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Abstract The key issues of automatic emergency braking (AEB) control algorithm are when and how to brake. This article proposes an AEB control algorithm that integrates risk perception (RP) and emergency braking characteristics of professional drivers for rear-end collision avoidance. Using the formulated RP by time to collision (TTC) and time headway (THW), the brake trigger time can be determined. Based on the professional driver fitting (PDF) characteristic, the brake pattern can be developed. Through MATLAB/Simulink simulation platform, the European New Car Assessment Programme (Euro-NCAP) test scenarios are used to verify the proposed control algorithm. The simulation results show that compared with the TTC control algorithm, PDF control algorithm, and the integrated PDF and TTC control algorithm, the proposed integrated PDF and RP control algorithm has the best performance, which can not only ensure safety and brake comfort, but also improve the road resource utilization rate.

Abstract Advanced passenger vehicles are complex dynamic systems that are equipped with several actuators, possibly including differential braking, active steering, and semi-active or active suspensions. The simultaneous use of several actuators for integrated vehicle motion control has been a topic of great interest in literature. To facilitate this, a technique known as control allocation (CA) has been employed. CA is a technique that enables the coordination of various actuators of a system. One of the main challenges in the study of CA has been the representation of actuator dynamics in the optimal CA problem (OCAP). Using model predictive control allocation (MPCA), this problem has been addressed. Furthermore, the actual dynamics of actuators may vary over the lifespan of the system due to factors such as wear, lack of maintenance, etc. Therefore, it is further required to compensate for any mismatches between the actual actuator parameters and those used in the OCAP.

Abstract Intelligent tires, as an emerging technology, have great potential for tire-road contact information identification and new vehicle active safety system design. In this article, a tire-road friction coefficient estimation method is proposed based on intelligent tires application with three-axis accelerometer. At first, a finite element tire model with an accelerometer is established using ABAQUS platform. Accelerometer body frame transformation is considered during the tire rotation. Subsequently, the contact patch length is determined according to the peak of the longitudinal acceleration profile. Meanwhile, tire lateral deflection is calculated from the tire lateral acceleration. By curve fitting the lateral deflection model with least square method, tire lateral force and the aligning moment are derived and then the friction coefficient is estimated via brush model.

Abstract Small uncrewed aircraft systems (sUAS) growth continues for recreational and commercial applications. By 2025, the Federal Aviation Administration (FAA) predicts the sUAS fleet to number nearly 2.4 million units. As sUAS operations expand within the National Airspace System (NAS), so too does the probability of near midair collisions (NMACs) between sUAS and aircraft. Currently, the primary means of recognizing sUAS NMACs rely on pilots to visually spot and evade conflicting sUAS. Pilots may report such encounters to the FAA as UAS Sighting Reports. Sighting reports are of limited value as they are highly subjective and dependent on the pilot to accurately estimate range and altitude information. Moreover, they do not account for NMACs that an aircrew member does not spot.

Abstract Multi-agent autonomous racing still remains a largely unsolved research challenge. The high-speed and close proximity situations that arise in multi-agent autonomous racing present an ideal condition to design algorithms which trade off aggressive overtaking maneuvers and minimize the risk of collision with the opponent. In this article we study a two-vehicle autonomous racing setup and present AutoPass—a novel framework for overtaking in a multi-agent setting. AutoPass uses the structure of an automaton to break down the complex task of overtaking into sub-maneuvers that balance overtaking likelihood and risk with safety of the ego vehicle. We present real-world implementation of 1/10-scale autonomous racing cars to demonstrate the effectiveness of AutoPass for the overtaking task.

Abstract Diesel engines include systems for cooling, lubrication, and fuel injection and contain a variety of components. A malfunction in any of the engine systems or the presence of any faulty element influences engine performance and deteriorates its components. This research is concerned with the untimely appearance of vital cracks in the liners of a turbocharged heavy-duty Diesel engine. To find the root causes for premature failure, rigorous examinations through visual observations, material characterization, and metallographic investigations are performed. These include Scanning Electron Microscope (SEM) and Energy-Dispersive Spectroscopy (EDS), fracture mechanics analysis, and performance examination, which are also followed by Finite Element Moldings. To find the proper remedy to resolve the problem, drawing a precise and reliable picture of the engine’s operating conditions is required.

Abstract To evaluate that automated vehicle is as safe as a human driver, a following question is studied: how does an automated vehicle react under extreme conditions close to collision? In order to understand the collision avoidance capability of an automated vehicle, we should analyze not only such post-extreme condition behavior but also pre-extreme condition behavior. We present a theory to analyze the collision avoidance capability of automated driving technologies. We also formulate a collision avoidance equation on the theory. The equation has two types of solutions: response driving plans and preparation driving plans. The response driving plans are supported by response strategy on which the vehicle reacts after detection of a hazard and they are highly efficient in terms of travel time.

Abstract The levels of sustained vehicle automation, as recently updated by SAE in J3016 (status: 06/2018), have become common knowledge. They facilitate overall understanding of the issue. Sustained automation describes the shift in workload from purely human-driven vehicles to full automation. Duties of the driver are assigned to the machine as automation levels rise. Yet sustained driving automation does not cover “automated driving” as a whole. Automated driving functions operating on a nonsustained basis cannot be classified by means of levels describing continuous automation. Emergency braking, e.g., is obviously an intensive, but discontinuous, automation of a single task. It cannot be classified under the regime of sustained automation. The resulting lack of visibility of these important functions cannot satisfy - especially in the light of effect they take on traffic safety.

Abstract The frequency of video-capturing collision events from surveillance systems are increasing in reconstruction analyses. The video that has been provided to the investigator may not always include a clear perspective of the relevant area of interest. For example, surveillance video of an incident may have captured a pre- or post-incident perspective that, while failing to capture the precise moment when the pedestrian was struck by a vehicle, still contains valuable information that can be used to assist in reconstructing the incident. When surveillance video is received, a quick and efficient technique to place the subject object or objects into a three-dimensional environment with a known rate of error would add value to the investigation.

Abstract The causes of failure due to cracking in the resistance spot welding of the advanced high-strength steels dual-phase 590 (DP590) were investigated using scanning electron microscopy (SEM), optical microscopy, and the tensile-shear test. The results showed that by increasing the current amount, the formation of the melting zone occurred in the heat-affected zone, leading to the cracking in this area, reducing the tensile strength and decreasing the mechanical properties; the initiation and growth of cracking and failure in this region also happened. In the heat-affected zone, by increasing the current amount with the softening phenomenon, the recrystallized coarse grains also occurred, eventually resulting in the loss of mechanical properties. The results of the tensile-shear test also indicated that by increasing the current up to 12 kA, the strength was raised, but the ductility was reduced.

Abstract This study implements Flame Image Velocimetry (FIV), a diagnostic technique based on post-processing of high-speed soot luminosity images, to show the in-flame flow field development impacted by after-injection in a single-cylinder, small-bore optical diesel engine. Two after-injection cases with different dwell times between the main injection and after-injection, namely, close-coupled and long-dwell, as well as a main-injection-only case are compared regarding flow fields, flow vector magnitude, and turbulence intensity distribution. For each case, high-speed soot luminosity movies from 100 individual combustion cycles are recorded at a high frame rate of 45 kHz for FIV processing. The Reynolds decomposition using a spatial filtering method is applied to the obtained flow vectors so that bulk flow structures and turbulence intensity distributions can be discussed.

Abstract TOC

Abstract Although tread block deformation analysis is important, the deformation measurement is difficult because fast-rotating tires maintain a continuous contact with the road surface. Furthermore, capturing small displacements near the edge of tread blocks using a high-speed camera is difficult because of the particularly limited resolution. Additionally, the tread blocks being significantly deformed at the edge and susceptible to wear powder, the state change of the feature points, is highly probable. To overcome these problems, a system that obtains high-resolution images and measures the deformation of a fast-rotating body (tire) is proposed herein. The developed system captures the deformation behavior through intermittent imaging. To further measure the strain distribution, fine tracking markers are drawn on the tread block using a laser processing machine. The displacement of the marker is calculated using the particle mask correlation method.

Abstract In the present study, the mechanical performances of plain carbon steel were explored based on the grain growth behavior. In the first step, the samples were normalized at different temperatures ranging from 900°C to 1100°C for 30, 60, 100, 150, and 200 min, respectively. In order to measure the grain size, the planimetric technique of Jeffries was used based on the optical micrographs taken for each sample. The mechanical properties of each grain such as hardness, elongation, yield, and tensile strength were studied, depending on the conventional methods. Experimental results showed that the increase in both heating temperature and holding time enhances grain growth, while the growth rate decreases with increasing time. The initial grain size and proportionality constant were calculated at 950°C, where K = 2.26 μm2/min and D 0 = 25.09 μm. Moreover, a significant increase in strength and hardness was observed with a decrease in grain size.

Abstract In this article, Al-Mg-Si-Mn alloy (AA6082) is butt joined by employing friction stir welding (FSW). The mechanical and metallurgical properties of joints are analyzed by conducting tensile and microhardness testing, respectively. To measure the temperature at different locations, eight thermocouples (L-shaped k-type) are placed at equal distance from the centerline. Least square method attempts to calculate the temperature at the centerline of joints. The process parameters are also optimized using Taguchi’s five-level experimental design. The optimum process parameters are determined, employing ultimate tensile strength (UTS) as a response parameter. A statistical test “analysis of variance” is used to check the adequacy of the model. It has been observed that rotational speed and feed rate are the predominant factors for UTS and microhardness.

Abstract An ongoing challenge with Gasoline engines is achieving rapid activation of the three-way catalyst during cold starts in order to minimize pollutant emissions. Retarded combustion is an effective way in achieving rapid light-up of the three-way catalyst and can be facilitated by stratified charge using late fuel injection. This, however, provides insufficient time for fuel entrainment with air, resulting in locally fuel-rich diffusion combustion. Employing a split injection strategy can help tackle these issues. The effects of a split injection strategy, using a high-pressure Solenoid injector, on the in-cylinder charge formation are investigated in the current study. The studies are performed inside an optical Gasoline engine using high-speed particle image velocimetry (PIV) in the central tumble and Omega tumble planes, by means of a high-speed laser and camera operating at a repetition rate of 10 kHz.

Abstract This research involves the study of the different properties of aluminum alloy (AA) 2024 in the presence of carbon nanotubes (CNTs) and Silicon (Si) nanoparticles. Structural morphology, elemental composition, mechanical properties (density, tensile strength, elongation, and hardness), and tribological properties (wear rate and coefficient of friction) of AA 2024 in the presence of CNTs, Si, and its combinations at various proportions were evaluated using a Scanning Electron Microscope (SEM), Energy Dispersive X-Ray Analyzer (EDX), Universal Testing Machine (UTM), Model HMV-2T Vickers hardness test machine, and pin-on-disk friction-and-wear test rig. The Hybrid Metal Matrix Composite (HMMC) material is prepared by a two-stage stir casting method. It was found that the density of the AA 2024 + 4%CNT + 2%Si is 2.22 g/cm3, ultimate tensile strength is 308 N/mm2, elongation is 15.5%, and Vickers hardness is 187.5 Vickers Hardness Number (VHN).

Abstract Threat assessment and reliable motion prediction of surrounding vehicles are essential for proactive decision-making and ensuring safety in autonomous vehicles. Most of the vehicles on roads are human-driven, which make it difficult to predict their intentions and movements. Moreover, different driver behaviors pose different kinds of threats. Various driver behavior predictive models have been proposed in the literature. However, these models cannot be trusted entirely due to the human drivers’ highly uncertain nature. This article proposes a novel trust-based driver behavior prediction and threat assessment methodology for various dangerous situations on the road. This trust-based methodology allows autonomous vehicles to quantify the degree of trust in their predictions to generate the probabilistically safest trajectory. This approach can be instrumental in near-crash scenarios where no collision-free trajectory exists.

Abstract Reliable detection of obstacles around an autonomous vehicle is essential to avoid potential collision and ensure safe driving. However, a vast majority of existing systems are mainly focused on detecting large obstacles such as vehicles, pedestrians, and so on. Detection of small obstacles such as road debris, which pose a serious potential threat are often overlooked. In this article, a novel stereo vision-based road debris detection algorithm is proposed that detects debris on the road surfaces and estimates their height accurately. Moreover, a collision warning system that could warn the driver of an imminent crash by using 3D information of detected debris has been studied.

Abstract High fuel injection pressure systems for Gasoline Direct Injection (GDI) engines have become widely used in passenger car engines to reduce emissions of particulates and pollutant gases. Current commercial systems operate at pressures of up to 450 bar, but several studies have examined the use of injection pressures above 600 bar, and some have even used pressures around 1500 bar. These works revealed that high injection pressures have numerous benefits including reduced particulate emissions, but there is still a need for more data on the possible benefits of injection pressures above 1000 bar. This article presents spray and engine data from a comprehensive study using several measurement techniques in a spray chamber and optical and metal engines. Shadowgraph imaging and Phase Doppler Interferometry (PDI) were used in a constant volume chamber to interpret spray behavior. Particle Image Velocimetry (PIV) was used to capture near-nozzle air entrainment.