• Journal of Auto-vehicle Safety Association
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• v.5 no.1
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• pp.16-24
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• 2013

Some GM (General Motors) vehicles are using a GMLAN (General Motors Local Area Network) communication protocol for control and diagnostics. The airbag control module uses vehicle speed information from the GMLAN to record the vehicle speed as pre-crash information. In order to use the vehicle speed information for crash reconstruction purposes, it helps to be able to understand the accuracy of the data. The actual vehicle speed is not expected to be the same as the GMLAN indicated speed in some situations like a spin or if there is hard braking. This paper compares the actual vehicle speed and vehicle speed information during specific vehicle maneuvers. Actual vehicle speed is calculated from a GPS sensor, while GMLAN vehicle speed is calculated from transmission output sensor by the Engine control module (ECM). Vehicle maneuvers defined as Mode #1, Mode #2, Mode #3. The Mode #1 maneuver simulates wheel lock-up and skidding f by hard-braking at a specific speed. The Mode #2 maneuver simulates a 90degree turn using a J-turn maneuver at a specific speed. The Mode#3 maneuver simulates a 180 degree turn using a spin type of maneuver at a specific speed. The study then compares the GMLAN speed and GPS speed to see what speed difference exists between them. The results of this paper are applicable to GM vehicles only. This paper catalogs the performance and limitations of two vehicles as useful reference for crash reconstructions where there is a need to understand the speed indicated in the pre-crash section of the SDM data.

• Journal of Auto-vehicle Safety Association
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• v.9 no.2
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• pp.33-39
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• 2017

In recent days, crash safety system based on vehicle-to-vehicle communication (V2V) has been legislated. This V2V based safety system collects information from nearby vehicles to predict any crash possibility. Thus, it requires accurate and reliable data. Regularly updated features of Basic Safety Message(BSM) will be used to test validity of various elements included in the BSM. Then, the focus was made on whether values of these elements had notable differences compared to previous values. Through this paper, the validation tool was implemented and the result from V2V OBU experiment was used to identify problems in the current model and additional features that need to be implemented in V2V OBU for more accurate BSM.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.81-91
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• 2021

Last year, the Autonomous Vehicle Act was enacted to respond to deployment of autonomous vehicles. But the Act stipulates the operation of autonomous vehicle pilot zones, In addition, in order to analyze autonomous vehicle accidents and establish a reasonable damage compensation system, the Automobile Damage Compensation Guarantee Act was revised. But, It is necessary to seek plans for institutional development such as detailed concepts of self-driving cars and driving, a security certification system for securing safety of autonomous cooperative driving, and enhancement of the effectiveness of special cases related to personal information processing. I would like to seek ways to improve the legal system to respond reasonably to the deployment of autonomous vehicles.

• 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.7 no.3
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• pp.25-29
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• 2015

Research for Vehicle-to-Vehicle communication has been progressed in order to prevent accidents. In this paper, we decided the events that has high frequency accident of between vehicles on the road and we was arranged possible accident scenarios of each event; EEBL, LCW, BSD, FCW, PCW, IMA. When the event occurs between vehicles, we studied how to evaluate whether the information transmitted safely.

• Journal of Auto-vehicle Safety Association
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• v.14 no.3
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• pp.71-76
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• 2022

In autonomous driving cars, 3D pose estimation can be one of the effective methods to enhance safety control for OOP (Out of Position) passengers. There have been many studies on human pose estimation using a camera. Previous methods, however, have limitations in automotive applications. Due to unexplainable failures, CNN methods are unreliable, and other methods perform poorly. This paper proposes robust real-time multi-human 3D pose estimation architecture in vehicle using monocular RGB camera. Using particle filter, our approach integrates CNN 2D/3D pose measurements with available information in vehicle. Computer simulations were performed to confirm the accuracy and robustness of the proposed algorithm.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.70-74
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• 2022

This paper describes the development of a target vehicle state estimation algorithm using vehicle-to-vehicle (V2V) communication. Perceiving the state of the target vehicle has great importance for successful autonomous driving and has been studied using various sensors and methods for many years. V2V communication has advantage of not being constrained by surrounding circumstances relative to other sensors. In this paper, we adopt the V2V signal for estimating the target vehicle state. Since applying only the V2V signal is improper by its low frequency and latency, the signal is used as additional measured data to improve the estimation accuracy. We estimate the target vehicle state using Extended Kalman filter (EKF); a point mass model was utilized in process update to predict the state of next step. The process update is followed by measurement update when ego vehicle receives V2V information. The proposed study evaluated state estimation by comparing input V2V information in an experiment where the ego vehicle follows the target vehicle behind it.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.45-50
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• 2022

The vehicle motion in urban environment is determined by surrounding traffic flow, which cause understanding the flow to be a factor that dominantly affects the motion planning of the vehicle. The traffic flow in this urban environment is accessed using various urban infrastructure information. This paper represents a color recognition algorithm for traffic lights to perceive traffic condition which is a main information among various urban infrastructure information. Deep learning based vision open source realizes positions of traffic lights around the host vehicle. The data are processed to input data based on whether it exists on the route of ego vehicle. The colors of traffic lights are estimated through pixel values from the camera image. The proposed algorithm is validated in intersection situations with traffic lights on the test track. The results show that the proposed algorithm guarantees precise recognition on traffic lights associated with the ego vehicle path in urban intersection scenarios.

• Journal of Auto-vehicle Safety Association
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• v.8 no.3
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• pp.10-15
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• 2016

The purpose of this study is to evaluate the injury mechanism of facial injury related to an air-bag's deployment in occupant motor vehicle accident (MVA) by using Hospital Information System (HIS) and reconstruction program, based on the materials related to motor vehicle accidents. Among patients who visited the emergency department of Wonju Severance Christian Hospital due to motor vehicle accidents from August 2012 to February 2014, we collected data on patients with agreement for taking the damaged vehicle's photos. After obtaining the verbal consent from the patient, we asked about the cause of the accident, information on vehicle involved in the accident, and the location of car repair shop. The photos of the damaged vehicle were taken on the basis of front, rear, left side and right side. Damage to the vehicle was presented using the CDC code by analytical study of photo-images of the damaged vehicle, and a trauma score was used for medical examination of the severity of the patient's injury. Among the 309 patients with agreement for an investigation, thirty five (11.3 %) were the severe who had ISS over 15. And also, sixteen (5.2%) derived from the reconstructed data (maximum collision energy, maximum acceleration, delta V) by PC-Crash. As a result, ISS including the facial injuries was affected by the condition. It was high when the number of crash extent, the safety belt was not fastened, and the seating position of occupant and the direction of collision is same. For accurate analysis of the relationship between occupant injury and vehicle damage in MVAs, build-up of an in-depth database through carrying out various policies for motor vehicle accidents is necessary for sure.

• Journal of Multimedia Information System
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• v.5 no.2
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• pp.105-110
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• 2018

Autonomous cars require the integration of multiple communication systems for driving safety. Many carmakers unveil mirrorless concept cars aiming to replace rear and sideview mirrors in vehicles with camera monitoring systems, which eliminate blind spots and reduce risk. This paper presents optical vehicle-to-vehicle (V2V) communications for autonomous mirrorless cars. The flicker-free light emitting diode (LED) light sources, providing illumination and data transmission simultaneously, and a high speed camera are used as transmitters and a receiver in the OCC link, respectively. The rear side vehicle transmits both future action data and vehicle type data using a headlamp or daytime running light, and the front vehicle can receive OCC data from the camera that replaces side mirrors so as not to prevent accidents while driving. Experimental results showed that action and vehicle type information were sent by LED light sources successfully to the front vehicle's camera via the OCC link and proved that OCC-based V2V communications for mirrorless cars can be a viable solution to improve driving safety.