Vehicle Shape Research Articles

Подход к формированию технического облика беспилотного воздушного судна

The article focuses upon the substantiation of efficiency criterion at formation of technical shape of an unmanned aerial vehicles. The authors analyze the criteria of efficiency of applying unmanned aerial vehicles, such as relative weight, flight time, unit cost of flight and life cycle cost and provide reasoning for the necessity of using the combined criterion considering economic and functional efficiency. Variable, non-variable and uncertain parameters characterizing an unmanned aerial vehicles are formulated. The optimization problem of determining the technical appearance is considered. The process of technical appearance formation is based on three interrelated processes: aerodynamic arrangement; volume-mass arrangement and structural-force arrangement. The purpose of the technical appearance is to find such interrelated values of the parameters of an unmanned aerial vehicle (UAV), which ensure the achievement of a compromise between the requirements while ensuring the extreme of any selected generalized criterion of optimality, for example, the minimum cost of the life cycle of the finished product - the aircraft. This criterion is one of the most general criteria for aircraft efficiency, but it is difficult to calculate it at an early stage of development. Therefore, in practice, it uses other criteria that are close to the cost of the life cycle stages. The specific feature of the process of UAV glare formation, as well as any complex technical system, is a large number of unknown and high degree of uncertainty, especially at the early stages of development. To overcome this uncertainty, the design process is divided into a series of successive iterative stages. The task of searching for the most advantageous combination of UAV design parameters depending on its purpose can be considered as the task of searching for the extremum of some target function – optimization task. Based on the conducted substantiation the authors propose the technique of defining the rational appearance of an unmanned aerial vehicles, considering the accepted restrictions.

Free Form Deformation Method Applied to Modeling and Design of Hypersonic Glide Vehicles

The aerodynamic shape of the hypersonic glide vehicle (HGV) has become a research topic nowadays due to its excellent aerodynamic performances. Some limitations need to be reduced when the free-form deformation (FFD) method is applied to parametric modeling and design of an HGV. In this paper, a typical lifting body is considered as an example, and we propose a border-based FFD modeling method that transforms the boundary of FFD lattice into the border of the windward side. Then, the superiority of the border-based FFD modeling method is demonstrated by comparison with the traditional FFD modeling method, and the mesh quality parameters are used to validate the well-deformed model and good geometric continuity of the proposed method. Finally, the border-based FFD modeling method is applied to deformable modeling and aerodynamic simulation of three typical HGV shapes. The results show that the higher efficiency, wider design space, and better applicability are performed by using the border-based FFD modeling method that outperforms the traditional FFD modeling method, and this method we proposed can allow a designer to achieve the better aerodynamic shape of HGVs.

The inclusion of vehicle shape and aerodynamic drag estimations within the life cycle energy optimisation methodology

The present work describes a widening of the scope of the Life Cycle Energy Optimisation (LCEO) methodology with the addition of shape-related design variables. They describe the curvature of a vehicle which impacts its aerodynamic drag and therewith its operational energy demand. Aerodynamic drag is taken into account through the estimation of the drag coefficient of the vehicle body shape using computational fluid dynamics simulations. Subsequently, the aforementioned coefficient is used to calculate the operational energy demand associated with the vehicle. The methodology is applied to the design of the roof of a simplified 2D vehicle model which is both mechanically and geometrically constrained. The roof is modelled as a sandwich structure with its design variables consisting of the material compositions of the different layers, their thicknesses as well as the shape variables. The efficacy of the LCEO methodology is displayed through its ability to deal with the arising functional conflicts while simultaneously leveraging the design benefits of the underlying functional alignments. On average, the optimisation process resulted in 2.5 times lighter and 4.5 times less life cycle energy-intensive free shape designs. This redesign process has also underlined the necessity of defining an allocation strategy for the energy necessary to overcome drag within the context of vehicle sub-system redesign.

The Prediction of Narrowband Noise Emitted from Real Vehicle Shape

The Prediction of Narrowband Noise Emitted from Real Vehicle Shape

CMNet: A Connect-and-Merge Convolutional Neural Network for Fast Vehicle Detection in Urban Traffic Surveillance

A wide variety of vehicle detection approaches using the deep convolutional neural network (CNN) have achieved great success in recent years. However, the existing CNN-based feature extraction algorithms, especially residual network, cannot obtain powerful semantic information in the vehicle detection task, and thus suffer from the problem of a missing detection, error detection, or repeated detection. In this paper, we present a connect-and-merge convolutional neural network (CMNet) for fast detecting vehicles in complex scenes. First, we propose a connect-and-merge residual network (CMRN) for performing feature extraction. Specifically, the CMRN assembles residual branches in parallel through a connect-and-merge mapping: Connect the input to the outputs of two residual branches separately (Connect), and merge the outputs of the connection as the input of the subsequent residual block (Merge), respectively. Second, we present a multi-scale prediction network (MSPN) to accurately regress the vehicle shape and classify vehicle fine-grained categories. In addition, the feature maps from the CMRN are merged with their corresponding upsampled features from the MSPN using concatenation. Thus, we can improve the information flow of the framework and make it easy to train. The experimental results on the KITTI dataset and the UA-DETRAC dataset demonstrate that the CMNet can achieve efficient detection performance in terms of accuracy and speed for the real-world traffic surveillance data.

A methodical approach for improved control of safety-related product properties in early phases of the automotive product development process

Pedestrians are among the most vulnerable participants in current urban traffic. For this reason, the legal requirements for vehicle-related pedestrian protection are becoming increasingly stringent, which requires the development of more effective protection concepts. The development of constructive and technological traffic safety measures usually takes place within the framework of a company-specific product development process, which is divided into different phases. Many fundamental considerations regarding the design of the vehicle take place primarily in phases such as product planning or automotive design process (in the sense of the creative vehicle shaping process), which permit few detailed and resilient technical evaluations. Using the example of the automotive design process, an approach for a procedure model is presented that is intended to support the evaluation of safety-relevant product properties in the early phases of product development. The main components are on the one hand the structured analysis and classification of product models with regard to their technical evaluability. On the other hand, in order to support the safety-related development process to be mastered by integrating suitable tools, the basic procedure for the subsequent targeted adaptation of design methods is described.

Designing of the body shape of an autonomous underwater vehicle using the design of experiments method

The process of designing autonomous underwater vehicles comprises several steps, including the designing of the body shape. The hydrodynamic designing of the body shape is a major step in designing the body of an underwater vehicle. The effective parameters in the hydrodynamic design of body shape include the lengths of nose and tail, nose and tail profiles, and also the dimensions of the blunt sections in front of the nose and behind the tail. In the present study, the design of experiments method has been employed to investigate the effect of each of the above parameters on the drag coefficient of an autonomous underwater vehicle body. For this purpose, in addition to introducing the body classes of the Hydrolab family of underwater vehicles, the numerical simulation results of fluid flow over the body of a Hydrolab500 AUV have been used for the design of experiments. In the first step, an experiment has been performed in water tunnel on a test model in order to validate the pressure profile for the body of Hydrolab500. The comparison between the empirical and numerical results related to Hydrolab500 body confirms the validity of the numerical approach used in this paper. The results of the present work show that the drag coefficient of an autonomous submersible in the final design can be accurately estimated with the help of the presented method.

Impedance control on rack steering vehicle for inertia shaping on cornering track

Overdriven factor in a vehicle motion is one of the issues that need to be tackled for safety and energy efficiencies, especially in the cornering track. This issue is crucial especially for rack steering vehicle with non-holonomic configuration, whereby inertia will contribute to high collisions to the peer walls or offroad incidents. Therefore this study has taken the initiative to propose a dynamic control technique that considers the interaction between the vehicle and the terrain using impedance control. This control technique allows coping with the issue by indirectly shaping inertia forces. The proposed impedance control is derived by handling the vehicle dynamic developed and shaping the vehicle steering angle. For the study purposes, a rack steering four wheels vehicle (RT4WV) is used as a platform, and its dynamic model was derived for analysis. The implementation of torque feedback based impedance control for inertia shaping is emphasized on both vertical (x axis) and horizontal (y axis) of the vehicle body, during which inertia could happen. The kinodynamic input for the system control input is the difference between steering angular changes in which representing front wheel angular changes. This proposed dynamic control strategy is verified by simulating the derived impedance control on RT4WV system model with road terrain and aerodynamic frictions as disturbances. The result shows that the proposed impedance control able to reduce the inertia forces via shaping the steering angular input to the vehicle although there have both road terrain and aerodynamic frictions, especially in cornering tracks.

Experimental Study of Flow Control Over a Standard Road Vehicle Using Plasma Actuator

Abstract Ahmed Body is a standard and simplified shape of a road vehicle that's rear part has an important role in flow structure and it's drag force. In this paper flow control around the Ahmed body with the rear slant angle of 25° studied by using the plasma actuator system situated in middle of the rear slant surface. Experiments conducted in a wind tunnel in two free stream velocities of U = 10m/s and U = 20m/s using steady and unsteady excitations. Pressure distribution and total drag force were measured and smoke flow visualization carried out in this study. The results showed that at U = 10m/s using plasma actuator suppress the separated flow over the rear slant slightly and be effective on pressure distribution. Also, total drag force reduces in steady and unsteady excitations for 3.65% and 2.44%, respectively. At U = 20m/s, using plasma actuator had no serious effect on the pressure distribution and total drag force.

Rear-Approaching Vehicle Detection using Frame Similarity base on Faster R-CNN

In this paper, we propose a new algorithm to detect rear-approaching vehicle using frame structure similarity based on deep learning algorithm for use in agricultural machinery systems. The commonly used deep learning models well detect various types of vehicles and detect the shapes of vehicles from various camera angles. However, since the vehicle detection system for agricultural machinery needs to detect only a vehicle approaching from the rear, when a general deep learning model is used, a false positive is generated by a vehicle running on the opposite side (passing vehicle). In this paper, first, we use Faster R-CNN model that shows excellent accuracy rate in deep learning for vehicle detection. Second, we proposed an algorithm that uses the structural similarity and the root mean square comparison method for the region of interest(vehicles area) which is detected by Faster R-CNN between the coming vehicle and the passing vehicle. Experimental results show that the proposed method has a detection rate of 98.2% and reduced the false positive values, which is superior to general deep learning method.

Qualitative Assessment of Aerocapture and Applications to Future Missions

We examine the current state of readiness of aerocapture at several destinations of interest, to identify what technologies are needed and to determine if a technology demonstration mission is required, before the first use of aerocapture for a science mission. The study team concluded that the current state of readiness is destination dependent, with aerocaptured missions feasible at Venus, Mars, and Titan with current technologies. The use of aerocapture for orbit insertion at the ice giant planets Uranus and Neptune requires at least additional study to assess the expected performance of new guidance, navigation, and control algorithms and possible development of new hardware, such as a mid-lift-to-drag entry vehicle shape or new thermal protection system materials. A variety of near-term activities could contribute to risk reduction for missions proposing the use of aerocapture, but an end-to-end, system-level technology demonstration mission is not deemed necessary before the use of aerocapture for a NASA science mission.

Designing the interaction of automated vehicles with other traffic participants: design considerations based on human needs and expectations

Automated vehicles (AV) are expected to be integrated into mixed traffic environments in the near future. As human road users have established elaborated interaction strategies to coordinate their actions among each other, one challenge that human factors experts and vehicle designers are facing today is how to design AVs in a way that they can safely and intuitively interact with other traffic participants. This paper presents design considerations that are intended to support AV designers in reducing the complexity of the design space. The design considerations are based on a literature review of common human–human interaction strategies. Four categories of information are derived for the design considerations: (1) information about vehicle driving mode; (2) information about AVs’ manoeuvres; (3) information about AVs’ perceptions of the environment; and (4) information about AVs’ cooperation capabilities. In this paper, we apply the four categories to analyse existing research studies of traffic participants’ needs during interactions with AVs and results of the CityMobil2 project. From the CityMobil2 project we present central results from face-to-face interviews, an onsite-survey and two focus groups. To further support the AV designers we describe and rate different design options to present the information of the four categories, including the design of the infrastructure, the vehicle shape, the vehicle manoeuvres and the external human–machine interface of the AV.

Model predictive path following control for autonomous cars considering a measurable disturbance: Implementation, testing, and verification

Abstract Model predictive control (MPC)-based path following schemes for autonomous cars represent a novel and highly debated control approach. Their high online computational load poses a challenge for practical real-time application in vehicle systems with fast dynamics. This paper proposes an implementation scheme for an MPC path following controller that considers the feasible road region and vehicle shape. Moreover, the model mismatch induced by varying road conditions and small-angle assumptions is considered in the form of a measurable disturbance. To solve the optimization problem for the proposed MPC path following controller, a differential evolution (DE) algorithm is adopted. To verify the computational performance of the proposed implementation scheme, an experimental platform was developed that consists of the Hongqi autonomous car HQ430, various sensors, and systems for communication and data processing. The experimental results indicate that the proposed DE-based implementation strategy for the MPC path following controller achieves good computational performance and satisfactory control performance for path following in autonomous cars.

Practical Endurance Estimation for Minimizing Energy Consumption of Multirotor Unmanned Aerial Vehicles

The practically applicable endurance estimation method for multirotor unmanned aerial vehicles (UAVs) using a battery as a power source is proposed. The method considers both hovering and steady-level flights. The endurance, thrust, efficiency, and battery discharge are determined with generally available data from the manufacturer. The effects of the drag coefficient related to vehicle shape and payload weight are examined at various forward flight speeds. As the drag coefficient increases, the optimum speed at the minimum required power and the maximum endurance are reduced. However, the payload weight causes an opposite effect, and the optimal flying speed increases with an increase in the payload weight. For more practical applications for common users, the value of S × Cd is determined from a preliminary flight test. Given this value, the endurance is numerically estimated and validated with the measured flight time. The proposed method can successfully estimate the flight time with an average error of 2.3%. This method would be useful for designers who plan various missions and select UAVs.

Aerodynamic heating of inflatable aeroshell in orbital reentry

The aerodynamic heating of an inflatable reentry vehicle, which is one of the innovative reentry technologies, was numerically investigated using a tightly coupled approach involving computational fluid dynamics and structure analysis. The fundamentals of a high-enthalpy flow around the inflatable reentry vehicle were clarified. It was found that the flow fields in the shock layer formed in front of the vehicle were strongly in a chemical nonequilibrium state owing to its low-ballistic coefficient trajectory. The heat flux tendencies on the surface of the vehicle were comprehensively investigated for various effects of the vehicle shape, surface catalysis, and turbulence via a parametric study of these parameters. In addition, based on the present results of the computational approach, a new heating-rate method was developed to calculate the heat flux of the nonequilibrium flow. It was demonstrated that the method could well-reproduce the heat flux on the inflatable reentry vehicle.

Vehicle Counting Based on Vehicle Detection and Tracking from Aerial Videos.

Vehicle counting from an unmanned aerial vehicle (UAV) is becoming a popular research topic in traffic monitoring. Camera mounted on UAV can be regarded as a visual sensor for collecting aerial videos. Compared with traditional sensors, the UAV can be flexibly deployed to the areas that need to be monitored and can provide a larger perspective. In this paper, a novel framework for vehicle counting based on aerial videos is proposed. In our framework, the moving-object detector can handle the following two situations: static background and moving background. For static background, a pixel-level video foreground detector is given to detect vehicles, which can update background model continuously. For moving background, image-registration is employed to estimate the camera motion, which allows the vehicles to be detected in a reference coordinate system. In addition, to overcome the change of scale and shape of vehicle in images, we employ an online-learning tracker which can update the samples used for training. Finally, we design a multi-object management module which can efficiently analyze and validate the status of the tracked vehicles with multi-threading technique. Our method was tested on aerial videos of real highway scenes that contain fixed-background and moving-background. The experimental results show that the proposed method can achieve more than 90% and 85% accuracy of vehicle counting in fixed-background videos and moving-background videos respectively.

Grid fins shape design of a launch vehicle based on sequential approximation optimization

This paper performed the optimization of grid fins shape of a launch vehicle based on Sequential Approximation Optimization (SAO) and Computational Fluid Dynamics (CFD) simulation coupling. An efficient and reliable method is proposed for determining the width of Gaussian functions based on a logical relationship between the width and local density. The performance of the proposed method is evaluated using five classical test functions. The proposed method for width determination generates almost no excessive calculation costs, and improves the accuracy, reliability, and stability of the Radial Basis Function (RBF) surrogate model notably. Based on the improved RBF surrogate model, a framework and detailed procedure for the SAO algorithm is presented, and the performance of the proposed SAO algorithm is tested, with obtained results showing that the proposed SAO algorithm reduces the calling times of the original model and improves the optimization efficiency remarkably. The objective function is strictly deduced and reflects the momentum loss caused by aerodynamic drag directly. Three constraints are imposed to ensure the static stability and controllability of the launch vehicle. Finally, grid fins shape optimization problem of the launch vehicle is solved, with the objective function and constraints calculation tasks accomplished automatically by batch mode CFD simulations. The global optimal solution is obtained after 54 calling times of the original model, and 92 h (3.84 days) of computation on a 96-core cluster. Once the baseline shape is replaced with the optimized shape, it is detected that (1) taking the minimum fuel as an objective function, the take-off mass is 2.07% lighter than the take-off mass of the baseline shape, (2) taking the maximum payload mass as an objective function, the payload mass is 14.3% heavier than the payload mass of the baseline shape.

Collision-Free Navigation of Autonomous Vehicles Using Convex Quadratic Programming-Based Model Predictive Control

Collision-free navigation of autonomous vehicles by means of convex quadratic programming (CQP) based model predictive control (MPC) is considered in this paper. A new collision-free navigation function is designed for real-time collision avoidance of an autonomous vehicle in both static and dynamic environments. Furthermore, vehicle shape is taken into consideration during trajectory generation as a convex polygonal region defined by linear constraints rather than a single point. Then, the MPC optimization problem with the vehicle shape is solved as a CQP-based MPC scheme in the sense of path planning. Compared to the previous MPC, which can only be reduced to a nonlinear programming problem, the control sequences of CQP-based MPC can be obtained quickly with improved real-time system performance. Simulations in diverse scenarios, including a real vehicle dataset, show the validity of the proposed approach.

RECOVERING THE 3D POSE AND SHAPE OF VEHICLES FROM STEREO IMAGES

Abstract. The precise reconstruction and pose estimation of vehicles plays an important role, e.g. for autonomous driving. We tackle this problem on the basis of street level stereo images obtained from a moving vehicle. Starting from initial vehicle detections, we use a deformable vehicle shape prior learned from CAD vehicle data to fully reconstruct the vehicles in 3D and to recover their 3D pose and shape. To fit a deformable vehicle model to each detection by inferring the optimal parameters for pose and shape, we define an energy function leveraging reconstructed 3D data, image information, the vehicle model and derived scene knowledge. To minimise the energy function, we apply a robust model fitting procedure based on iterative Monte Carlo model particle sampling. We evaluate our approach using the object detection and orientation estimation benchmark of the KITTI dataset (Geiger et al., 2012). Our approach can deal with very coarse pose initialisations and we achieve encouraging results with up to 82 % correct pose estimations. Moreover, we are able to deliver very precise orientation estimation results with an average absolute error smaller than 4°.

Have pedestrian subsystem tests improved passenger car front shape?

Subsystem impactor tests are the main approaches for evaluation of safety performance of vehicle front design for pedestrian protection in legislative regulations. However, the main aspects of vehicle safety for pedestrians are shape and stiffness, and though it is clear that subsystem impact tests encourage lower vehicle front stiffness, it is unclear whether they promote improved vehicle front shapes for pedestrian protection. The purpose of this paper is therefore to investigate the effects of European pedestrian safety regulations on passenger car front shape and pedestrian injury risk using recent German In-Depth Accident Study (GIDAS) pedestrian collision data and numerical simulations. Firstly, a sample of 579 pedestrian collision cases involving 190 different car models between 2000–2015 extracted from the GIDAS was used to compare front-end shapes of passenger cars manufactured before and after the legislative pedestrian safety regulations were introduced in Europe. The focus was on changes in passenger car front shape and differences in pedestrian AIS2+ (Abbreviated Injury Scale at least level 2) leg, pelvis/femur and head injury risk observed in collisions. Multi-body simulations were also used to assess changes in vehicle aggressivity due to the observed changes in vehicle shape. The results show that newer passenger cars tend to have a flatter and wider bumper, higher bonnet leading edge, shorter and steeper bonnet and a shallower windscreen. Both the collision data and the numerical simulations indicate that newer passenger car front bumper designs are significantly safer for pedestrians’ legs. However, the results also show that the higher bonnet leading edge in newer passenger cars is poor for pedestrian pelvis/femur protection, even though newer cars show an obviously lower AIS2+ injury risk to younger pedestrians in collisions. Newer cars have a lower AIS2+ head injury risk for pedestrians in collisions, but the numerical analysis indicate that this is not likely due to shape changes in passenger car fronts. Overall, the introduction of pedestrian safety regulations has resulted in reductions in pedestrian injury risk, but further benefits would accrue from tests which promote a lower bonnet leading edge. The influence of vehicle shape on pedestrian head injury risk remains unclear.