• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.2
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• pp.81-86
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• 2013

This paper presents the lane change system for collision avoidance. The proposed algorithm for the collision avoidance consists of path generation and path following. Using a calculated TTC (Time to Collision), partial braking is operated and collision avoidance path is generated considering relative distance, velocity and acceleration. Based on the collision avoidance path, desired yaw angle and yaw rate are calculated for the automated path following. The lateral controller is designed by a Lyapunov function approach using 3 D.O.F vehicle model and vehicle parameters. The required steering angle is determined from wheel velocity, longitudinal and lateral velocity in order to follow the desired yaw angle and yaw rate. This system is developed MATLAB/Simulink and its performance is evaluated using the commercial software CarSim.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.8
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• pp.233-247
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• 1999

Traffic accidents are normally caused by late or faulty judgements due to the driver's inaccurate estimation of the distance, velocity, and acceleration from the surrounding vehicles as well as his carelessness or inattention. Thus, the development of collision avoidance systems is motivated by their great potential for increased vehicle safety. A typical collision avoidance system consists of the forward-looking sensor, the criteria for activation of collision warming and avoidance, the collision avoidance maneuvers, and the user interface. This thesis is concerned with the development of a collision warning algorithm in which the driver is warned of approaching collision with the visual and/or the audible signals . The warning algorithm based on fuzzy logic is presented here based on new warning criteria. It has been newly derived from the conventional warning equation by adding a new input variable of the required deceleration to avoid collision. The algorithm is also able to adapt to the individual driver's taste along with the different road conditions by externally controlling the warning intensity. Finally , the proposed algorithm has been validated using computer simulation.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.107-112
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• 2022

The automotive industry is motivated to provide more and more amenities to its customers. The industry is taking advantage of artificial intelligence by increasing different sensors and gadgets in vehicles machoism is forward collision warning, at the same time road accidents are also increasing which is another concern to address. So there is an urgent need to provide an A.I based system to avoid such incidents which can be address by using artificial intelligence and global positioning system. Automotive/smart vehicles protection has become a major study of research for customers, government and also automotive industry engineers In this study a two layered novel hypothetical approach is proposed which include in-time vehicle/obstacle detection with auto warning mechanism for collision detection & avoidance and later in a case of an accident manifestation GPS & video camera based alerts system and interrupt generation to nearby ambulance or rescue-services units for in-time driver rescue.

• International Journal of Automotive Technology
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• v.3 no.2
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• pp.79-88
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• 2002

Emergent Collision Avoidance Systems (CAS's) are beginning to assist drivers by performing specific tasks and extending the limits of driver's perception. As CAS's evolve from simple systems handling discrete tasks to complex systems managing interrelated driving tasks, the risk of failure from hidden causes greatly increases. The successful implementation of such a complex system depends upon a robust software architecture. Host of the difficulty in implementing system arises from interconnections between the components. The CAS architecture presented in this paper focuses on these interconnections to mitigate this problem. Moreover, by constructing the GAS architecture through the composition of existing architectural styles, the resulting system will exhibit predictable qualities. Some of the qualities represent limitations that translate into constraints on the system. Others are beneficial aspects that satisfy stakeholder requirements .

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.2
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• pp.156-165
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• 2000

This paper describes modeling and simulation of automotive forward collision warning and avoidance system using CASE(Computer-Aided Systems Engineering) tool. The system is composed or many sensors, a controller, warning devices, brakes and etc. The system was modeled by one activity chart, fourteen state charts and one module chart. Rear-end collision scenarios was generated by Simulink and used to support Stalemate model. The resulting model was used to evaluate the correctness of function and behavior of the system. A simulator for the system has been designed and used to validate the model under realistic operating conditions in the laboratory. To model and simulate the system's functionality and behavior brings clarity to system design early in the system development.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.8
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• pp.784-790
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• 2009

A forward-looking automotive radar typically utilizes the frequency modulated continuous wave(FMCW) or pulsed-Doppler waveform for the Information acquisition of the target range and velocity. In order to obtain the high resolution target information, however, a narrow pulse width and wide bandwidth are inherently required, thus resulting in high peak power and high speed digital converter processing. In this paper, a stepped-frequency pulsed-Doppler(SFPD) waveform algorithm is proposed for high resolution forward looking automotive radar application. The performance of the proposed SFPD waveform technique is analyzed and compared with the conventional FMCW and PD method. Since this technique can be used for the high resolution target imaging with arbitrary range and Doppler resolution, it is expected to be useful In automotive radar target classification for the precision collision avoidance applications in the future.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.487-490
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• 2003

In this research, we will devise an obstacle avoidance algorithm for a previously unmanned vehicle. Whole systems consist mainly of the vehicle system and the control system. The two systems are separated; this system can communicate with the vehicle system and the control system through wireless RF (Radio Frequency) modules. These modules use wireless communication. And the vehicle system is operated on PIC Micro Controller. Obstacle avoidance method for unmanned vehicle is based on the Virtual Force Field (VFF) method. An obstacle exerts repulsive forces and the lane center point applies an attractive force to the unmanned vehicle. A resultant force vector, comprising of the sum of a target directed attractive force and repulsive forces from an obstacle, is calculated for a given unmanned vehicle position. With resultant force acting on the unmanned vehicle, the vehicle's new driving direction is calculated, the vehicle makes steering adjustments, and this algorithm is repeated.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.240-257
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• 2022

Autonomous vehicles use various local sensors such as camera, radar, and lidar to perceive the surrounding environment. However, it is difficult to predict the movement of vulnerable road users using only local sensors that are subject to limits in cognitive range. This is true especially when these users are blocked from view by obstacles. Hence, this paper developed an algorithm for collision avoidance with VRU using V2X information. The main purpose of this collision avoidance system is to overcome the limitations of the local sensors. The algorithm first evaluates the risk of collision, based on the current driving condition and the V2X information of the VRU. Subsequently, the algorithm takes one of four evasive actions; steering, braking, steering after braking, and braking after steering. A simulation was performed under various conditions. The results of the simulation confirmed that the algorithm could significantly improve the performance of the collision avoidance system while securing vehicle stability during evasive maneuvers.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.240-248
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• 1999

This paper presents a lane-change collision avoidance control algorithm for autonomous vehicles that will be used in AHS(Automated Highway System). In the proposed control algorithm, nominal control inputs are generated by solving the inverse vehicle dynamic equations of motion for a lane-change maneuver. In addition, a corrective steering input from preview as well as DYC (Direct Yaw Moment Control) may be included to reduce unpredictable errors and to insure yaw directional stability, respectively. The performance of the algorithm is evaluated with an ABS HILS system which consist of 17 DOF vehicle model and real ABS hardware parts. The HILS simulation results show that the proposed algorithm may be used for emergency lane-change maneuvers for autonomous vehicles.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.3
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• pp.241-249
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• 2014

This paper presents a path planning algorithm of an autonomous vehicle (ADAM III) for collision avoidance in the presence of multiple obstacles. Under the requirements that a low-cost GPS is used and its computation should be completed with a sampling time of sub-second, heading angle estimation is proposed to improve performance degradation of its measurement and a hierarchical structure for path planning is used. Once it is decided that obstacle avoidance is necessary, the path planning consists in three steps: waypoint generation, trajectory candidate generation, and trajectory selection. While the waypoints and the corresponding trajectory candidates are generated based on position of obstacles, the final desired trajectory is determined with considerations of kinematic constraints as well as an optimal condition in a term of lateral deviation. Finally the proposed algorithm was validated experimentally through field tests and its demonstration was performed in Autonomous Vehicle Competition (AVC) 2013.