Vehicle Motion Parameters Research Articles

Research on precise route control of unmanned aerial vehicles based on physical simulation systems

In order to understand the precise route control system of unmanned aerial vehicles, the author proposes a research on precise route control of unmanned aerial vehicles based on wireless sensor networks and physical simulation. The author first introduces the definitions of various coordinate systems and related motion parameters of unmanned aerial vehicles. On this basis, the nonlinear dynamic equations and kinematic equations of the unmanned aerial vehicle were obtained through force analysis. Secondly, based on wireless sensor networks, a route control system for unmanned aerial vehicles was designed. There may be deviations between the actual route and the planned route of drones during flight, which not only reduces the quality of operations but also affects operational efficiency. Wireless sensor network is a technology closely integrated with unmanned aerial vehicles, which can be used to control the route of unmanned aerial vehicles. The system consists of four parts: unmanned aerial vehicle platform, sensor nodes, convergence nodes, and control center. The control of the route is completed through a two-dimensional coordinate system following algorithm. Finally, the drone will undergo flight tests before and after the installation of this route control system. The drone before the installation of this system will use traditional route control methods. There are two types of planned routes: straight and curved, with the curve being a circular shape with a radius of 5 km; Record the deviation value between the actual route and the planned route every 150 s during the flight, and compare the control accuracy of the two methods on the route. The experimental results show that the wireless sensor network is more stable in tracking straight and curved routes, and has high accuracy in route control.

Exhaust Emissions from Euro 6 Vehicles in WLTC and RDE—Part 1: Methodology and Similarity Conditions Studies

The article is an attempt to perform an ecological assessment of passenger cars with various types of engines in road emission tests. The main research problem and, at the same time, the goal was to develop a method for determining the exhaust emissions from motor vehicles in real traffic conditions based on results obtained in homologation tests. The tests were carried out on vehicles equipped with gasoline, diesel, and hybrid engines, and the obtained results were analyzed. All of the selected vehicles were of the same class—passenger cars, with a similar curb weight, similar maximum engine power, and in the same emission class (Euro 6d). The authors compared the dynamic parameters of vehicle motion in established emission tests: Worldwide harmonized Light vehicles Test Cycles and Real Driving Emissions. Four procedures were used to analyze and compare the operating conditions of the vehicles in the WLTC and RDE tests, differing in how the phases in the tests were divided as well as having a different methodology for determining the road emissions in the tests. The procedures were as follows: WLTC (where the test was divided and the determination of the road emission of exhaust gases was carried out according to the standard WLTP procedure), RDE (the road test was divided into sections and the exhaust emission was determined according to the standard RDE procedure), WLTC1+2 (the test was divided into phases: 1 + 2, 3, and 4; a combination of phases 1 and 2 corresponding to the urban section of the RDE test), WLTCRDE (where drive phases were divided and emissions determined in the same way as in the RDE procedure, which assumes the division of the test into sections based on vehicle speed). The implementation of the research task in the form of an algorithm procedure when comparing the dynamic parameters of the movement in the WLTC and RDE tests is the leading goal presented in this article. The division of the WLTC test into sections (urban, rural, and motorway) according to the RDE procedure and also the calculation of the total emissions in the test according to this procedure resulted in obtaining similar road emission values in the test.

The straight-line stability analysis of the vehicle with the electronic stability control

BACKGROUND: At present time, branches of industry have been increasingly filled with electronics, capable of controlling different processes in order to achieve demanded paremeters values. Automotive industry, safety issues of which such as vehicle stability and handling are paid much attention, have not become an exclusion. Vehicle safety improvement is one of the areas of development of modern auto-motive industry. Manufacturers permanentally increase the number of control systems and raise the level of control on wheeled vehicle motion parameters in order to achieve the highest possible level of stability and handling. Using of various all-wheel-drive systems becomes more relevant and reasonable. Traction force distribution between all wheels improves dynamic performance indicators, makes cross-country ability better in similar road conditions and allows using algorithms, improving handling and course-keeping ability of a vehicle.
 AIMS: Determination of variation range of the control parameter in order to ensure stable straight-line motion of a vehicle with controlled transmission.
 MATERIALS AND METHODS: The two-axled vehicle, which transmission has an ability of torque distribution between front and rear axles, is considered in the article. The system of diiferential equations in terms of middle wheels side slip angles was made up in the study. The LinardChipart algebraic cri-terion was used to define variation ranges of the control parameter in order to ensure stable straight-line motion of the vehicle.
 RESULTS: The obtained variation ranges of the control parameter are included in the adjustment range of modern torque distribution mechanisms, consequently, it is possible to speak about ability to ensure stability of straight-line motion of a full-wheel-driven vehicle with currently existing mechanisms. The scientific novelty of the study lies in analytical determination of variation range of the control parameter for the case of straight-line motion of a vehicle equipped with the electronic stability control.
 CONCLUSIONS: Practical value of the study lies in establishment of ability to ensure stability of straight-line motion of a full-wheel-driven vehicle with currently existing mechanisms.

Ensemble deep learning-based lane-changing behavior prediction of manually driven vehicles in mixed traffic environments

<abstract><p>Accurately predicting lane-changing behaviors (lane keeping, left lane change and right lane change) in real-time is essential for ensuring traffic safety, particularly in mixed-traffic environments with both autonomous and manual vehicles. This paper proposes a fused model that predicts vehicle lane-changing behaviors based on the road traffic environment and vehicle motion parameters. The model combines the ensemble learning XGBoost algorithm with the deep learning Bi-GRU neural network. The XGBoost algorithm first checks whether the present environment is safe for the lane change and then evaluates the likelihood that the target vehicle will make a lane change. Subsequently, the Bi-GRU neural network is used to accurately forecast the lane-changing behaviors of nearby vehicles using the feasibility of lane-changing and the vehicle's motion status as input features. The highD trajectory dataset was utilized for training and testing the model. The model achieved an accuracy of 98.82%, accurately predicting lane changes with an accuracy exceeding 87% within a 2-second timeframe. By comparing with other methods and conducting experimental validation, we have demonstrated the superiority of the proposed model, thus, the research achievement is of utmost significance for the practical application of autonomous driving technology.</p></abstract>

Advancements in autonomous mobility of planetary wheeled mobile robots: A review

Mobility analysis is crucial to fast, safe, and autonomous operation of planetary Wheeled Mobile Robots (WMRs). This paper reviews implemented odometry techniques on currently designed planetary WMRs and surveys methods for improving their mobility and traversability. The methods are categorized based on the employed approaches ranging from signal-based and model-based estimation to terramechanics-based, machine learning, and global sensing techniques. They aim to detect vehicle motion parameters (kinematic states and forces/torques), terrain hazards (slip and sinkage) and terrain parameters (soil cohesion and friction). The limitations of these methods and recommendations for future missions are stated.

Heaving foil propulsion performance under combined base and perturbation signal inputs

The thrust variation, efficiency, and wake evolution of a flapping foil were investigated for a variety of base and perturbation frequencies. The study was inspired by the complex environment in which fish swim. In this numerical study, the waveform of the perturbation signal was adjusted by the waveform parameter k. The results demonstrate that the addition of perturbations increases thrust in the majority of cases, with square wave perturbations having the most substantial effect. However, the addition of a perturbation signal reduces the propulsion efficiency; a square wave perturbation significantly reduces the propulsion efficiency, while a sinusoidal or approximate sawtooth wave perturbation slightly decrease the propulsion efficiency. The change in the wake structure is closely related to the perturbation signal waveform, base frequency magnitude, and perturbation frequency magnitude, according to the wake structure analysis. The present work provides useful findings for optimizing underwater vehicle motion parameters.

Lateral acceleration tests during circular driving maneuvers and double lane change

The paper presents the analysis of lateral acceleration based on a vehicle traveling in a circle with a double lane change. The maneuvers of driving in a circle and double lane changes were chosen not by accident. Tests were carried out on a popular brand passenger car on wet and dry surfaces. The vehicle is equipped with high-class electronic equipment that records vehicle motion parameters such as lateral acceleration, longitudinal acceleration, speed and others. In the study, the results of maneuvers were statistically analyzed and tabulated in order to compare and influence the comfort of travellers.

Evaluating traffic parameters of vehicles according to registrars when conducting automotive research

The main tendencies in developing the methods of evaluating vehicles movement according to registrars when conducting automotive research of road accidents are considered. It is noted that modern video recorders, in addition to the standard recording of events in the form of video, have additional functions of recording the parameters of traffic, which allows more objective and in-depth investigation of the circumstances of road accidents. Goal. The aim of the work is development of the method of obtaining quantitative data that allow to estimate the parameters of vehicle movement on video recordings made with the help of DVR MiVue-j85. Methodology. Theoretical data of the functionality of the MiVue-j85 video recorder were verified and analyzed during the real experiment. The study includes an analysis of quantitative data to assess the parameters of vehicle movement on video recordings made using a video recorder MiVue-j85. Results. It is noted that this method currently has a number of disadvantages, which are the imperfect system of synchronization, display and recording of the received data using software designed for the DVR. The presence of integrated in the DVR GPS-navigation and G-sensor, make it possible to determine the parameters of the vehicle and the coordinates of the location of the vehicle in the process of changing its dynamics, but with a significant error that does not meet the requirements of accident research. Originality. For the first time, the method of obtaining vehicle motion parameters using a video recorder with a built-in G-sensor is shown. Practical value. The obtained results can be used in practice in the study of the circumstances of the accident. Application of the certain method will allow facilitating the process of reception of initial data, namely the parameters of vehicle movement when studying road accidents.

Simulation Analysis of Vehicle Handling Stability Based on Trucksim

Based on the Trucksim simulation platform and referring to the parameters of the real vehicle, the vehicle body model, tire model, powertrain model, steering system model and braking system model was constructed. After the parametric modeling of the whole vehicle, the steering wheel angle step test was selected for simulation verification referring to the standards of automobile handling stability test in China. Besides, the vehicle handling stability was analyzed with changing part of the vehicle structure parameters. The research result shows that, although the response forms of vehicle motion parameters are different, they all indicate that the faster the vehicle speed is, the more obvious the vibration of vehicle parameter curve will be, and the vehicle handling stability performance will decrease accordingly. In the steering wheel angle step test, by changing the height of the vehicle’s center of mass and the front and rear wheelbases, it can be explained that reducing the height of the vehicle’s center of mass and increasing the wheelbase can improve the handling stability of the vehicle.

Solution of Problems to Ensure Road Safety by Means of Intelligent Transport Systems

The article is devoted to intelligent transport systems based on short-range radio technology (DSRC). The main feature of this type of system is the ability to provide communication between vehicles without the direct involvement of drivers and without access to the global network. This allows to solve a number of problems related mainly to road safety. This article is about collision prediction and the detection of dangerous driving elements. For these problems, mathematical models of their solution are given, a description of the basic terms of the proposed algorithms, and the results of simulation experiments delivered using the traffic simulator Simulation of Urban Mobility are presented. The model for prediction of vehicle collisions is based on methods for approximating vehicle trajectories and their pairwise comparison. The detection of dangerous driving elements is based on the statistical processing of a number of vehicle motion parameters in the visibility range of the such DSRC device.

Identification of vehicle directional parameters using the sigma-point Kalman filters

The article discusses the problem of identifying the parameters of the vehicle's directional movement, which are necessary for the operation of active safety systems (SAB). The inability to determine some of the parameters necessary for the functioning of the SAB by direct measurements with on-board sensors (due to the absence of corresponding sensors in production vehicles) makes it relevant to use indirect computational methods for identifying these parameters, which are based on mathematical structures called observers.
 The purpose of this work is to create a system for identifying vehicle motion parameters, which, using the measurements available on board the vehicle and the mathematical apparatus of the theory of observers and optimal filters, indirectly determines unmeasured parameters that are important for the operation of active safety systems.
 Based on the analysis of existing methods and tools, a diagram of the observer of the parameters of the vehicle's directional movement using the sigma-point Kalman filter is proposed. The observer identifies the lateral component of the vehicle speed vector, the coefficients of the lateral adhesion of the tires to the supporting surface and the wheel slip angles using the vehicle dynamics model and on-board inertial sensors that measure the linear acceleration and yaw rate of the vehicle.
 The observer's performance and adequacy was confirmed by comparing the parameters he identifies with direct measurements made during road tests of the vehicle. There was used a root-mean-square error of identification as a measure for assessing the accuracy with respect to direct measurements of the parameters of course movement. An additional assessment of the adequacy is made by comparing the identified grip characteristic (the dependence of the coefficient of adhesion on the slip angle) with the characteristic obtained by approximation using a mathematical model of the tire. The assessment showed a good quality of identification of course movement parameters provided by the developed observer, which gives grounds to consider it a useful tool for research and development of active safety systems.

Practical speed measurement for an intelligent vehicle based on double Radon transform in urban traffic scenarios

An on-board vision system is recognized as a promising tool for vehicle early warning and monitoring. Timely accurate estimation of vehicle speed is critical in allowing the on-board vision system to calculate the vehicle location, plan a driving path, and apply emergency brakes to avoid accidents. However, the scene images captured by the vision system always suffer from global motion blur, which causes great difficulty in precisely estimating vehicle speed. While extensive efforts have been focused on blurred image restoration and real-time driving speed estimation in highway scenarios, very limited work has addressed urban scenarios in which the vehicle speed is often less than 40 km h−1. In order to bridge this research gap, this study proposes a new method for real-time vehicle speed estimation. Firstly, the spectrum characteristics of blurred images at low vehicle speeds were investigated to determine the relationship between the direction and spacing of the spectrogram and vehicle motion parameters. Then, the blur-direction and blur-scale of the vehicle motion were analyzed by double Radon transform to develop a speed estimation model. Experimental evaluation results demonstrate that the proposed method was able to estimate vehicle speed in urban scenarios without updating the hardware of existing on-board vision systems. The estimation error was below 7.13% and the calculation efficiency of a single frame was 30 ms, both of which meet the practical application requirements of intelligent vehicles.

Bayesian Predictive Beamforming for Vehicular Networks: A Low-Overhead Joint Radar-Communication Approach

The development of dual-functional radar-communication (DFRC) systems, where vehicle localization and tracking can be combined with vehicular communication, will lead to more efficient future vehicular networks. In this paper, we develop a predictive beamforming scheme in the context of DFRC systems. We consider a system model where the road-side unit estimates and predicts the motion parameters of vehicles based on the echoes of the DFRC signal. Compared to the conventional feedback-based beam tracking approaches, the proposed method can reduce the signaling overhead and improve the accuracy of the angle estimation. To accurately estimate the motion parameters of vehicles in real-time, we propose a novel message passing algorithm based on factor graph, which yields a near optimal performance achieved by the maximum a posteriori estimation. The beamformers are then designed based on the predicted angles for establishing the communication links. With the employment of appropriate approximations, all messages on the factor graph can be derived in a closed-form, thus reduce the complexity. Simulation results show that the proposed DFRC based beamforming scheme is superior to the feedback-based approach in terms of both estimation and communication performance. Moreover, the proposed message passing algorithm achieves a similar performance of the high-complexity particle filtering-based methods.

Research on the Comfort of Vehicle Passengers Considering the Vehicle Motion State and Passenger Physiological Characteristics: Improving the Passenger Comfort of Autonomous Vehicles.

Comfort is a significant factor that affects passengers’ choice of autonomous vehicles. The comfort of an autonomous vehicle is largely determined by its control algorithm. Therefore, if the comfort of passengers can be predicted based on factors that affect comfort and the control algorithm can be adjusted, it can be beneficial to improve the comfort of autonomous vehicles. In view of this, in the present study, a human-driven experiment was carried out to simulate the typical driving state of a future autonomous vehicle. In the experiment, vehicle motion parameters and the comfort evaluation results of passengers with different physiological characteristics were collected. A single-factor analysis method and binary logistic regression analysis model were used to determine the factors that affect the evaluation results of passenger comfort. A passenger comfort prediction model was established based on the bidirectional long short-term memory network model. The results demonstrate that the accuracy of the passenger comfort prediction model reached 84%, which can provide a theoretical basis for the adjustment of the control algorithm and path trajectory of autonomous vehicles.

FORENSIC EXAMINATION OF THE ESTABLISHMENT OF CAUSES OF FAULTS IN THE “ACTIVE CURVE SYSTEM” STABILIZATION SYSTEM OF MERCEDES-BENZ GLS500 4MATIC

Establishing of causes and circumstances that could affect failure of both parts individually and mechanisms generally of the “Active curve system” active stabilization system in Mercedes-benz GLS500 4MATIC cars is considered. The relevance of this scientific paper is due to novelty of installing an active stabilizer on vehicles which ensures minimal car body roll. Design, a principle of work and forensic expert research while inspection and study of the “Active curve system” active stabilization system of Mercedes-benz GLS500 4MATIC using modern equipment and research methods are presented. Measures to prevent failure of structural parts and systems are considered, which will ensure reliable and safe work of the “Active curve system” active stabilization system in the process of operation.
 The system allows you to keep a car within the path set by a driver in various driving modes (acceleration, braking, moving along a straight line, while road curves and free rolling). Determination of occurrence of a traffic collision is carried out by comparing actions of a driver and parameters of a car. In case when a driver’s actions (desired driving parameters) differ from the actual vehicle motion parameters, the “Active curve system” active stabilization system recognizes the situation as uncontrolled and starts working. In case of understeer, the “Active curve system” active stabilization system prevents a car from slipping out of turning trajectory by slowing down a rear inner wheel and changing an engine torque. In case of oversteer, skidding of a car during turns is prevented by slowing down a front outer wheel and changing an engine torque. Operation in this case is of a cyclical nature: pressure increase, pressure containment and pressure relief in the “Active curve system” active stabilization system. The system that combines the system of electronic stability control, steering and car suspension is called vehicle dynamics management integrated system.

Two-Stage Kalman Filter for Fault Tolerant Estimation of Wind Speed and UAV Flight Parameters

Abstract In this study, an estimation algorithm based on a two-stage Kalman filter (TSKF) was developed for wind speed and Unmanned Aerial Vehicle (UAV) motion parameters. In the first stage, the wind speed estimation algorithm is used with the help of the Global Positioning System (GPS) and dynamic pressure measurements. Extended Kalman Filter (EKF) is applied to the system. The state vector is composed of the wind speed components and the pitot scale factor. In the second stage, in order to estimate the state parameters of the UAV, GPS, and Inertial Measurement Unit (IMU) measurements are considered in a Linear Kalman filter. The second stage filter uses the first stage EKF estimates of the wind speed values. Between these two stages, a sensor fault detection algorithm is placed. The sensor fault detection algorithm is based on the first stage EKF innovation process. After detecting the fault on the sensor measurements, the state parameters of the UAV are estimated via robust Kalman filter (RKF) against sensor faults. The robust Kalman filter algorithm, which brings the fault tolerance feature to the filter, secures accurate estimation results in case of a faulty measurement without affecting the remaining good estimation characteristics. In simulations, noise increment and bias type of sensor faults are considered.

Simulation of noise generated by a rotary-screw mover as a result of friction

The article describes the theoretical study of the noise generation parameters under friction of a base cylinder of a rotary-screw mover. The analysis of the influence of parameters of the base cylinder (diameter, angle of winding of the helical blade, length) and the vehicle motion parameters (speed, mass) on the noise level arising from mover interaction with a single obstacle is presented in the paper. The conditions for the occurrence of sound vibrations are shown. Analysis of the research results allows us to conclude that a significant noise level generated by the rotary-screw mover can take place only when the vehicle is moving on ice. The created model and the obtained results can be applied by developers of all-terrain vehicles.

ROBUST CONTROLLER FOR SUPERSONIC UNMANNED AERIAL VEHICLE

The article is devoted to the synthesis of robust controllers of supersonic unmanned aerial vehicle motion parameters. During the flight, the velocity and altitude of the aircraft varies rapidly within wide limits. Therefore, the required quality of control on each trajectory is provided by a set of dynamic controllers with constant coefficients. The article substantiates the number of such controllers, researches the range of their efficiency. The obtained restrictions on the amplitude-frequency characteristics and weight functions are given. Transients are shown

Modeling of the scanning transport detector in the VisSim package

The subject matter of the study is the scanning transport detector, which can be used for providing a modern level of the management and organization of motion on the urban road network. It allows to get information that characterizes the parameters of a separate vehicle motion and flow of transport as a whole in real time. The aim of the article is to study the laser scanning transport detector by the computer simulation methods. By the author are previously developed and patented the transort detector and the technologies of motion parameters light traffic regulation on block diagrams level. But the further processing of photodetector pulsed signals formation processes in order to obtain the desired motion parameters was not carried out. Results. The structure of transport detector fragment model for scanning a type case of the vehicle transit on two control zones was developed. The simulation package was chosen, the model of scanning detector work, embodied in the interactive virtual stand form, was developed and tested. It allows the quickly move from modeling to device realization of the investigated system. The subsystems of all scanning process components and measuring-computational operations modeling were developed. It was shown that separate parameters of vehicle motion determination according to the proposed technology is carried out with sufficient presicion. Conclusions. The simulation method confirms the expected functionality and shows the advantages of scanning technology proposed by the author, and devices for its realization. It can be a basis for futher research to create an experimental prototype of the intelligent traffic light system.

The system of acquisition and archiving of motion parameters of mobile systems - mathematical methods, digital filters

The work presents numerical methods and digital filters that enable correction of the measurement signal obtained during experimental tests of vehicle motion parameters. The inertial navigation measuring module used consists of three-axis accelerometers, gyroscopes made in MEMS technology and a magnetometer. The collected measurement data made it possible to refer them to a point in three-dimensional space in order to determine the trajectory of vehicle movement. The article presents numerical methods of rotation of the local coordinate system to the global system and selected digital filters enabling smoothening the measurement signal in real time.