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High-speed vehicles in low illumination environments severely blur the images used in object detectors, which poses a potential threat to object detector-based advanced driver assistance systems (ADAS) and autonomous driving systems. Augmenting the training images for object detectors is an efficient way to mitigate the threat from motion blur. However, little attention has been paid to the motion of the vehicle and the position of objects in the traffic scene, which limits the consistence between the resulting augmented images and traffic scenes. In this paper, we present a vehicle kinematics-based image augmentation algorithm by modeling and analyzing the traffic scenes to generate more realistic augmented images and achieve higher robustness improvement on object detectors against motion blur. Firstly, we propose a traffic scene model considering vehicle motion and the relationship between the vehicle and the object in the traffic scene.

In order to avoid the influence of the change of the camera pitch angle and the variation of the height of the ground on the ranging accuracy, improve the real-time performance of the algorithm by substituting the current widely-used monocular vision ranging algorithm which builds the optical model based on the shadow of the vehicle floor and the lane line, as well as avoid the classification of vehicle detection, a vehicle distance measurement algorithm based on monocular vision and license plate width is established. Firstly, the target image acquisition and preprocessing are studied. Then the paper studies the license plate image location segmentation method based on accelerated template matching. On this basis, the algorithm for obtaining the ratio of license plate width to image width is studied, and the function of vehicle distance and license plate ratio width is established.

Highly accurate parking slot detection methods are crucial for Automated Valet Parking (AVP) systems, to meet their demanding safety and functional requirements. While previous efforts have mostly focused on the algorithms’ capabilities to detect different types of slots under varying conditions, i.e. the detection rate, their accuracy has received little attention at this time. This paper highlights the importance of trustworthy slot detection methods, which address both the detection rate and the detection accuracy. To achieve this goal, an accurate slot detection method and a reliable ground-truth slot measurement method have been proposed in this paper. First, based on a 2D laser range finder, datapoints of obstacle vehicles on both sides of a slot have been collected and preprocessed. Second, the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm has been improved to efficiently cluster these unevenly-distributed datapoints.

The exhaust aftertreatment strategy is one of the most fundamental aspects of spark ignition engine technologies. For various types of engines (e.g., carburetor engine, PFI engine and GDI engine), measuring, purifying, modeling, and control strategies regarding the exhaust aftertreatment systems vary significantly. The primary goal of exhaust aftetreatment systems is to reduce the exhaust emission levels of NOx, HC and CO as well as to lower combustion soot. In general, there is a tradeoff among different engine performance aspects. The exhaust catalytic systems, such as the three way catalyst (TWC) and lean NOx trap (LNT) converters, can be applied together with the development of other engine technologies (e.g., variable valve timing, cold start). With respect to engine soot, some advanced diagnosing techniques are essential to obtain thorough investigation of exhaust emission mechanisms.

The cab is an essential part of a light truck, and its fatigue durability performance plays an important role in the design and development stage. Accelerated fatigue bench test has been widely applied to product development of carmakers for its low cost and short development cycle. However, in reality, interference exists generally in torsional conditions for the light truck cab when tested on the 4-post vehicle road simulation system. To solve this problem and minimize the lateral force applied on the hydraulic cylinders, the direction and size combinations of displacement release about front and rear suspensions were discussed based on multi-body dynamics simulation and fixture design theory in this paper. Through comparative study, the optimum design and layout scheme of fixtures was determined to conduct the next test procedure. The weak positions of the light truck cab were firstly predicted by utilizing finite element method (FEM) and fatigue analysis theory.

Centrifugal Pendulum Vibration Absorber (CPVA for short) is used to absorb torsional vibrations caused by the shifting motion of the engine. It is increasingly used in modern powertrains. In the research of the dynamic characteristics of the CPVA, it is necessary to obtain the real motion of the pendulum to compensate the fitting performance of mathematical model. The usual method is to install an angle sensor to measure the movement of the pendulum. On the one hand, the installation of the sensor will affect its movement to a certain extent, so that the measurement results do not match the actual motion. On the other hand, the motion of the pendulum is not only the rotational motion around the rotational axis of the CPVA rotor, but also has translation relative to it. As a result, it is difficult to obtain accurate motion only by the angle sensor. We proposed a non-contact centrifugal pendulum motion measurement method.

For an in-line diesel engine with four cylinder operating in four-stroke mode, the second-order reciprocating inertia forces generally cannot be well balanced with direct approach. The unbalanced second-order inertia forces are the main reason to cause vibration and noise in a diesel engine within low frequency range. The more superior tone quality for modern diesel engine has been expected even for bus application all the time, and there are tougher requirements for truck noise in developed countries, i.e. in Europe and USA. In present research a unique crankshaft system configuration was proposed, which including opposed piston, inner and outer connecting rod, and crankshaft but running in two-stroke mode, to eliminate the second-order inertia force considerably rather than by adding an extra balance shaft mechanism.

During the launch of a car, severe torsional vibration sometimes may occur in its driveline due to somewhat the slipping of the clutch, its intuitive sense for an occupant is the longitudinal vibration of the vehicle, referred to as the launch shudder whose characteristic frequency is from 5 to 25 Hz generally. As the main vibration sources of the driveline and its crucial nonlinear components, the variable stiffness and backlash of the gear meshing are considered, their impacts on the launch shudder are analyzed in this paper. Conformal mapping, finite element method and regression method etc. are the main approaches to calculate the variable meshing stiffness of a gear pair. If this stiffness is get, it can usually be substituted for its approximate analytical expression, just with finite harmonic terms, in Fourier Series form into Ordinary Differential Equations(ODEs) to calculate the vehicle responses with its nonlinearity considered.

Emissions of diesel engine have been received much more attention since the Volkswagen Emission Scandal. The Euro VI emission standard has already included cold start emissions in the legislative emission driving cycles which is one of the hardest part of emission control. High altitude performance is also considered in the latest regulations which will be stricter in the future. Heating the coolant is one of the most common method to improve the cold start performance. But researches focus on the emission of a diesel engine in different coolant temperature at high altitude which up to 4500m have not been seen. The present research investigated the effect of coolant temperature on performance and exhaust emissions (gaseous and particulate emissions) during the cold start of a diesel engine. A plateau simulation system controlled the inlet and exhaust pressure to create altitude environments from 0m to 4500m, and the coolant temperature was controlled from 20°C to 60°C.

In order to explore approaches for improving object detection accuracy in intelligent vehicle system, we exploit super-resolution techniques. A novel method is proposed to confirm the conjecture whether some popular super-resolution networks used for environmental perception of intelligent vehicles and robots can indeed improve the detection accuracy. COCO dataset which contains images from complex ordinary environment is utilized for the verification experiment, due to it can adequately verify the generalization of each algorithm and the consistency of experimental results. Using two representative object detection networks to produce the detection results, namely Faster R-CNN and YOLOv3, we devise to reduce the impact of resizing operation. The two networks allow us to compare the performance of object detection between using original and super-resolved images. We quantify the effect of each super-resolution techniques as well.

The increasingly stringent emission regulations have mandated the use of CCRT (catalyzed continuously regeneration trap) made by upstream DOC (diesel oxidation catalyst) and downstream CDPF (catalyzed diesel particulate filter) for heavy-duty diesel vehicles, which is proved to be the only way that can efficiently control the gaseous and particulate emissions. The performance of after-treatment is greatly influenced by the running conditions of the diesel vehicle and its exhaust parameters, so this paper intended to use grey relational analysis to study the correlation between running conditions (velocity, acceleration, VSP (vehicle specific power)), exhaust parameters (exhaust flow rate, DOC inlet temperature, concentrations of CO, THC, O2 and NOX) and the performance of DOC and CCRT based on chassis dynamometer test. Results showed that the effect of DOC on CO and THC is mainly affected by exhaust flow rate, exhaust temperature and THC concentration.

The present work proposed to implement oxy-fuel combustion mode into a homogeneous charge compression ignition engine to reduce complexity in engine emissions after-treatment and lower carbon dioxide emission. The combination of oxy-fuel combustion mode with homogeneous charge compression ignition engine can be further optimized by the utilization of direct high temperature and pressure water injection to improve cycle performance. A retrofitted conventional diesel engine coupled with port fuel injection and direct water injection is utilized in this study. A self-designed oxygen and carbon dioxide mixture intake system with flexible oxygen fraction adjustment ability is implemented in the test bench to simulate the adoption of exhaust gas recirculation. Water injection system is directly installed in the combustion chamber with a modified high speed solenoid diesel injector.

The diesel particulate filter (DPF) is an effective device for reducing particulate emissions from diesel engines, while its durability and reliability after long-term use are causes for concern. Usually, particulates are considered to be uniformly deposited in DPF channels to form a cake or end plug, however, recent studies have found that a “middle channel deposit” phenomenon of particulates can form a bridge near the middle of the DPF channel. This phenomenon has serious adverse effects on the durability and reliability of the DPF, including abnormally increased pressure drop and frequent regeneration. Since the width of the DPF channel is only about 1-2 millimeters, conventional methods cannot observe the particulate deposition process inside the DPF.

Based on the working model of a diesel engine, the influence of 2 Miller cycle strategies-Early Intake Valve Closure (EIVC) and Late Intake Valve Closure (LIVC) on the combustion and emissions of diesel engine was analyzed. Then the working condition of each Miller cycle strategies on the engine under the rated speed was optimized through the adjust of the valve timing, boost pressure and the injection timing. The research found that both delaying and advancing the closure timing of the intake valve can decrease the pressure and temperature during compression stroke, prolonging the ignition delay. However, due to the decrease of the working media inside the cylinder, the average in-cylinder temperature and soot emissions will increase, which can be alleviated by raising the boost pressure and the resulting compensation of the intake loss.

The camera-based advanced driver assistance systems (ADAS) like lane departure warning system (LDWS) and lane keeping assist (LKA) can make vehicles safer and driving easier. Lane detection is indispensable for these lane-based systems for achieving vehicle local localization and behavior prediction. Since the vision is vulnerable to the variable environment conditions such as bad weather, occlusions and illumination, the robustness is important. In this paper, a robust algorithm for detecting and tracking multiple lanes with arbitrary shape is proposed. We extend the previously lane detection and tracking process from the space domain to the temporal-spatial domain by using a more robust and general multi-lane model. First, new slice images containing temporal information are generated from image sequences. Instead of binarization process, we use a more general detector for extracting the lane marker candidates with prior knowledge to generate the binary slice image.

Deep neural network models have been widely used for environment perception of intelligent vehicles. However, due to models’ innate probabilistic property, the lack of transparency, and sensitivity to data, perception results have inevitable uncertainties. To compensate for the weakness of probabilistic models, many pieces of research have been proposed to analyze and quantify such uncertainties. For safety-critical intelligent vehicles, the uncertainty analysis of data and models for environment perception is especially important. Uncertainty estimation can be a way to quantify the risk of environment perception. In this regard, it is essential to deliver a comprehensive survey. This work presents a comprehensive overview of uncertainty estimation in deep neural networks for environment perception of intelligent vehicles.

In this paper, Digital Image Correlation Method (DICM) is employed to measure the shear mechanical property of the new style automotive structural adhesive specimens and traditional spot welded specimens under quasi static uniaxial shear tensile test. This experiment adopts a non-contact measuring method to measure the strain of specimens. A CCD and a computer image processing system are used to capture and record the real-time surface images of the specimens before and after deformation. Digital correlation software is used to process the imagines before and after deformation to obtain the specimen's strain of the moment. And then both the force-displacement curve and the stress-strain curve during the tensile process could be obtained. The test and analysis results show that the new style structural adhesive specimens have a great advantage with the spot welded specimens. It provides experimental evidence for further improvement of this structural adhesive.

Lithium-ion batteries (LIBs) with relatively high energy, power density and eco-friendly characteristic are considered as a vital energy source in consumer market of portable electronics and transportation sector especially in electric vehicles (EVs). To meet the higher capacity requirements, the nickel-rich LIBs with higher capacity has been used as the commercial power batteries. However, the battery with higher energy density is more destructive, which could result in thermal runaway accidents and make the battery safety issues become more and more prominent. Thermal runaway of LIBs is one of the key scientific problems in safety issues. Until now, the inducement of thermal runaway process is complicated which perplex researchers and industry a lot. On the one hand, the internal mechanism about thermal runaway should be deeply studied. On the other hand, in-situ monitoring should be developed to supply the mechanism study and early warning.

Automotive window seal has great influence on NVH (Noise-Vibration-Harshness) performance. The aerodynamic effect on ride comfort has attracted increasing research interest recently. A new method for quantifying and transferring aerodynamics-induced load on window seal re-design is proposed. Firstly, by SST (Shear Stress Transport) turbulence model, external turbulent flow field of full scale automotive is established by solving three-dimensional, steady and uncompressible Navier-Stokes equation. With re-exploited mapping algorithm, the aerodynamics pressure on overall auto-body is retrieved and transferred to local glass area to be external loads for seals, thus taking into account the aerodynamics effect of high speed fluid-structure interaction. This method is successfully applied on automotive front window seal design. The re-design header seal decreases the maximum displacements of leeward and windward glass with 9.3% and 34.21%, respectively.

Accurate and reliable localization in GNSS-denied environments is critical for autonomous driving. Nevertheless, LiDAR-based and camera-based methods are easily affected by adverse weather conditions such as rain, snow, and fog. The 4D Radar with all-weather performance and high resolution has attracted more interest. Currently, there are few localization algorithms based on 4D Radar, so there is an urgent need to develop reliable and accurate positioning solutions. This paper introduces RIO-Vehicle, a novel tightly coupled 4D Radar/IMU/vehicle dynamics within the factor graph framework. RIO-Vehicle aims to achieve reliable and accurate vehicle state estimation, encompassing position, velocity, and attitude. To enhance the accuracy of relative constraints, we introduce a new integrated IMU/Dynamics pre-integration model that combines a 2D vehicle dynamics model with a 3D kinematics model.