• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.1-9
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• 2012

In this paper, we propose a vision-based robust vehicle detection and inter-vehicle distance estimation algorithm for driving assistance system. We use the haar-like features of car rear-shadows, as well as the edge features for detecting of vehicles. The use of additional vehicle edge features greatly reduces the false-positive errors in the vehicle detection. And, after analyzing the conventional two inter-vehicle distance estimation methods: the location-based and the vehicle width-based, an improved inter-vehicle distance estimation algorithm which has the advantage of both method is proposed. Several experimental results show the effectiveness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.621-626
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• 2015

This paper presents a camera calibration method in order to estimate the lane detection and inter-vehicle distance estimation system for an automotive safety driving system. In order to implement the lane detection and vision-based inter-vehicle distance estimation to the embedded navigations or black box systems, it is necessary to consider the computation time and algorithm complexity. The process of camera calibration estimates the horizon, the position of the car's hood and the lane width for extraction of region of interest (ROI) from input image sequences. The precision of the calibration method is very important to the lane detection and inter-vehicle distance estimation. The proposed calibration method consists of three main steps: 1) horizon area determination; 2) estimation of the car's hood area; and 3) estimation of initial lane width. Various experimental results show the effectiveness of the proposed method.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.1
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• pp.79-85
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• 2017

Vehicular ad-hoc networks (VANETs) cause link disconnection problems due to the rapid speed and the frequent moving direction change of vehicles. Link disconnection in vehicle-to-vehicle communication is an important issue that must be solved because it decreases the reliability of packet forwarding. From the characteristics of VANETs, greedy forwarding protocols using the position information based on the inter-vehicle distance have gained attention. However, greedy forwarding protocols do not perform well in the urban environment where the direction of the vehicle changes greatly. It is because greedy forwarding protocols select the neighbor vehicle that is closest to the destination vehicle as the next transmission vehicle. In this paper, we propose a greedy anycast forwarding (GAF) protocol to improve the reliability of the inter-vehicle communication. The proposed GAF protocol combines the greedy forwarding scheme and the anycast forwarding method. Simulation results show that the GAF protocol can provide a better packet delivery rate than existing greedy forwarding protocols.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.5
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• pp.137-144
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• 2000

In this paper, a longitudinal control of the lead vehicle for a platoon in IVHS Regulation Layer is proposed. The backstepping method has been used for the controller design. This method has an advantage in that its stability need not be proven since the controller is designed based on the Lyapunov Function. The control object is that the lead vehicle tracks a reference velocity and maintains a safe distance between the inter-platoons while the followers are keeping the speed of the lead vehicle of a platoon. The coordinate of system is transformed to a new coordinate system for its convenience to design controller. The new coordinate system is composed of error and new error variable. The error is the difference between the safe distance and the actual distance of inter-platoons. A new error variable is the difference between the velocity of vehicle and the estimated state of a system operated by the virtual input. The Lyapunov function is obtained based on the variables of new coordinate system. In the computer simulation, several cases have been studied such as when the lead vehicle is tracking the optimal speed. or a lead vehicle of the following platoon tracks the velocity of the previous platoon while maintaining a safe distance. Also a nonlinear engine time constant case has been investigated. All the simulation results show that the designed controller satisfies the control object sufficiently.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.192-192
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• 2000

In this paper, a platoon merging is considered as a remote-controlled system with the state represented by a stochastic process. In this system, it becomes to encounter situations where a single decision maker controls a large number of subsystems, and observation and control signals are sent over a communication channel with finite capacity and significant transmission delays. Unlike classical estimation problem in which the observation is a continuous process corrupted by additive noise, there is a constraint that the observation must be coded and transmitted over a digital communication channel with finite capaci쇼. A recursive coder-estimator sequence is a state estimation scheme based on observations transmitted with finite communication capacity constraint. Using the coder-estimator sequence, the remote control station designs a feedback controller. In this paper, we introduce a stochastic model for the lead vehicle in a platoon of vehicles considering the angle between a road surface and a horizontal plane as a stochastic process. The simulation results show that the inter-vehicle distance and the deviation from the desired inter-vehicle distance are well regulated.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.6
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• pp.935-941
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• 2017

This paper proposes a method for estimating the distance betweeen vehicles in a moving situation using the image ratio of the distance between the tail lamps of a front vehicle. The actual distance between the tail lamps of a front vehicle was transmitted by LED tail lamps using visible light communication. As the distance between the front vehicle and the rear vehicle changes, it calculates the ratio of the pixel width between the tail lamps of the front vehicle projected on the image. The calculated values are used to derive a distance-mapping function through non-linear regression technique. Then, the distance between vehicles in the moving situation is estimated based on this function.

• The Journal of the Korea Contents Association
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• v.8 no.3
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• pp.47-54
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• 2008

In order to realize Intelligent Transport System (ITS) without any road facilities support, Inter-vehicle Communication (IVC) is increased attention. IVC makes it possible to exchange real-time information among vehicles without centralized infrastructure. The IVC systems use multi-hop broadcast to disseminate information. In this paper, we propose the improved AODV routing protocol based on location information. The proposed AODV routing protocol transmits Hello packet with location information to calculate the distance between nodes. Then it achieves fast link recovery. We confirm the throughput performance of the proposed AODV routing protocol compared with the AODV routing protocol using Qualnet ver.3.8 simulator.

• Journal of Advanced Navigation Technology
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• v.4 no.2
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• pp.143-151
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• 2000

In this paper, short range IVC(Inter-Vehicle Communication) channel is modeled in three kinds considering rain attenuation and oxygen absorption. And the performance of DS/CDMA communication system in one path Rician model suitable for platton driving which is the final goal of AVHS(Advanced Vehicle & Highway System) is analyzed. Also, the reflection coefficients in 60 GHz is calculated. For the performance improvement both BCH channel coding and MRC diversity reception technique are adopted. The BER performance is evaluated as a function of packet length, Rician depth and the distance between vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.73-82
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• 2022

Driver acceptance of autonomous driving is very important. The autonomous driving longitudinal controller, which is one of the factors affecting acceptability, consists of a high-level controller and a low-level controller. The host controller decides the cruise control and the space control according to the situation and creates the required target speed. The sub-controller performs control by creating an acceleration signal to follow the target speed. In this paper, we propose an algorithm to improve the inter-vehicle distance fluctuations that occur in the cruise control and space control switching problems in the host controller. The proposed method is to add an approach algorithm to the cruise control at the time of switching from cruise control to space control so that it is switched to space control at the correct switching distance. Through this, the error was improved from 12m error to 4m, and actual vehicle verification was performed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2098-2114
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• 2021

Light intensity variation is one of the key factors which affect the accuracy of vehicle face re-identification, so in order to improve the robustness of vehicle face features to light intensity variation, a Nonnegative Matrix Factorization model with the constraint of image acquisition time difference is proposed. First, the original features vectors of all pairs of positive samples which are used for training are placed in two original feature matrices respectively, where the same columns of the two matrices represent the same vehicle; Then, the new features obtained after decomposition are divided into stable and variable features proportionally, where the constraints of intra-class similarity and inter-class difference are imposed on the stable feature, and the constraint of image acquisition time difference is imposed on the variable feature; At last, vehicle face matching is achieved through calculating the cosine distance of stable features. Experimental results show that the average False Reject Rate and the average False Accept Rate of the proposed algorithm can be reduced to 0.14 and 0.11 respectively on five different datasets, and even sometimes under the large difference of light intensities, the vehicle face image can be still recognized accurately, which verifies that the extracted features have good robustness to light variation.