• Journal of Auto-vehicle Safety Association
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• v.10 no.1
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• pp.38-44
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• 2018

This paper presents an analysis on driving safety in lane change situation based on road driving data. Autonomous driving is a global trend in vehicle industry. LKAS technologies are already applied in commercial vehicle and researches about lane change maneuver have been actively studied. In autonomous vehicle, not only safety control issue but also imitating human driving maneuver is important. Driving data analysis in lane change situation has been usually dealt with ego vehicle information such as longitudinal acceleration, yaw rate, and steering angle. For this reason, developing safety index according to surrounding vehicle information based on human driving data is needed. In this research, driving data is collected from perception module using LIDAR, radar and RT-GPS sensors. By analyzing human driving pattern in lane change maneuver, safety index that considers both ego vehicle and surrounding vehicle state by using relative velocity and longitudinal clearance has been designed.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.2
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• pp.31-35
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• 2000

An nonlinear observer-based longitudinal control law for vehicles is presented in this paper. It is assumed that for vehicle i knows only the distance between vehicle i and the preceding vehicle, i-1. An nonlinear state observer for vehicle I is developed to estimate the velocity and acceleration of the preceding vehicle, i-1. The communication of the position, velocity, and acceleration information is not used in the proposed method. It will be shown by mathematical analysis that the longitudinal control of vehicle can be implemented without an communication of the informations. It will be proven that the observation errors of the nonlinear states converge to zero asymptotically. To show the effectiveness of the proposed method, the simulation results are presented for the longitudinal control of the vehicle.

• Journal of Auto-vehicle Safety Association
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• v.15 no.4
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• pp.16-22
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• 2023

This paper presents a proactive longitudinal motion planning algorithm for improving the safety of an automated bus. Since the field of view (FOV) of the autonomous vehicle was limited depending on onboard sensors' performance and surrounding environments, it was necessary to implement vehicle-to-vehicle (V2V) communication for overcoming the limitation. After a virtual V2V-equipped target was constructed considering information obtained from V2V communication, the reference motion of the ego vehicle was determined by considering the state of both the V2V-equipped target and the sensor-detected target. Model predictive control (MPC) was implemented to calculate the optimal motion considering the reference motion and the chance constraint, which was deduced from manual driving data. The improvement in driving safety was confirmed through vehicle tests along actual urban roads.

• Journal of Auto-vehicle Safety Association
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• v.4 no.1
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• pp.12-17
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• 2012

ADAS(Advanced Driver Assistance System) which is developed for alleviating driver's load has become improved with extending it's role. Previously, ADAS offered simple function just to make driver's convenience. However, nowadays ADAS also acts as Active Safety system which is made to release and/or prevent accidents. Longitudinal control system, as one of major parts of Active Safety System, is assessed as doing direct effect on avoiding accidents. Therefore, many countries such as Europe and America has pushed longitudinal control system as a government-wide project. In this paper, it covers the result of evaluation system and vehicle evaluation for development study in FCW, ACC and AEB.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.113-113
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• 2000

A robust adaptive technique for the longitudinal control of a platoon of automated vehicles is presented. A nonlinear model is used to represent the vehicle dynamics of each vehicle within the platoon. The external disturbance such as wind gust and a disturbance term due to engine transmission variations and so on are considered. The state observer is used to avoid direct measurement of the relative velocity or acceleration between the controlled and leading vehicles or the controlled vehicle's acceleration. It is shown that platoon stability can be recovered in operation even if a speed dependent spacing policy is adopted, which incorporates a constant time headway in addition to the constant distance. The simulation results demonstrate excellent tracking even in the presence of disturbances.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.7
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• pp.202-213
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• 1999

Adaptive Cruise Control (ACC) is one of key features on intelligent Transportation System(ITS). In ACC, the steering is done by a driver, but the engine throttle valve and the brake are controlled electronically. The relative velocity and distance from the preceeding vehicle are measured by radars or image processing units and relevant vehicular spacing is maintained in ACC control systems. In this study, vehicle longitudinal dynamics are modeled to simulate vehicle longitudinal maneuver and to design longtitudinal controllers for ACC vehicles. The control algorithm is designed based on the modeled vehicle longitudinal dynamics using a non-linear sliding mode control method. To verity the performance of the control algorithm, a real time numerical simulation program is developed on a Silicon Graphics workstation using C-language . A real time graphic program is alos develpe and integrated with the numerical simulation program.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.408-412
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• 2003

Obstacle avoidance algorithm is very important on an unmanned vehicle. Therefore, in this research, we propose a algorithm of obstacle avoidance and we can prove through vehicle test and sensor experiments. Obstacle avoidance must be divided into two parts: the first part includes the longitudinal control for acceleration and deceleration and the second part is the lateral control for steering control. Each system is used for unmanned vehicle control, which notes its location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control strategy of the vehicle can detect obstacles and perform obstacle avoidance on the road, which involves vehicle velocity. In this paper, we propose a method for vehicle control, modeling, and obstacle avoidance, which are confirmed through vehicle tests.

• International Journal of Automotive Technology
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• v.4 no.4
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• pp.173-180
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• 2003

Obstacle avoidance is considered as one of the key technologies in an unmanned vehicle system. In this paper, we propose a method of obstacle avoidance, which can be expressed as vehicle control, modeling, and sensor experiments. Obstacle avoidance consists of two parts: one longitudinal control system for acceleration; and deceleration and a lateral control system for steering control. Each system is used for unmanned vehicle control, which notes its location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control strategy of the vehicle can detect obstacles and perform obstacle avoidance on the road, which involves vehicle velocity. The method proposed for vehicle control, modeling, and obstacle avoidance has been confirmed through vehicle tests.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.2
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• pp.92-97
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• 2000

The Lyapunov stability theorem is used to derive a control law that can be used to control the spacing between vehicles in a platoon. A third order system is adopted to model the vehicle and power-train dynamics. In addition, the concept of

• International Journal of Automotive Technology
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• v.6 no.4
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• pp.359-365
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• 2005

The absolute longitudinal speed of a vehicle is estimated by using data from an accelerometer of the vehicle and wheel speed sensors of a standard 50-tooth antilock braking system. An intuitive solution to this problem is, 'When wheel slip is low, calculate the vehicle velocity from the wheel speeds; when wheel slip is high, calculate the vehicle speed by integrating signal of the accelerometer.' The speed estimator weighted with fuzzy logic is introduced to implement the above concept, which is formulated as an estimation method. And the method is improved through experiments by how to calculate speed from acceleration signal and slip ratios. It is verified experimentally to usefulness of estimation speed of a vehicle. And the experimental result shows that the estimated vehicle longitudinal speed has only a $6\%$ worst-case error during a hard braking maneuver lasting a few seconds.