Hyun-Yong Jeong

Crash Probability and Error Rates for Head-On Collisions Based on Stochastic Analyses

Active safety systems are developed in the automotive industry to help avoid or mitigate collisions. To develop collision-avoidance or mitigation systems, an appropriate lead time must be determined to provide a warning or action with acceptable false positive and negative rates. There has been much research on the lead time for the rear-end collision, but the lead time for the head-on collision has not been studied much because of the complexity of the loadcase. In this paper, the crash probabilities of the head-on collision were estimated, and adaptive lead times were proposed. In addition, false positive and false negative rates were assessed for some precrash sensor errors. For the assessment, an analytical vehicle model was validated against static and dynamic test data, and the drivers behaviors in normal and evasive maneuvers were surveyed and modeled. Using the analytical vehicle model and the driver models, stochastic analyses were conducted to assess the crash probability, the adaptive lead times, and the error rates.

Heat Aging Effects on the Material Property and the Fatigue Life of Vulcanized Natural Rubber, and Fatigue Life Prediction Equations

When natural rubber is used for a long period of time, it becomes aged; it usually becomes hardened and loses its damping capability. This aging process affects not only the material property but also the (fatigue) life of natural rubber. In this paper the aging effects on the material property and the fatigue life were experimentally investigated. In addition, several fatigue life prediction equations for natural rubber were proposed. In order to investigate the aging effects on the material property, the load-stretch ratio curves were plotted from the results of the tensile test, the compression test and the simple shear test for virgin and heat-aged rubber specimens. Rubber specimens were heat-aged in an oven at a temperature ranging from 50°C to 90°C for a period ranging from 2 days to 16 days. In order to investigate the aging effects on the fatigue life, fatigue tests were conducted for differently heat-aged hourglass-shaped and simple shear specimens. Moreover, finite element simulations were conducted for the specimens to calculate physical quantities occurring in the specimens such as the maximum value of the effective stress, the strain energy density, the first invariant of the Cauchy-Green deformation tensor and the maximum principal nominal strain. Then, four fatigue life prediction equations based on one of the physical quantities could be obtained by fitting the equations to the test data. Finally, the fatigue life of a rubber bush used in an automobile was predicted by using the prediction equations, and it was compared with the test data of the bush to evaluate the reliability of those equations.

A Novel Algorithm for Crash Detection Under General Road Scenes Using Crash Probabilities and an Interactive Multiple Model Particle Filter

Driver inattention causes the majority of vehicular crashes, and these accidents produce extensive economic and social costs, as well as injuries and fatalities. Thus, the development of imminent crash detection systems is one of the most important issues in automotive safety. Various crash detection algorithms have been proposed, but the coverage of these algorithms has been limited to one or two crash scenarios. To widen the coverage of crash detection systems to include various crash modes, driver behaviors that are dependent on road scenes and vehicle dynamics should be considered. This paper proposed an algorithm for detecting an imminent collision in general road scenes. The proposed algorithm consists of crash probability data generated from Monte Carlo simulations that consider driver behavior and vehicle dynamics, a tracking algorithm that uses an interactive multiple-model particle filter, and a threat assessment algorithm that estimates crash probabilities. To reduce nuisance and false-positive alarms, the algorithm discriminated between normal and dangerous road scenes, and a point of no return was detected using three driver models that addressed different levels of driver input. The performance of the proposed algorithm was evaluated under three scenarios, and it successfully discriminated between collision and near-miss cases, and it adjusted warning times depending on the road scenes. It is expected that the proposed algorithm would have good driver acceptability based on the results of the near-miss cases. The proposed algorithm can be used as an integrated crash detection algorithm for crash warning, avoidance, and mitigation purposes while incorporating tracking information from multiple sources.

An improved friction model and its implications for the slip, the frictional energy, and the cornering force and moment of tires

An improved friction model was proposed with consideration of the effect of the sliding speed, the contact pressure and the temperature, and it was implemented into a user subroutine of a commercial FEM code, ABAQUS/Explicit. Then, a smooth tire was simulated for free rolling, driving, braking and cornering situations using the improved friction model and the Coulomb friction model, and the effect of the friction models on the slip, the frictional energy distribution and the cornering force and moment was analyzed. For the free rolling, the driving and the braking situations, the improved friction model and the Coulomb friction model resulted in similar profiles of the slip and the frictional energy distributions although the magnitudes were different. The slips obtained from the simulations were in a good correlation with experimental data. For the cornering situation, the Coulomb friction model with the coefficient of friction of 1 or 2 resulted in lower or higher cornering forces and moments than experimental data. In addition, in contrast to experimental data it did not result in a maximum cornering force and a decrease of the cornering moment for the increase of the speed. However, the improved friction model resulted in similar cornering forces and moments to experimental data, and it resulted in a maximum cornering force and a decrease of the cornering moment for the increase of the speed, showing a good correlation with experimental data.

A Simple Vehicle Model for Path Prediction During Evasive Maneuvers and a Stochastic Analysis on the Crash Probability

Active safety systems are being developed in automotive industry, and an analytical vehicle model is needed in such systems to predict vehicle path to assess the crash probability. However, the bicycle model cannot result in a good correlation with test data and ADAMS simulation results, and other analytical vehicle models which have 8 or 14 degrees of freedom need more computation time. Therefore, in this study a simple analytical vehicle model was proposed to predict vehicle path especially during evasive maneuvers. The analytical vehicle model can predict a vehicle’s path based on the given vehicle speed and steering angle. In the analytical vehicle model, two different moment arms were used for inboard and outboard wheels, and lateral and longitudinal load transfers were taken into account. In addition, the magic formula tire model was used to estimate the lateral force. The analytical vehicle model has been validated with a sophisticated ADAMS model, and it resulted in a good correlation with test data. Using the simple analytical model, a stochastic analysis was conducted to analyze the effect of the initial offset amount and the heading angle on the crash probability. Another stochastic analysis was also conducted to analyze the effect of a sensing error on the false negative rate (FNR) and the false positive rate (FPR). It was found that the initial offset amount and the heading angle played a key role in the crash probability, and only FPR was affected noticeably by a sensing error.Copyright

A Crash Prediction Algorithm Using a Particle Filter and Bayesian Decision Theory

Active safety systems have been developed in automotive industry, and a tracking algorithm and a threat assessment algorithm are needed in such systems to predict the collision between vehicles. It is difficult to track a threat vehicle accurately because of lack of information on a threat vehicle and the measurement noise which does normally not follow Gaussian distribution. Therefore, there is an uncertainty whether the collision will occur or not. Particle filtering is widely used for nonlinear and non-Gaussian tracking problems, and statistical decision theory can be used to make an optimal decision in an uncertain case. In this study, a crash prediction algorithm has been developed using a particle filter and statistical decision making.Copyright

Finite element analyses for improved design of peripheral stents

Abstract Due to the recent increase in the number of stent insertion procedures, the number of studies to evaluate the mechanical behaviors of stents, such as the stress and deformation states, using finite element analysis is also increasing. However, it is still not easy to design stents that are uniformly expanded and show enough radial strength and flexibility. Therefore, in this study, the Taguchi method and finite element analysis were used to determine a set of optimal design variables for unit patterns of stents, and a new design approach was developed to realize uniform expansion, enough radial strength and good flexibility. The stent designed using the new design approach was verified by experiments.

A Fatigue Test Method for Tire Specimens

Crack growth in tires plays an important role in the durability of tires, and it is necessary to evaluate the characteristics of crack growth accurately. Since a tire is subjected to interlaminar shear stresses, a Mode III fatigue test method was developed. The fatigue life of three different tire specimens was measured by using the fatigue test method. Based on the fatigue test results, the effects of heat aging, temperature and belt stiffness on crack growth were analyzed.Copyright

A Fatigue Test to Assess the Deformation Behavior of Dental Implants

A purpose of this paper is to analyze the effects of material properties and design of a jig on fatigue test results of dental implants. An implant fatigue test method is specified in ISO14801 [1], but it is not described well about the fatigue test jig. The jig of ISO14801 has to firmly hold the fixture, and the elastic modulus of the jig should be more than 3 GPa. These requirements are not sufficient enough to represent the dental implant in the jawbone because the fixture is osseointegrated in the jawbone that is made up with the cortical bone and cancellous bone. In this paper three different materials were used for the jig, and two different fixation methods to hold the fixture were examined in several FE (Finite Element) simulations and fatigue tests. From the simulation and test results, the effects of material properties and design of the jig were evaluated in the light of fatigue life of dental implants.Copyright

The study on the evaluation of failure consequence and the adequacy of maintenance task for the air brake system of a railroad vehicle

In this study, the evaluation of failure consequence is performed including failure mode and effect in the brake system of railroad vehicle which have a priority in safety. In addition, base on the evaluated failure consequences, the adequacy of maintenance task is examined in the corresponding systems.