fuel consumption of a preceding vehicle is provided to the following one, an inter-vehicular distance is shortened during deceleration to contribute to smooth traffic flow. From the above results, it is suggested that, when targeting a vehicle group, sharing the information on preceding vehicles is effective.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.203-207
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• 2006

Nowadays, Cars are continuing to grow at an alarming rate but they also cause many problems such as traffic accident, pollutions and so on. One of the most effective methods that prevent traffic accidents is the use of traffic monitoring systems, which are already widely used in many countries. The monitoring system is beginning to be used in domestic recently. An intelligent monitoring system generates photo images of cars as well as identifies cars by recognizing their plates. That is, the system automatically recognizes characters of vehicle plates. An automatic vehicle plate recognition consists of two main module: a vehicle plate locating module and a vehicle plate number identification module. We study for a vehicle plate number identification module in this paper. We use image preprocessing, feature extraction, multi-layer neural networks for recognizing characters of vehicle plates and we present a feature-comparison method for improving the performance of vehicle plate number identification module. In the experiment on identifying vehicle plate number, 300 images taken from various scenes were used. Of which, 8 images have been failed to identify vehicle plate number and the overall rate of success for our vehicle plate recognition algorithm is 98%.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.907-913
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• 1999

For an automated transportation system like PRT(Personal Rapid Transit) system or IVHS, an efficient vehicle-merging algorithm is required for smooth operation of the network. For management of merging, collision avoidance between vehicles, ride comfort, and the effect on traffic should be considered. This paper proposes an unmanned vehicle-merging algorithm that consists of two procedures. First, a longitudinal control algorithm is designed to keep a safe headway between vehicles in a single lane. Secondly, 'vacant slot and ghost vehicle' concept is introduced and a decision algorithm is designed to determine the sequence of vehicles entering a converging section considering energy consumption, ride comfort, and total traffic flow. The sequencing algorithm is based on fuzzy rules and the membership functions are determined first by an intuitive method and then trained by a learning method using a neural network. The vehicle-merging algorithm is shown to be effective through simulations based on a PRT model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.6
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• pp.21-36
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• 2015

These days Automated Vehicle(AV) has been receiving attention as a fundamental solution to resolve the various transportation problems and various researches related to the benefits of AV have been done. However, previous researches mainly analyzed the effects in the virtual network. The purpose of this research is to predict and to find out the benefits by introducing the Automated Vehicle to present road traffic system. Thus, the study analyzes the traffic-flow changes of Gyeongbu freeway Seoul-Singal basic section which is planned for setting the test-bed. The results show that Automated Vehicle can have negative effects on the traffic-flow in low volume of LOS A and B. However, the average speed increases and the traffic density decreases in more than LOS C, the traffic volume increase. Therefore, the introduction of Automated Vehicle achieves positive effect on various transportation problems such as the traffic congestion.

• Wind and Structures
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• v.20 no.2
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• pp.117-142
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• 2015

The performance of bridges under strong wind and traffic is of great importance to set the traveling speed limit or to make operational decisions for severe weather, such as controlling traffic or even closing the bridge. Meanwhile, the vehicle's safety is highly concerned when it is running on bridges or highways under strong wind. During the past two decades, researchers have made significant contributions to the simulation of the wind-vehicle-bridge system and their interactive effects. This paper aims to provide a comprehensive review of the overall performance of the bridge and traffic system under strong wind, including bridge structures and vehicles, and the associated mitigation efforts.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.161-165
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• 2005

In order to produce an optimal traffic cycle. We must first check how many waiting cars are at the lower intersection, because waiting queue is bigger than the length of upper traffic intersection. Start up delay time and vehicle waiting time occurs. To reduce vehicle waiting time, in this paper, we present an optimal green time algorithm using fuzzy neural network. Through computer simulation has been proven to be improved average vehicle speed than fixed traffic signal light which do not consider different intersection conditions.

• Journal of Auto-vehicle Safety Association
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• v.12 no.4
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• pp.70-77
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• 2020

In this study, we estimate the vehicle speed by analyzing the acoustic data recorded in a single microphone of a surveillance camera. The frequency analysis of the acoustic data corrects the Doppler effect, which is a characteristic of the moving sound source, and reflects the geometric relationship according to the location of the sound source and the microphone on the two-dimensional plane. The acoustic data is selected from the horn sound that is mainly observed in an urgent situation among various sound sources that may occur in a traffic accident, and the characteristics of the monotone source are considered. We verified the reliability of the proposed method by time domain acoustic analysis and actual vehicle evaluation. This method is effective and can be used for traffic accident analysis in the blind spot of the camera using a single microphone built into the existing surveillance camera.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.110-123
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• 2019

Traffic data is the most basic element necessary for transportation planning and traffic system operation. Recently, a method of estimating traffic flow characteristics using distance to a leading vehicle measured by an ADAS camera has been attempted. This study investigated the feasibility of the ADAS vehicle reflecting the distance error of image-based vehicle identification technology as a means to estimate the traffic flow through the normalized root mean square error (NRMSE) based on the number of lanes, traffic demand, penetration rate of probe vehicle, and time-space estimation area by employing the microscopic simulation model, VISSIM. As a result, the estimate of low density traffic flow (i.e., LOS A, LOS B) is unreliable due to the limitation of the maximum identification distance of ADAS camera. Although the reliability of the estimates can be improved if multiple lanes, high traffic demands, and high penetration rates are implemented, artificially raising the penetration rates is unrealistic. Their reliability can be improved by extending the time dimension of the estimation area as well, but the most influential one is the driving behavior of the ADAS vehicle. In conclusion, although it is not possible to accurately estimate the traffic flow with the ADAS camera, its applicability will be expanded by improving its performance and functions.

• Wind and Structures
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• v.24 no.3
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• pp.287-306
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• 2017

In the present study, a new assessment simulation of ride safety based on a new wind-traffic-pavement-bridge coupled vibration system is developed considering stochastic characteristics of traffic flow and bridge surface. Compared to existing simulation models, the new assessment simulation focuses on introducing the more realistic three-dimensional vehicle model, stochastic characteristics of traffic, vehicle accident criteria, and bridge surface conditions. A three-dimensional vehicle model with 24 degrees-of-freedoms (DOFs) is presented. A cellular automaton (CA) model and the surface roughness are introduced. The bridge deck pavement is modeled as a boundless Euler-Bernoulli beam supported on the Kelvin model. The wind-traffic-pavement-bridge coupled equations are established by combining the equations of both the vehicles in traffic, pavement, and bridge using the displacement and interaction force relationship at the patch contact. The numerical simulation shows that the proposed method can simulate rationally useful assessment and prevention information for traffic, and define appropriate safe driving speed limits for vulnerable vehicles under normal traffic and bridge surface conditions.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.5
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• pp.42-51
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• 2001

Vehicle detection is the basic of traffic monitoring. Video based systems have several apparent advantages compared with other kinds of systems. However, In video based systems, shadows make troubles for vehicle detection, especially active shadows resulted from moving vehicles. In this paper, a new method that combines background subtraction and edge detection is proposed for vehicle detection and shadow rejection. The method is effective and the correct rate of vehicle detection is higher than 98% in experiments, during which the passive shadows resulted from roadside buildings grew considerably. Based on the proposed vehicle detection method, vehicle tracking, counting, classification and speed estimation are achieved so that traffic parameters concerning traffic flow is obtained to describe the load of each lane.