Longitudinal Acceleration Research Articles

Acceleration-based friction coefficient estimation of a rail vehicle using feedforward NN: validation with track measurements

Low friction can lead to poor adhesion conditions between the rail and wheel, which is detrimental to rail vehicle operation and safety. Up to date knowledge of the rail-wheel friction level is currently not available across rail networks, meaning planning mitigation strategies is difficult. This paper presents a real-time friction coefficient estimation algorithm based on a feed-forward neural network (FNN). Unlike conventional methods, the FNN does not depend on slip/adhesion curves or creep force models, and only requires wheelset longitudinal acceleration and speed. The wheelset acceleration and friction measurements are obtained by running a two-car rail vehicle on a friction-modified track with five different levels of friction conditions at four different vehicle speeds. Four different FNNs are trained for four speed conditions, and their estimation performance were validated by training multiple FNNs and testing them in each speed case using new sets of data. Validation results show that the average mean absolute errors from the four FNNs remains below 0.0083.

Possibilities to evaluate the vehicle’s accelerations through MATLAB Simulink simulations

This scientific present paper explores the methods for assessing the longitudinal and lateral accelerations of a vehicle through the combination of experimental validation and MATLAB Simulink simulations. Comprehending these accelerations is essential for a number of uses, such as stability, overall performance analysis, and vehicle safety. The first step of the study is building a detailed Simulink model of the car. With an emphasis on lateral and longitudinal accelerations, this model makes it easier to simulate a range of driving scenarios and explore how a vehicle handles and behaves under different circumstances. A key element of the study is the experimental validation of the Matlab Simulink model, which involves gathering real-world data from vehicle testing and contrasting it with simulated outcomes. Simulink model iterative refinement is made possible by the integration of simulation and experimentation, which ultimately improves the model’s predictive accuracy. The study’s conclusions demonstrate the integrated approach’s potential to advance vehicle dynamics analysis and make cars safer and more effective. Furthermore, it offers insights into the optimization of vehicle designs and the development of innovative control strategies to enhance overall road safety and vehicle performance.

Heart rate reduction during voluntary deep diving in free-ranging loggerhead sea turtles.

Air-breathing vertebrates exhibit cardiovascular responses to diving including heart rate reduction (diving bradycardia). Field studies on aquatic mammals and birds have shown that the intensity of bradycardia can vary depending on diving behaviour, such as the depth of dives and dive duration. However, in aquatic reptiles, the variation in heart rate during deep dives under natural conditions has not been fully investigated. In this study, we released five loggerhead sea turtles (Caretta caretta) outfitted with recorders into the sea and recorded their electrocardiogram, depth, water temperature and longitudinal acceleration. After 3days, the recorders automatically detached from the turtles. The heart rate signals were detected from the electrodes placed on the surface of the plastron. The mean (±s.d.) heart rate of 12.8±4.1beatsmin-1 during dives was significantly lower than that of 20.9±4.1beatsmin-1 during surface periods. Heart rate during dives varied with dive depth, although it remained lower than that at the surface. When the turtle dived deeper than 140m, despite the relatively high flipper stroke rate (approximately 19strokesmin-1), the heart rate dropped rapidly to approximately 2beatsmin-1 temporarily. The minimum instantaneous heart rate during dives was lower at deeper dive depths. Our results indicate that loggerhead sea turtles show variations in the intensity of diving bradycardia depending on their diving behaviour, similar to that shown by marine mammals and birds.

The dynamics of a bicycle on a pump track – first results on modeling and optimal control

Abstract We investigate the dynamics of a bicycle on an uneven mountain bike track split into straight sections with small jumps (kickers) and banked corners. A basic model of the interaction of bicycle and rider proposed and used to derive equations of motion, which capture the possibilities to accelerate the bicycle without pedaling. Since this is a first approach to the problem, only corners connected by straight lines are considered to compute optimal riding strategies. The simulation is validated with experimental data obtained on a real pump track. It is demonstrated that the model effectively captures the longitudinal bike acceleration resulting from the relative vertical motion between the rider’s upper body and the bicycle. Our numerical results are in good analogy with real rider’s actions on similar tracks.

Controlling a vehicle braking and longitudinal acceleration using a seeking control approach

Traditional methods for tracking the paths of driverless vehicles use plant models to determine the corresponding control laws. Due to the intricate interactions between the road and the tires, time-varying characteristics, and unidentified disturbances. It is challenging to create an accurate vehicle model. As a result, data-driven controllers, which are independent of a predetermined plant model are becoming more and more well-liked. This work implements adaptive cruise control (ACC) by employing a control approach called extremum seeking technique (EST), which is a model-free control (MFC), to control a vehicle braking and longitudinal acceleration. The main aim here is to create an ego vehicle that travels at a specific speed with maintaining a secure space with respect to a guide vehicle. A car including an ACC technique called ego car, exploits radar to determine relative velocity and relative space relating to the guiding car. The ACC technique is considered to keep maintain a relatively secure space or a preferred cruising velocity concerning the guiding vehicle. The developed model succeeded to determine the relative velocity and relative space according for the ego car to another guiding car with acceleration not more than ±2 m/s2 and spacing error less than 6 m.

Four-Wheeled Vehicle Sideslip Angle Estimation: A Machine Learning-Based Technique for Real-Time Virtual Sensor Development

In the last few decades, the role of vehicle dynamics control systems has become crucial. In this complex scenario, the correct real-time estimation of the vehicle’s sideslip angle is decisive. Indeed, this quantity is deeply linked to several aspects, such as traction and stability optimization, and its correct understanding leads to the possibility of reaching greater road safety, increased efficiency, and a better driving experience for both autonomous and human-controlled vehicles. This paper aims to estimate accurately the sideslip angle of the vehicle using different neural network configurations. Then, the proposed approach involves using two separate neural networks in a dual-network architecture. The first network is dedicated to estimating the longitudinal velocity, while the second network predicts the sideslip angle and takes the longitudinal velocity estimate from the first network as input. This enables the creation of a virtual sensor to replace the real one. To obtain a reliable training dataset, several test sessions were conducted on different tracks with various layouts and characteristics, using the same reference instrumented vehicle. Starting from the acquired channels, such as lateral and longitudinal acceleration, steering angle, yaw rate, and angular wheel speeds, it has been possible to estimate the sideslip angle through different neural network architectures and training strategies. The goodness of the approach was assessed by comparing the estimations with the measurements obtained from an optical sensor able to provide accurate values of the target variable. The obtained results show a robust alignment with the reference values in a great number of tested conditions. This confirms that the adoption of artificial neural networks represents a reliable strategy to develop real-time virtual sensors for onboard solutions, expanding the information available for controls.

Impacts of g-g-v Constraints Formulations on Online Minimum-Time Vehicle Trajectory Planning

The g-g-v diagram is a popular representation of a vehicle’s maximum longitudinal and lateral accelerations, as a function of its speed. Recently, g-g-v diagrams have been used as performance constraints for online minimum-time vehicle trajectory planning with economic nonlinear model predictive control (E-NMPC). However, in the related literature, the modeling accuracy of the g-g-v formulations was often compromised in favor of computational efficiency for online E-NMPC. This paper compares various formulations of the g-g-v constraints, evaluating their accuracy, computational efficiency and impact on the lap times, when applied by an artificial race driver (ARD) to control a sports car model on a circuit. Also, we propose a new g-g-v diagram formulation, based on convex polytopic and non-convex polynomial constraints. Our formulation yields improved modeling accuracy while preserving a low computational burden for online E-NMPC. Finally, we analyze the vehicle trajectories, to understand how ARD achieves lower lap times through an improved knowledge of the maximum performance.

A Framework for Combining Lateral and Longitudinal Acceleration to Assess Driving Styles Using Unsupervised Approach

A Framework for Combining Lateral and Longitudinal Acceleration to Assess Driving Styles Using Unsupervised Approach

ТЯГОВІ ВИПРОБУВАННЯ МОБІЛЬНИХ МАШИН ІЗ ВИКОРИСТАННЯМ ПРИНЦИПІВ КІНЕМОДИНАМІКИ

The study aims to develop a method for traction testing of mobile machines using the principles of kinemodynamics. To achieve these goals, it is necessary to: justify the method of traction testing of mobile machines using the principles of kinemodynamics; and carry out experimental validation of the proposed test method. Methods and materials. The methodological basis of the work is the principles of kinemodynamics, namely partial accelerations. The development of a test method consists of determining the possibility of measuring the established indicators and assessing the method’s suitability. To determine the power and energy characteristics of mobile machines, it is proposed to use a measuring complex consisting of a linear accelerometer and special software for processing the measured data. Results. A method for traction testing of mobile machines using the principles of kinemodynamics has been developed; experimental validation of the proposed test method was carried out. The essence of the method is the direct measurement of longitudinal accelerations that occur during the acceleration of a car and the subsequent processing of the results of these measurements, using an energy approach based on determining the change (difference) in the kinetic energy of the car over a certain period. This made it possible to determine the force on the wheels of the car, which leads to its acceleration (or maintaining uniformly accelerated motion) and the share of engine power spent on this car. An experimental validation of the developed method was carried out, which consisted of determining the coefficient of agreement of test results with variations in certain specific factors. Conclusions. The use of the principles of kinemodynamics allows us to determine the fraction of force that leads to acceleration during the acceleration of the car and the fraction of engine power expended. Based on the test results obtained by the proposed method, the following analysis can be made: determine the conditions (gear ratio in the gearbox) under which maximum acceleration is possible, determining the share of the maximum possible design force in each gear used to accelerate the machine; determine the weighted average power reserve of the machine engine, which can be used to overcome additional interference. Experimental validation of the proposed method in terms of agreement showed satisfactory results. Keywords: traction tests, method, coincidence coefficient, power, traction force, acceleration.

Comparison of Fuzzy Logic Control and Model Predictive Control for a Smart Adaptive Cruise Control Vehicle System

Adaptive Cruise Control (ACC), Cruise Control (CC), and Automatic Emergency Braking (AEB) serve as the basis of longitudinal automated driving, and as Adaptive cruise control (ACC), cruise control (CC), and automatic emergency braking (AEB) serve as the basis of longitudinal automated driving, and as such have been the subject of much research. Model predictive control (MPC) and fuzzy logic are often considered to be the next steps in improving the capability of these systems, but the two control strategies have not been compared to each other in the ACC, CC and AEB applications. Also, the three features (ACC, CC and AEB) have never been compiled into a single fuzzy logic controller. The purpose of this paper is to design a fuzzy logic-based ACC, CC, and AEB controller and compare it to an equivalent MPC controller. All three controllers control the desired longitudinal acceleration, and their functionality is tested using Matlab’s Fuzzy Logic Designer and other Simulink toolboxes. Ultimately, the results of the analysis demonstrate that the proposed fuzzy controller operates just as well if not better than the MPC controller and that the fuzzy controller is able to operate well in all tested scenarios.

LSTM-Based Virtual Load Sensor for Heavy-Duty Vehicles.

In this paper, a special recurrent neural network (RNN) called Long Short-Term Memory (LSTM) is used to design a virtual load sensor that estimates the mass of heavy vehicles. The estimation algorithm consists of a two-layer LSTM network. The network estimates vehicle mass based on vehicle speed, longitudinal acceleration, engine speed, engine torque, and accelerator pedal position. The network is trained and tested with a data set collected in a high-fidelity simulation environment called Truckmaker. The training data are generated in acceleration maneuvers across a range of speeds, while the test data are obtained by simulating the vehicle in the Worldwide harmonized Light vehicles Test Cycle (WLTC). Preliminary results show that, with the proposed approach, heavy-vehicle mass can be estimated as accurately as commercial load sensors across a range of load mass as wide as four tons.

Determination of Parameters for Limiting Longitudinal Acceleration to Optimize Energy Consumption for Train Traction

Purpose. The main purpose of the article is to improve traction calculations using mathematical modeling when solving the equation of train motion. The train model is adapted to optimize the parameters of train movement during speed gain with the determination of functional relationships between the power of the locomotive power plant and the profile of the track section with the consumption of energy resources by the locomotive. Methodology. Modern methods of mathematical modeling were used to solve the tasks. The modeling of the power plant operation was performed using interpolation and approximation methods. The simulation modeling method was used to create a model of the electrical part of the diesel locomotive transmission. The method of integrating the differential equation of motion was used to calculate the parameters and nature of the train's movement and the problem was solved, which consists in finding a solution to this equation over the length of the traction section, taking into account the variable values of the locomotive power and the slopes of the track profile. Findings. To analyze the results of traction calculations, we obtained such indicators as technical speed and diesel fuel consumption, and compared these indicators. The results show that in the case of acceleration limitation, there is a decrease in diesel fuel consumption at almost unchanged technical speed. Originality. The improvement of energy efficiency of train operation has been further developed, namely, the functional dependence of the relative power of the locomotive power plant, which takes into account the actual profile of the site, has been obtained, which makes it possible to determine energy-saving modes of locomotive control and reduce energy consumption, load on the diesel engine and elements of the diesel locomotive traction transmission during transient modes, which, in turn, in addition to saving diesel fuel, will affect the reliability of the power plant elements. The practical value of the study is to save diesel fuel in the modes of movement that provide speed gain and increase the reliability of the power plant due to reduced load.

Adaptive Distributed Fixed-Time Cooperative Three-Dimensional Guidance Law for Multimissiles against Manoeuvring Target

The problem of cooperative interception of the manoeuvring target is investigated in this paper. Firstly, in light of fast fixed-time consensus theory, time-to-go, and undirected topologies, adaptive cooperative guidance along the line-of-sight (LOS) direction is proposed to guarantee impact time synchronization. Next, novel nonsingular terminal sliding mode (NTSM) is designed to establish adaptive fixed-time guidance law for steering LOS angular rates to the origin or its small neighbourhood. Without the knowledge of target manoeuvre, the proposed cooperative guidance law can be provided by lateral and longitudinal accelerations of each missile, while more reasonable and rigorous analysis of fixed-time stability is carried out through the Lyapunov theory. Within the specified time, both control tasks of simultaneous attack and the desired impact angles can be completed before the final time of the guidance process. Finally, numerical simulations demonstrate the feasibility and effectiveness of the proposed scheme.

Implications of wave–current interaction on the dynamic responses of a floating offshore wind turbine

This study investigates the implications of wave–current interaction on the dynamic responses of the W2Power semisubmersible platform for floating offshore wind turbines under operational and extreme conditions. Firstly, two analytical models based on Airy wave theory are developed to analyse the effects of current interaction with regular and irregular waves. Then, these models are integrated with the well-known engineering tool OrcaFlex for the coupled aero-hydro-servo-elastic analysis. The presence of current was found to significantly modify the wave profiles and influence the static equilibrium, mooring system, and motion dynamics of the FOWT.The results reveal that the translational motion responses, such as surge and heave, are affected by wave–current interaction, with mean and maximum values decreasing under a following current and increasing under an opposing current. However, rotational motion responses are minimally affected. Wave–current interaction also notably affects maximum mooring tensions, with variations of up to ±22% depending on the current direction and mooring layout. Furthermore, reductions in maximum longitudinal acceleration are observed due to such interaction. Incorporating wave–current interaction in simulations enhances our understanding of FOWT dynamics and allows for more reliable estimations of system behaviour, emphasising the importance of ensuring safe operating conditions, particularly in sites with opposing currents.

Post Take-Over Performance Varies in Drivers of Automated and Connected Vehicle Technology in Near-Miss Scenarios.

This study examined the impact of monitoring instructions when using an automated driving system (ADS) and road obstructions on post take-over performance in near-miss scenarios. Past research indicates partial ADS reduces the driver's situation awareness and degrades post take-over performance. Connected vehicle technology may alert drivers to impending hazards in time to safely avoid near-miss events. Forty-eight licensed drivers using ADS were randomly assigned to either the active driving or passive driving condition. Participants navigated eight scenarios with or without a visual obstruction in a distributed driving simulator. The experimenter drove the other simulated vehicle to manually cause near-miss events. Participants' mean longitudinal velocity, standard deviation of longitudinal velocity, and mean longitudinal acceleration were measured. Participants in passive ADS group showed greater, and more variable, deceleration rates than those in the active ADS group. Despite a reliable audiovisual warning, participants failed to slow down in the red-light running scenario when the conflict vehicle was occluded. Participant's trust in the automated driving system did not vary between the beginning and end of the experiment. Drivers interacting with ADS in a passive manner may continue to show increased and more variable deceleration rates in near-miss scenarios even with reliable connected vehicle technology. Future research may focus on interactive effects of automated and connected driving technologies on drivers' ability to anticipate and safely navigate near-miss scenarios. Designers of automated and connected vehicle technologies may consider different timing and types of cues to inform the drivers of imminent hazard in high-risk scenarios for near-miss events.

Investigation of vibration's effect on driver in optimal motion cueing algorithm.

The increased sensation error between the surroundings and the driver is a major problem in driving simulators, resulting in unrealistic motion cues. Intelligent control schemes have to be developed to provide realistic motion cues to the driver. The driver's body model incorporates the effects of vibrations on the driver's health, comfort, perception, and motion sickness, and most of the current research on motion cueing has not considered these factors. This article proposes a novel optimal motion cueing algorithm that utilizes the driver's body model in conjunction with the driver's perception model to minimize the sensation error. Moreover, this article employs H∞ control in place of the linear quadratic regulator to optimize the quadratic cost function of sensation error. As compared to state of the art, we achieve decreased sensation error in terms of small root-mean-square difference (70%, 61%, and 84% decrease in case of longitudinal acceleration, lateral acceleration, and yaw velocity, respectively) and improved coefficient of cross-correlation (3% and 1% increase in case of longitudinal and lateral acceleration, respectively).

Synthetic Drivers’ Performance Measures Related to Vehicle Dynamics to Control Road Safety in Curves

The road alignment design relies on the knowledge of vehicle dynamics variables. However, it assumes that drivers faithfully follow the lane axis on straights and curves. Deviating from this assumption leads to unexpected outcomes and can significantly impact users’ safety. In this context, vehicle speed and longitudinal acceleration play a crucial role as key references in the international standards. They provide insights into critical driving aspects; therefore, it is essential to thoroughly analyze their real trends. Broad data collection campaigns should derive synthetic indicators in order to highlight eventual significant deviations between the ideal and real dynamics. To achieve this objective, the authors propose some indexes deduced during an experimental study with a Sim-Easy driving simulator, by AVSimulation. Importantly, these indicators can be freely applied in real driving scenarios without limitations. These indexes were tested on four different horizontal curves and proved effective in identifying relevant characteristics related to longitudinal acceleration and speed. Looking ahead, by analyzing similar data for numerous driving contexts on real roads, infrastructure managers could use this methodology to identify those sections with increased vulnerability for users’ safety. Moreover, the collected data from sensors, processed using these indicators, can be filtered and transmitted to users (via ADAS tools) while driving on a specific road to provide timely warnings about potential difficulties. The indicators control the physical variable (acceleration or speed) on a certain geometric element with reference to what is prescribed by the standard. For example, the acceleration indicators are normalized with respect to a threshold value while for speed indexes, the result depends on the difference between the end control points of the geometrical element. In both cases, international regulations report prescribed or recommended reference values, so the analyst is immediately aware of any critical issues in the maneuver.

Cold Nuclear Fusion, Based on the Theory of New Axioms and Laws

It is known that the Classical field theory is based on 1 basic Axiom set by Maxwell (1864) (Landau & Lifshitz, 1980). This basic Axiom describes a field with movement along a closed loop and with constant speed. It is an ideal foundation for describing an Electromagnetic Field, but it is not suitable for other more complex fields with variable speed and different accelerations. The author has proposed a more general Theory of Extended Field which consists of 2 Axioms and 8 Laws. New Axiom1 describes a structure of field with movement along open loop or open vortex with variable speed. New Axiom2 describes two mutual orthogonal structures of fields which work in resonance. This new Theory leads to the following results: movement in a closed loop is replaced with movement in an open loop or vortex; evenly movement is replaced with unevenly movement (decelerated or accelerated ); during its movement decelerating vortex emits primary free cross vortices, while accelerating vortices suck in of this same primary free cross vortices; movement in 2D is transformed into the movement in 3D; a transverse vortex in 2D generates a longitudinal vortex in 3D through a special transformation and vice versa - a longitudinal vortex in 3D through another special transformation generates the cross vortex in 2D (Markova, 2003; 2005; 2015). Now the author proposes to use a longitudinal accelerating vortex for cold fusion. With a force proportional to the positive acceleration, it will suck in both vortices and atoms - in this case the isotope of hydrogen (deuterium). The accelerator vortex sucks in and sticks two of all the deuterium, which will form helium in an exothermic reaction with the release of a lot of heat. A longitudinal acceleration vortex can be generated by applying Law 2. A decelerating transverse vortex in plane 2D (moving outside-inward) generates at its center a longitudinal accelerating vortex in 3D perpendicular to the 2D plane. This perpendicular accelerating vortex at the center pulls the transverse decelerating vortex up (against the Gravitational Force) or has quality of Anti-Gravity Force (Markova, 2018a; 2018b; 2020a).

Understanding the behaviour of motorcycle riders: An objective investigation of riding style and capability

Human errors are the primary cause of powered two-wheeler crashes worldwide due to the demanding control required and the often ineffective rider-training programs. Literature on rider behaviour is limited, partly due to the lack of standard investigation methodologies.This work investigated the differences in riding style and capability of a diverse set of riders. It explored the impact of familiarisation and riding instruction through objective metrics. Correlation with experience was a particular focus.Seven riders of various experience levels performed trials on an instrumented motorcycle, following three riding instructions: ‘Free Riding’, ‘Handlebar Riding’, and ‘Body Riding’. Objective metrics assessed rider familiarisation, capability and willingness to excite motorcycle dynamics, riding style, and input preference.Results indicated that riders asymptotically converged to their motorcycle dynamics intensity level after a specific distance; both intensity and distance were positively correlated with experience. Experienced riders achieved higher longitudinal acceleration and utilised combined dynamics to a higher degree. The negative longitudinal jerk during braking varied greatly among riders and correlated with experience. A clustering approach identified two prominent trial groups concerning the motorcycle response intensity. Higher diversity emerged in the inputs, leading to five clusters with distinct riding style meanings. Instructions influenced behaviour, particularly regarding input usage.The unsupervised approach and metrics proposed should make rider behaviour research more straightforward and objective. It could be applied to naturalistic riding sessions for more conclusive evidence of inter-driver differences. The diversity that emerged concerning the command inputs used warrants a revision of training practices to promote riding safety.

Detection accuracy of target accelerations based on vortex electromagnetic wave in keyhole space

The influence of the longitudinal acceleration and the angular acceleration of detecting target based on vortex electromagnetic waves in keyhole space are analyzed. The spectrum spreads of different orbital angular momentum (OAM) modes in different non-line-of-sight situations are simulated. The errors of target accelerations in detection are calculated and compared based on the OAM spectra spreading by using two combinations of composite OAM modes in the keyhole space. According to the research, the effects about spectrum spreads of higher OAM modes are more obvious. The error in detection is mainly affected by OAM spectrum spreading, which can be reduced by reasonably using different combinations of OAM modes in different practical situations. The above results provide a reference idea for investigating keyhole effect when vortex electromagnetic wave is used to detect accelerations.