Design factor optimization of 3D flash lidar sensor based on geometrical model for automated vehicle and advanced driver assistance system applications

Sensor technologies have been innovated and enhanced rapidly for highly automated vehicle and advanced driver assistance systems (ADAS) in automotive industry; however, in order to adopt sensors into mass production vehicle in near future, various requirements should be satisfied such as cost, durability, and maintainance without any loss of overall performance of the sensors. In this sense, a 3D flash lidar is one of primising range sensors because of no moving parts, compact package, and precise measure for distance by using a laser. In spite of the several advantages, the 3D flash lidar is not commonly used in automotive industry because it is quite expensive for adoption and it is manufactured with only general purpose currently; therefore, the cost reduction and optimal design to satisfy various purposes of ADAS or autonomous driving should be accomplished. In this paper, we propose a novel approach for design factor optimization of the 3D flash lidar based on a geometrical model by using structural similarity between the 3D flash lidar and 2D digital camera. In particular, focal length and area of a receiver (focal plane array and read-out integrated circuit) which directly affect on sensor performance (field of view and maximum detection range) are optimized as the design factors. From the optimization results in simulation, we show that optimal design factors according to various purposes required in ADAS could be easily determined and the sensor performances could be evaluated before manufacturing. It will reduce temporal and economic burdens for design and manufacturing in development process.     

Effects of altitude on combustion characteristic during cold start of heavy-duty diesel engine

Altitude has a significant effect on combustion of heavy-duty diesel engines, especially during cold start. An experimental study on a heavy-duty diesel engine operating at different altitudes was conducted. Tests were based on a direct injection (DI) turbocharged diesel engine with intake and exhaust pressure controlled by the plateau simulation test system to stimulate altitude conditions including 0 m, 1000 m, 2000 m, 3000 m and 4000 m. Results indicated that the compression and expansion resistance moment reduced and the speed increased during the cranking period. The peak pressure of several cycles was increased during the start-up period; however, the expansion pressure dropped more and the indicated mean effective pressure (IMEP) reduced as the altitude rose. While at an altitude of over 2000 m, the peak pressure fluctuated obviously during the start-up period. The higher the altitude was, the more the fluctuation amplitude and cycle number increased and combustion instability enhanced, which resulted the start-up period time increasing at high altitude. When the altitude rose, the cycle-to-cycle variation of the peak pressure and speed fluctuation increased during the idle, the ignition and CA50 were delayed and the combustion duration was shortened. The effect of altitude on combustion characteristics of the diesel engine was more significant during the start-up period than during its idle period.     

Pedaling torque sensor-less power assist control of an electric bike via model-based impedance control

This paper proposes a method to assist human force acting on electric bike without using costly torque sensors via a model-based impedance control technique. In general, electric bikes are classified into two categories, i.e., pedelec electric bikes and throttle electric bikes. We focus on the system called a pedelec electric bike. It assists human pedaling force using the pedaling information, e.g., pedaling force or speed. To obtain the human’s pedaling information in real-time, it needs physical sensors such as a torque sensor and a velocity sensor. But, these sensors are expensive and weak against external loads. Also, since these sensors are fixed directly to the forced component in a bike system, there are the risks of damage. For these reasons, sensor-less control methods based on a disturbance observer have been studied so far. In this paper, we have proposed a pedaling torque sensor-less power assist method and have applied it to the experimental pedelec electric bike. A power assist control algorithm, designed by employing an impedance model, consists of a PI-type feedback controller, an inverse model-based feedforward controller, and a pedaling torque observer. Finally, we performed experiments and confirmed the effectiveness of a proposed power assist control method.     

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.