Drowsy behavior detection based on driving information

Drowsy behavior is more likely to occur in sleep-deprived drivers. Individuals’ drowsy behavior detection technology should be developed to prevent drowsiness related crashes. Driving information such as acceleration, steering angle and velocity, and physiological signals of drivers such as electroencephalogram (EEG), and eye tracking are adopted in present drowsy behavior detection technologies. However, it is difficult to measure physiological signal, and eye tracking requires complex experiment equipment. As a result, driving information is adopted for drowsy driving detection. In order to achieve this purpose, driving experiment is performed for obtaining driving information through driving simulator. Moreover, this paper investigates effects of using different input parameter combinations, which is consisted of lateral acceleration, longitudinal acceleration, and steering angles with different time window sizes (i.e. 4 s, 10 s, 20 s, 30 s, 60 s), on drowsy driving detection using random forest algorithm. 20 s-size datasets using parameter combination of accelerations in lateral and longitudinal directions, compared to the other combination cases of driving information such as steering angles combined with lateral and longitudinal acceleration, steering angles only, longitudinal acceleration only, and lateral acceleration only, is considered the most effective information for drivers’ drowsy behavior detection. Moreover, comparing to ANN algorithm, RF algorithm performs better on processing complex input data for drowsy behavior detection. The results, which reveal high accuracy 84.8 % on drowsy driving behavior detection, can be applied on condition of operating real vehicles.     

Effect of steady airflow field on drag and downforce

The purpose of this study is to examine the effect of the steady airflow field of a rear spoiler on the coefficients of drag (C_D) and downforce (C_DF). The type of spoiler is suggested as a two-jointed arm model that mimics the flapping flight mechanism of the Canada goose. Computational fluid dynamics (CFD) technique was used for the steady airflow analysis of a vehicle implemented with various spoiler topologies. We evaluated C_D and C_DF due to the three types of airfoils and the five phases of each airfoil. We obtained the following conclusions from the results: (1) We found that the best cases for C_D and C_DF were the case of Phase 5 and symmetry airfoil, and the case of Phase 1 and reverse airfoil, respectively. (2) It is clear that C_D becomes the largest at Phase 1 of the reverse airfoil, since the eddy magnitude at the rear of the vehicle is the largest, and C_DF also becomes the largest during that phase, since the pressure distribution on the upper surface of the spoiler is very large. (3) As Phase 1 moves to Phase 5 in the same type of airfoil, it is advantageous for C_D and disadvantageous for C_DF, respectively.     

Impact phase in frontal vehicle-pedestrian collisions

The paper presents an alternative model developed in order to determine the pedestrian throw distance, taking into account ten distinct parameters. The collision dynamics, after the primary and secondary impact (pedestrian’s head hitting the vehicle windshield-hood area) between the vehicle and the pedestrian, entails the pedestrian ‘carrying’ phase onto the vehicle hood-windshield. Other parameters influencing the pedestrian throw distance, such as road inclination, friction coefficient between the pedestrian and the ground, vehicle and pedestrian mass, pedestrian launch angle are considered for the analysis. A comparison between the results obtained through the formula proposed in this paper and the results obtained by other researchers as well as a comparison with the results extracted from the casuistry analyzed by the authors on both accident reconstruction and laboratory tests is carried out.     

Robust estimation of maximum tire-road friction coefficient considering road surface irregularity

An accurate estimation of the maximum tire-road friction coefficient may provide higher performance in a vehicle active safety control system. Unfortunately, real-time tire-road friction coefficient estimation is costly and necessitates additional sensors that must be installed and maintained at all times. This paper proposes an advanced longitudinal tire-road friction coefficient estimation method that is capable of considering irregular road surfaces. The proposed algorithm uses a stiffness based estimation method, however, unlike previous studies, improvements were made by suggesting a third order model to solve problems related to nonlinear mu-slip curve. To attain the tire-road friction coefficient, real-time normalized force is obtained from the force estimator as exerted from the tire in the low slip region using the recursive least squares method. The decisive aspect of using the suggested algorithm lies in its low cost and versatility. It can be used under irregular road conditions due to its capability of easily obtaining wheel speed and acceleration values from production cars. The newly improved algorithm has been verified to computer simulations as well as compact size cars on dry asphalt conditions.     

Estimation of vehicle sideslip angle and tire-road friction coefficient based on magnetometer with GPS

This paper presents a method that estimates the vehicle sideslip angle and a tire-road friction coefficient by combining measurements of a magnetometer, a global positioning system (GPS), and an inertial measurement unit (IMU). The estimation algorithm is based on a cascade structure consisting of a sensor fusing framework based on Kalman filters. Several signal conditioning techniques are used to mitigate issues related to different signal characteristics, such as latency and disturbances. The estimated sideslip angle information and a brush tire model are fused in a Kalman filter framework to estimate the tire-road friction coefficient. The performance and practical feasibility of the proposed approach were evaluated through several tests.     

Cooperative control of the motor and the electric booster brake to improve the stability of an in-wheel electric vehicle

A cooperative control algorithm for an in-wheel motor and an electric booster brake is proposed to improve the stability of an in-wheel electric vehicle. The in-wheel system was modeled by dividing it into motor and mechanical parts, and the electric booster brake was modeled through tests. In addition, the response characteristics of the in-wheel system and the electric booster brake were compared through a frequency response analysis. In the cooperative control, the road friction coefficient was estimated using the wheel speed, motor torque, and braking torque of each wheel, and the torque limit of the wheel to the road was determined using the estimated road friction coefficient. Based on the estimated road friction coefficient and torque limit, a cooperative algorithm to control the motor and the electric booster brake was proposed to improve the stability of the in-wheel electric vehicle. The performance of the proposed cooperative control algorithm was evaluated through a hardware-in-the-loop simulation (HILS). Furthermore, to verify the performance of the proposed cooperative control algorithm, a test environment was constructed for the anti-lock braking system (ABS) hydraulic module hardware, and the performance of the cooperative control algorithm was compared with that of the ABS by means of a HILS test.     

Electrochemical battery model and its parameter estimator for use in a battery management system of plug-in hybrid electric vehicles

This paper reports the development of a battery model and its parameter estimator that are readily applicable to automotive battery management systems (BMSs). Due to the parameter estimator, the battery model can maintain reliability over the wider and longer use of the battery. To this end, the electrochemical model is used, which can reflect the aging-induced physicochemical changes in the battery to the aging-relevant parameters within the model. To update the effective kinetic and transport parameters using a computationally light BMS, the parameter estimator is built based on a covariance matrix adaptation evolution strategy (CMA-ES) that can function without the need for complex Jacobian matrix calculations. The existing CMA-ES implementation is modified primarily by region-based memory management such that it satisfies the memory constraints of the BMS. Among the several aging-relevant parameters, only the liquid-phase diffusivity of Li-ion is chosen to be estimated. This also facilitates integrating the parameter estimator into the BMS because a smaller number of parameter estimates yields the fewer number of iterations, thus, the greater computational efficiency of the parameter estimator. Consequently, the BMS-integrated parameter estimator enables the voltage to be predicted and the capacity retention to be estimated within 1 % error throughout the battery life-time.     

Air flow trajectory and surge avoidance of centrifugal compressor under variable pressure operation of automotive fuel cells

The compressor of an automotive proton exchange membrane fuel cell requires severe dynamic performance under normal driving patterns. Because the air flow demand of the automotive fuel cell requires steep increase/decrease, it is very important to understand the air flow trajectory of the centrifugal compressor to avoid the compressor surge. In this study, a simulation model of an automotive fuel cell system with a dynamic compressor was developed to investigate the proper trajectory of air flow rate on a performance map of an air compressor. The dynamic response of the compressor shows that the cathode inlet and exit valves have a significant effect on surge evolution. In particular, the results showed that a proper combination of valve opening areas is required to avoid compressor surge. In this study, the original two valve approach was reduced to a single cathode exit valve control with fixed cathode inlet orifice. A surge rejection algorithm was also developed, based on the comparison of surge protection envelope pressure with actual measured pressure. The results show that surge evolution is effectively avoided by controlling the cathode exit valve.     

Finite element damage analysis of an underwater glider–ship collision

Underwater gliders, which are profiling autonomous underwater vehicles designed to make oceanographic measurements, are increasingly used in the coastal ocean. As they regularly surface for data transmission, gliders increasingly pose a risk for fast ships. In order to estimate the extent of damage due to collision, 3D finite element simulations of collisions between a glider and a high-speed craft with a glass-fiber reinforced plastic hull are performed. Different collision scenarios such as impact locations, angles of attack and speeds are examined. The results are compared to an analytical solution based on simplifying assumptions. Although both methods reveal consistent results, it is shown that finite element simulations are required to account for the 3D shape of the ship. The results indicate that at ship velocities exceeding 7.5 m/s (14.6 kt) the glider penetrates the ship’s hull causing severe damage to its structure.