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The utilization of the SLAM (Simultaneous Localization and Mapping) technique was extended from the robotics to the autonomous vehicles for achieving the positioning. However, SLAM cannot obtain the global position of the vehicle but a relative one to the start. For sake of this, a fast and accurate system was proposed to obtain both the local position and the global position of vehicles based on mono-SLAM which realized the SLAM by using monocular camera with a lower cost and power consumption. Firstly, the rough latitude and longitude of current position was obtained by using common GPS without differential signal. Then, the Mono-SLAM operated on the consecutive video frames to generate the localization and local trajectory and its accuracy was further improved by utilizing the IMU information. After that, a piece of Map centered in the rough position obtained by common GPS was downloaded from the Open Street Map.

In this paper, a new method for determining the forming limit diagram (FLD) of thin sheet metals, called DIC-Grid method, is proposed based on digital image correlation (DIC) technique. It's assumed that there exists one virtual grid with an initial diameter of 2.5mm, which is usually the same dimension as the grid in traditional circular grid analysis, close to the crack of specimen, and the limit strain point on FLD is determined by the deformation of this virtual grid. The DIC-Grid method has been compared with traditional circular grid analysis and the standard ISO/FDIS 12004-2 in Nakajima tests. The results show that the forming limit strains obtained by the newly proposed method are more stable and precise. Furthermore, DIC-Grid method can avoid the measurement error which exists in the circular grid analysis. Meanwhile, it overcomes the shortcomings of time-consuming data processing and non-applicable for unrealistic strain distribution in the method of ISO standard.

Vehicle and pedestrian detection technology is the most important part of advanced driving assistance system (ADAS) and automatic driving. The fusion of millimeter wave radar and camera is an important trend to enhance the environmental perception performance. In this paper, we propose a method of vehicle and pedestrian detection based on millimeter wave radar and camera. Moreover, the proposed method complete the detection of vehicle and pedestrian based on dynamic region generated by the radar data and sliding window. First, the radar target information is mapped to the image by means of coordinate transformation. Then by analyzing the scene, we obtain the sliding windows. Next, the sliding windows are detected by HOG features and SVM classifier in a rough detect. Then using the match function to confirm the target. Finally detecting the windows in a precision detection and merging the detecting windows. The target detection process is carried out in the following three steps.

Similar laser welded blanks with same material and same gauge have been extensive applied in automobile body for improving the material utilization and extending maximum coil size. It is known that, for TWBs with dissimilar material and thicknesses, the difference of material properties and/or thickness of the welded blanks, change of the material properties in the weld seam and heat-affected zones (HAZ) as well as location and orientation of the weld seam are reasons for reduced formability. However, the plastic deformation capacity of TWBs is reduced even when the material and thickness are the same. The aim of this paper is to evaluate the deformation behaviors of similar laser welded joints. Uniaxial tensile of five laser welded joints, with 90°,60°,45°,30°and 0°weld orientations, were tested by using optical measurement-DIC (Digital Image Correlation). Strain /strain ratio distribution and evolution of each joint was analyzed and compared with base material.

An experimental study is presented on the evaporation of diluted droplet-laden two-phase jet flows within a heated air channel co-flow. In this study, n-heptane is pre-atomized by an ultrasonic nozzle to produce droplet cluster with a median diameter of about15μm, and a continuous cold air flow is applied to carry the fuel droplet cluster to emerge from a nozzle tube, producing a free turbulent jet of droplet stream. The droplet stream is then introduced as a central jet into a square-shaped channel with heated air co-flow for evaporation investigations. With flexibilities of the initial properties of droplet stream and surrounding conditions of channel flow, the axial evolution of droplet size is determined to characterize the evaporation behavior of n-heptane droplet stream under various boundary conditions. The equivalence ratios of droplet streams are varied by changing both the carrier-air flow rate and the fuel flow rate.

Being one of the most simple and basic driving scenarios, highway scenario can be one of the first scenarios to achieve autonomous driving. Both car following (CF) and lane changing (LC) are the most basic and frequent maneuver during highway driving tasks, and therefore become two key issues to focus on in recent researches about autonomous vehicle (AV). Different from conventional CF and LC researches that attach much importance to the character, psychology, perception ability, and driving experience of human drivers, more timely and accurate reactions based on fast perception and communication technology as well as the automatic actuator are hypotheses for this research. Moreover, based on these hypotheses, a modified intelligent driver model (MIDM) is proposed for AVs’ following behavior to alleviate the fluctuations caused by lane changing behaviors.

This workbook, a companion to the book Road Vehicle Dynamics, will enable students and professionals from a variety of disciplines to engage in problem-solving exercises based on the material covered in each chapter of that book. Emphasizing application more than theory, the workbook presents systematic rules of analysis that students can follow in a step-by-step manner to understand the efficiencies or shortcomings of various techniques. Readers will gain a greater understanding of the factors influencing ride, handling, braking, acceleration, and vehicle safety.

This set combines the book Road Vehicle Dynamics with its corresponding workbook companion, Road Vehicle Dynamics: Problems and Solutions. Road Vehicle Dynamics provides a detailed overview of the dynamics of road vehicle systems, giving readers an understanding of how physical laws, human factor considerations, and design choices affect ride, handling, braking, acceleration, and vehicle safety. Chapters cover analysis of dynamic systems, tire dynamics, ride dynamics, vehicle rollover analysis, handling dynamics, braking, acceleration, total vehicle dynamics, and accident reconstruction. The workbook will enable students and professionals from a variety of disciplines to engage in problem-solving exercises based on the material covered in each chapter of that book. It presents systematic rules of analysis that students can follow in a step-by-step manner to understand the efficiencies or shortcomings of various techniques.

Real-time and reliable perception of the surrounding environment is an important prerequisite for advanced driving assistance system (ADAS) and automatic driving. And vision-based detection plays a significant role in environment perception for automatic vehicles. Although deep convolutional neural networks enable efficient recognition of various objects, it has difficulty in accurately detecting special vehicles, rocks, road pile, construction site, fence and so on. In this work, we address the task of traffic scene understanding with semantic image segmentation. Both driveable area and the classification of object can be attained from the segmentation result. First, we define 29 classes of objects in traffic scenarios with different labels and modify the Deeplab V2 network. Then in order to reduce the running time, MobileNet architecture is applied to generate the feature map instead of the original models.

Connected and autonomous vehicles are different from traditional vehicles. The communication between vehicles (V2V) or between vehicles and infrastructures (V2I) renders it possible to convey traffic information (e.g. signal timing or speed advisory) from signal controllers to vehicles as well as vehicles to vehicles in real time. Taking this advantage, this paper aims to developing an algorithm which enables the interconnected autonomous vehicles running efficiently on arterials. A set of driving rules determining random behavior and swarm behavior of autonomous vehicles is developed based on swarm intelligence theory. Under control of these rules, each autonomous vehicle follows the same rules, which make it select target vehicle from all the optimal individuals in detection zone according to characteristics of itself, then approach to the target by changing lane, following former car, or accelerating.

Automotive radar is an important environment perception sensor for advance driving assistance system. It can detect objects around the vehicle with high accuracy and it works in all bad weathers. For traditional automotive radar, it cannot measure the objects’ height. Thus, a manhole cover on the road surface or a guideboard high above the road would be taken erroneously as a non-moving car. In such cases, the adaptive cruise system would decelerate or stop the vehicle erroneously and make the driver uncomfortable. A 3D automotive radar with two-dimensional electronic scanning can measure the targets’ height as well as the targets’ azimuth angle. This paper presents a 79 GHz ultra-wide band automotive 3D imaging radar. Due to the 4 GHz wide bandwidth, the range resolution of this radar can be as small as 3.75 cm.

Research studies have suggested that changes to the ignition system are required to generate a more robust flame kernel in order to secure the ignition process for the future advanced high efficiency spark-ignition (SI) engines. In a typical inductive ignition system, the spark discharge is initiated by a transient high-power electrical breakdown and sustained by a relatively low-power glow process. The electrical breakdown is characterized as a capacitive discharge process with a small quantity of energy coming mainly from the gap parasitic capacitor. Enhancement of the breakdown is a potential avenue effectively for extending the lean limit of SI engine. In this work, the effect of high-power capacitive spark discharge on the early flame kernel growth of premixed methane-air mixtures is investigated through electrical probing and optical diagnosis.

In order to solve the problem that in the traditional trilateral positioning algorithm, the final positioning error is large when there is a certain error in the measured three-sided distance, a UWB positioning algorithm based on Back Propagation (BP) neural network is proposed. The algorithm utilizes the fast learning characteristic and the ability of approximating any non-linear mapping of neural network, and realizes the location of the mobile label through the TOA measurement value provided by the base station and the BP neural network. By comparing the traditional trilateral positioning algorithm, the BP neural network algorithm based on four distance inputs and the BP neural network algorithm based on four distance inputs with trilateral positioning coordinates, it can be seen that the positioning error of traditional trilateral positioning algorithm is 30 cm, and the positioning error of the positioning algorithm based on the BP neural network proposed in this paper is 10 cm.

Adhesive bonding has many applications in the automotive industry. The single-lapped bonded joint is the most typically used among various bonding types. This paper presents experimental research for determining the strain field of the single-lapped joint under tensile loading. The materials for the joint are epoxy-based structural adhesive and low-carbon electrolytic zinc steel plate. In the study, a DIC (digital image correlation) system was adopted to measure the strain distribution of the bonded joint during a tensile test. The bonded steel coupons in the tensile test were prepared according to the ASTM standard. During the measurement, images of the coupon joint were taken before and after the deformation process. Then the DIC system measured the strain of bonded joint by comparing two consecutive images. The measured data from the DIC was compared to data taken simultaneously from a traditional extensometer.