Search

Four-wheel steering (4WS) is an effective technique to improve handling performance and lateral stability of road vehicles. Conventionally, controllers utilise the driver's actions and vehicle dynamics to coordinate front and rear-axle steering. This paper proposes a novel approach for 4WS controller design, based on the concept of Artificial Flow Guidance (AFG), which relies on a spatially distributed motion reference through a two-dimensional vector field. This field provides high-level guidance while lower-level steering controllers to control axle centres motions relative to the flow. These flow vectors, computed in real-time via simple geometric construction, can be pre-computed globally to evaluate the guidance algorithm's efficacy. When controlling only the front axle, this same approach can function as an autonomous driving system. Relying solely on a spatial reference field and control targets' velocities enables the controller to work in a simple and robust fashion, without using a reference vehicle dynamics model or lengthy parameter tuning. The proposed approach's effectiveness is validated through co-simulation with MATLAB/Simulink and the CarMaker simulation platform. AFG control performance is found to be at least comparable to that of more complex 4WS controllers using methods such as MPC; in the cases considered, AFG provides superior path-tracking performance. [ABSTRACT FROM AUTHOR]

The paper presents a novel control strategy for autonomous vehicles, which can effectively handle the nonlinear effects and uncertainties of the controlled system. This solution is based on a new formulation of the ultra-local model-based control approach. This method can deal with the unknown dynamics and other uncertainties of the vehicle without any further measurement or complex modelling process. The control methods require a reduced-complexity nominal linear model of the system, and the unknown part is continuously estimated by the proposed ultra-local model. The proposed control-oriented vehicle modelling method leads to an increased performance level of vehicle motion. The effectiveness of the proposed method through a high-fidelity vehicle simulator (CarMaker) is illustrated. Moreover, the operation of the control through its implementation on a test vehicle of ThyssenKrupp is also demonstrated. [ABSTRACT FROM AUTHOR]

Semi-active primary suspensions are an effective means of improving ride quality in high-speed railway vehicles in relation to the mitigation of car-body bending vibration. In this paper, prototype magnetorheological (MR) dampers are tested and the results are used to define a mathematical model of the dampers. Then, three control schemes for semi-active primary suspensions are proposed: Skyhook, LQG and Mix-1-Sensor, and their performance is assessed by means of Hardware-In-the-Loop (HIL) tests considering a simple quarter-vehicle model which is run on a real-time board and set in interaction with one physical MR damper. The results show that all three considered control strategies lead to a reduction of car-body vibration by around 30% and a very good agreement is found between HIL tests and numerical simulations in which the physical damper is replaced by the mathematical damper model. The damper model is finally interfaced with a flexible multi-body model of the complete vehicle to provide further assessment of semi-active control. The results of the latter simulations show that the semi-active suspension could provide an improvement of the $ {N_{mvz}} $ N mvz ride quality index in the order of 40–45% with respect to the passive vehicle for all three control schemes. [ABSTRACT FROM AUTHOR]

Polygonalization is a typical non-uniform wear phenomenon that affects the performance and comfort of the vehicle/track system. Therefore, the vehicle system performance could be strictly troubled by polygonal damage close to the wheel circumference at the wheel/rail contact. A 3D vehicle/track an EMU type train consisting of 8 coupled vehicles model has been established. The coupled model car body and bogie frame are considered rigid and integrated with the flexible wheelset, rail, and slab track to investigate the elastic deformation caused by the impact load induced by the wheel polygonalization. The flexible track can be incorporated into the multi-body vehicle model using the movable reference frame formulation. Uncertainty parameters are presented, such as passenger weight, wind force, coefficient friction, and suspension variation. The proposed research is validated based on the existing research work and shows excellent agreement. The simulation result deliberated the vertical wheel-rail force, wheelset acceleration, rail acceleration, rail displacement, and slab track acceleration. The results of this study show that as the wheel polygonal damage amplitude increase, the value of wheel/rail normal forces and the dynamic vibrational response of the wheelset axle increase. Additionally, polygonal wear-induced impact stresses may cause the wheelset axle to resonate. When wheel polygonal damage amplitude and uncertainty parameters are corporate into the system dynamics, the maximum magnitude of the wheelset, rail, and slab track acceleration increases. Besides, the train failure degree is comparable to the polygonised wheel harmonic order, defect parameters, and amplitude of out-of-roundness. [ABSTRACT FROM AUTHOR]

To increase vehicle dynamics modelling accuracy in simulation environments, in this work, we propose a model, where the mutual influence of the vehicle dynamics and tyre wear is taken into account. In this context, simulation-oriented models aim at representing the main features of the vehicle dynamics, while keeping the complexity low, making them suitable for control-oriented analyses and design. The wear model quantifies tyre wear as a tyre mass loss depending on the tyre-road interaction, derived from the vehicle dynamics and kinematics; then, the outcome of this model is consequently used to update the tyre friction characteristics, by modifying the main parameters of the Pacejka's magic formula. We also discuss the steps required to use the model in two-wheeled vehicles, where the roll dynamics plays an important role in the tyre wear. The main features of the developed model are discussed on a motorcycle, as a simulation case-study. [ABSTRACT FROM AUTHOR]

In a typical traffic scenario, automated vehicles are required to interact with surrounding traffic participants, e.g. human-driven vehicles, pedestrians, etc. In this paper, a novel adaptive authority allocation strategy considering the social behaviours of surrounding vehicles is proposed for the shared steering control (SSC) of automated vehicles. First, a Koopman-based potential-field-driven distributed model predictive control (K-PF-DMPC) method is proposed for the modelling of vehicle interaction to describe surrounding vehicle's social behaviour. This method effectively deals with the nonlinearity embedded in the non-cooperative game-based vehicle interaction model, so that the analytical form of Nash equilibrium can be derived for a fast online solution. Then, the SSC system of the automated vehicle is implemented by a weighted summation method. To balance the driving performance and intervention degree while considering the surrounding vehicles' social behaviours, a hybrid fuzzy strategy (HFS) is proposed for allocating the control authority between the driver and automation. The value of authority allocation coefficient is calculated by fusing the outputs from two shared fuzzy controllers, i.e. the enhanced and weakened shared fuzzy controllers, in accordance to the belief of the surrounding vehicle's type. Several numerical simulations and driver-in-the-loop simulator experiments are conducted for validation. Results show that the proposed strategy can provide appropriate steering intervention to the driver owing to the consideration of the surrounding vehicle's social behaviour and obtains the best driver-automation collaboration performance compared with the comparative groups. [ABSTRACT FROM AUTHOR]

A comprehensive RFD-FTC-DCA system is proposed for the hypersonic vehicle with saturation constraints to resist the control surface damage, actuator faults, disturbances and parameter perturbation. Firstly, the hypersonic vehicle fault model is established. Secondly, the robust fault detection (RFD) observer is designed to detect the control surface damage and actuator faults accurately under the influences of disturbances and parameter perturbation. Thirdly, the fault-tolerant control (FTC) law is designed to resist the control surface damage, actuator faults, disturbances and parameter perturbation simultaneously. Finally, a dynamic control allocation (DCA) algorithm is designed to reallocate the FTC law and limit the deflection angle and velocity within saturation constraint. The comparison simulation results are presented to demonstrate that the RFD observer can detect the faults accurately and reduce false alarm rates effectively, the FTC law can resist the control surface damage, actuator faults, disturbances and parameter perturbation simultaneously, and the tracing errors of attack angle, side-slip angle and roll angle are only $ \pm 0.7^\circ $ ± 0.7 ∘ , $ \pm 0.2^\circ $ ± 0.2 ∘ and $ \pm 1.5^\circ $ ± 1.5 ∘ , respectively, and the DCA algorithm can reallocate the FTC law and limit the deflection angle and velocity within saturation values. [ABSTRACT FROM AUTHOR]

We present a general approach to model the motion of a rigid body ground vehicle on a smooth nonplanar road surface. We generalise planar control-oriented models while preserving standard model states, inputs and outputs. We derive our approach from first principles, apply it to existing vehicle modelling approaches and test it through real-world experiments. We demonstrate that our approach improves upon the prediction accuracy of planar models. [ABSTRACT FROM AUTHOR]

In this paper, a typical motion-based modelling and tracking issue is investigated for vehicle targets in linear road segment by a variable structure multiple model (VSMM) method. Vehicle target motions in a road with multiple lanes are described by typical lane keeping and lane changing manoeuvres. To describe trajectories of typical manoeuvres, an Ornstein–Uhlenbeck process and a sine half-cycle are used to model lane keeping and lane changing motions in lateral direction, respectively. Note that starting point and length of lane changing motion are unknown in target tracking. Time-varying model sets are designed based on the current motion model with different motion parameters. A VSMM tracking frame is constructed to obtain target state estimates with time-varying model set. The effectiveness of the proposed typical motion-based tracking scheme is displayed by simulation results on road vehicle tracking. [ABSTRACT FROM AUTHOR]

Countdown timers impact driver behavior significantly and are widely used at signalized intersections in many countries. Literature shows potential vehicle class-specific temporal and spatial variations in driver behavior in the presence of timer. Therefore, first, this paper analyzed the temporal, spatial, and vehicle class-specific impacts of timer on driver behavior in heterogeneous traffic conditions based on variations in acceleration. Second, a Long Short-Term Memory model was developed to model vehicle discharge, incorporating the heterogeneity of traffic and impacts of timer. The performance of the model was compared with that of the Intelligent Driver Model using field trajectory data from three signalized intersections in Kerala, India. The model accurately predicts the following behavior with mixed spacing errors of 0.24 to 0.35 and an average mean squared error of spacing of 1.23. The results were better than, or comparable to, results from recent data-driven car-following models and significantly better than IDM. [ABSTRACT FROM AUTHOR]

The so-called g-g diagram is widely employed to assess the performance of road vehicles since it provides the maximum longitudinal and lateral accelerations that can be extracted from the selected vehicle. The different points of the g-g diagram are usually computed independently from one another, e.g. the maximum longitudinal accelerations corresponding to given lateral accelerations are computed sequentially. In this work, the problem of computing the points of the g-g diagram is transformed into an optimal control problem, which allows to avoid one of the most annoying practical problems often encountered when deriving such diagrams, namely the 'jumps' between different solutions (i.e. large slip vs. small slip solutions at similar lateral acceleration) in adjacent points along the g-g envelope. In the proposed method, the objective is to maximise the area enclosed within the g-g diagram, which has a polar representation. The rate of change of the radial coordinate is the control input. Additional constraints are included to enforce the continuity between the states of the vehicle model in adjacent points along the envelope. These conditions can hardly be enforced using standard methods based on sequential and independent computation of the g-g points. An example of the application of the method is demonstrated on the classic double-track car model with nonlinear tyres. [ABSTRACT FROM AUTHOR]

In this paper, we compared the linear and nonlinear motion prediction models of a long combination vehicle (LCV). We designed a nonlinear model predictive control (NMPC) for trajectory-following and off-tracking minimisation of the LCV. The used prediction model allowed coupled longitudinal and lateral dynamics together with the possibility of a combined steering, propulsion and braking control of those vehicles in long prediction horizons and in all ranges of forward velocity. For LCVs where the vehicle model is highly nonlinear, we showed that the control actions calculated by a linear time-varying model predictive control (LTV-MPC) are relatively close to those obtained by the NMPC if the guess linearisation trajectory is sufficiently close to the nonlinear solution, in contrast to linearising for specific operating conditions that limit the generality of the designed function. We discussed how those guess trajectories can be obtained allowing off-line fixed time-varying model linearisation that is beneficial for real-time implementation of MPC in LCVs with long prediction horizons. The long prediction horizons are necessary for motion planning and trajectory-following of LCVs to maintain stability and tracking quality, e.g. by optimally reducing the speed prior to reaching a curve, and by generating control actions within the actuators limits. [ABSTRACT FROM AUTHOR]

The safety of increasingly automated vehicles is of great concern to regulators, yet crash rates are generally reported by manufacturers using proprietary metrics with limited source data. Without consistent definitions of crashes and exposure, automated vehicle crash rates cannot be meaningfully compared with baseline datasets. The objective of this study was to establish methods to normalize automated vehicle crash rates using one manufacturer's crash reports as a case study. The manufacturer's quarterly crash rates for vehicles using SAE Level 1 and Level 2 automation were compared. Road type was controlled for using data from a naturalistic driving study with the same model vehicles, while driver age was controlled for using demographic ownership surveys. Although Level 2 vehicles were claimed to have a 43% lower crash rate than Level 1 vehicles, their improvement was only 10% after controlling for different rates of freeway driving. Direct comparison with general public driving was impossible due to unclear crash severity thresholds in the manufacturer's reports, but analysis showed that controlling for driver age would increase reported crash rates by 11%. These results establish the need for detailed crash data, crash definitions, and exposure and demographic data in order to accurately assess automated vehicle safety. [ABSTRACT FROM AUTHOR]

Mobility is a vast and comprehensive system where many new multimodal technology revolutions occur. To make strategies of sustainable development, policy makers particularly focus on the residents’ trip scenarios in the long-term future affected by policies but not the extreme accuracy of the predictions. In this paper, we construct a strategic and integrated model of residents’ travel demand and trip pattern based on system dynamics methods. Changes from and relationships between policies, markets and consumers under electrification, automation and sharing revolution in mobility have been considered in this model. This model follows the utility methods in travel cost calculation from MARS and retains the original framework of travel pattern. Moreover, it includes new modes and models under technology revolutions such as (1) new sharing patterns: paratransit; (2) new travel modes: customized shuttle bus and sharing cars and (3) new vehicle models: EVs and Avs. As using the three-level classification system of ownership—mode—model, this strategic analysis model demonstrated a comprehensive structure of future mobility. The validity of model was verified through a case study of Shanghai 2035 with three scenarios developed under possible policy directions. [ABSTRACT FROM AUTHOR]

Faults of railway suspension units may endanger vehicle operation safety. Therefore, timely fault detection of railway suspension is necessary. The reported fault detection method that uses Bidirectional Long Short-Term Memory (BiLSTM) neural network in a denoising autoencoder fashion suffers from a shortcoming that the condition monitoring data under faulty states needs to be ultilized to determine the added noise level. Such data is not always available in practice. In this paper, we modified the BiLSTM such that the output data point is excluded from the input when predicting this specific output data point. The requirement of using condition monitoring data under faulty states is therefore relaxed, as the modified BiLSTM is free from determining the level of added noise. A case study on railway suspension fault detection was presented. We used the railway vehicle dynamics model to generate car body vibration under healthy, three levels of reduced first suspension stiffness states, and three levels of reduced first suspension damping states. We compared the performance of the modified BiLSTM with the linear autoregression model, LSTM, and BiLSTM-DAE models. The results have shown that the modified BiLSTM-based fault detection method performs the best, having the highest area under the receiver operating curve. [ABSTRACT FROM AUTHOR]

This work describes the development of a vehicle state estimator, designed to be employed onboard in real-time, based on the data acquisitions already available within the vehicle CAN bus infrastructure. The proposed estimation algorithm, taking into account the suspension elasto-kinematics, the longitudinal, lateral and combined dynamics of the tyres as well as the aligning interaction torques at the ground, represents at the current stage a significantly complete tool, since it also provides an estimation of road slope and banking angles, generalising the adoption of the presented vehicle model even on highly inclined roads. A further advantage of the presented estimator consists of its capability to identify in real-time and with a good level of accuracy the tyre/road interaction physical characteristics in terms of grip and cornering stiffness. [ABSTRACT FROM AUTHOR]

To enhance the lateral stability of a certain type of high-speed train under bogie's active control, characteristics of inertial actuators that generate control force in the active control system are studied, the control delay of the whole Hardware-in-the-Loop (HIL) system is measured, and multi-objective optimisation for feedback parameters with or without the control delay is achieved in this study. A linear model of bogie lateral dynamics, with two inertial actuators, acting on the front and rear end beams, is established for the optimisation. Correspondingly, a nonlinear vehicle model is established in the Simpack platform for both mathematical simulation and HIL simulation to verify the control effects. As the force source of active control, dynamic characteristics of the inertial actuator with different control strategies are examined. Multi-objective optimal control is carried out on the linear active bogie models with and without the delay measured in the experiment to improve the bogie hunting stability. The control method is then evaluated in a nonlinear vehicle model and HIL simulation. Simulation results show that the lateral dynamic performance of the high-speed train can be effectively improved with the active stability system even with a large time delay. [ABSTRACT FROM AUTHOR]

xComputational representation of real-world systems plays an important role in vehicle analysis. Aiming to improve mobility systems, this article presents the development of a chassis dynamometer and vehicle model describing the vehicle longitudinal dynamics considering the tire-bench contact. The model simulates the longitudinal vehicle-bench tests where the system is powered by the bench's electric motor and the gearbox in the neutral position, considering tire interaction forces, rolling resistance, and system losses. It was implemented in Matlab/Simulink™ and validated by coast-down experiments, starting at 60 km/h and 100 km/h, where the model result curves presented an appropriated representativity for the experimental data. A total movement resistance analysis resulted in a mean error of 6.71% when compared to experimental data, while the literature slip-independent equations presented mean errors between 31.94% and 77.61%. The developed model is a representative approximation of the vehicle-dynamometer set and can predict longitudinal experiments, helping the vehicle evaluation process, and saving time and resources. [ABSTRACT FROM AUTHOR]

Semi-active suspensions are seen as a promising technology to improve ride quality in high-speed railway vehicles as they provide substantial benefits not achievable through an optimisation of the passive suspension while avoiding some drawbacks of full-active control. Previous works showed that semi-active primary suspensions (SAPS) offer significant improvement of ride quality. However, published implementations of this concept did not consider the coupling effects between car-body and bogie vibrations, which play a decisive role in the success of control strategies for SAPS. This paper provides a comprehensive analysis of SAPS to improve vehicle ride comfort, with special attention to the mitigation of car-body bending vibration. A vehicle model considering the coupling of car-body bending and bogie pitch is proposed and used for the synthesis of an LQG controller. The performance of the semi-active suspension and controller is assessed using a detailed flexible multibody system of a high-speed vehicle. The proposed control scheme is shown to be highly effective in reducing car-body vibration in the entire frequency range of interest from 1 Hz to20Hz. A remarkable ride comfort improvement is found in the entire speed range from 150 km/h to 350 km/h. [ABSTRACT FROM AUTHOR]

A growing number of studies have demonstrated the effectiveness and superiority of reverse engineering in using axle box vibration acceleration signals to deduce the operation state of wheelsets. However, there is a lack of discussion and summary on the overall mapping relationship between wheel excitation and axle box response, and there has been no detailed investigation on resonance characteristics of axle box. To address the deficiency, a novel resonant excitation loading method is proposed, which is applied to the vehicle model with flexible wheelset and axle box. Amplitude frequency response (AFR) curve of the resonance characteristics of axle box is obtained. AFR is used to characterise the characteristics of various excitation states of wheel, including wheel polygon, wheel tread flat, and wheel-rail separation state, and the corresponding evolution law is revealed. Finally, through two case studies, the guiding role of axle box resonance characteristics on wheel operation status detection is discussed in detail. Analyses show that mastering the resonance characteristics of axle box is an effective way to deduce the operation status of wheel based on the complex axle box vibration response signal, and it will provide a basis for the quantitative evaluation of wheel local damage. [ABSTRACT FROM AUTHOR]

Vehicle active safety system is the hotspot of current research and development, and the road adhesion coefficient is one of the essential parameters in the development of automobile active safety system, which plays a pivotal role in automobile safety. To improve the real-time performance and accuracy of the road adhesion coefficient, this paper proposes different control methods and compares and analyzes them. To accurately estimate the road adhesion coefficient in real-time, an eight-degree-of-freedom vehicle model was adopted in this paper. According to the tire torque and wheel speed, the adhesion coefficient was estimated based on the second-order nonlinear extended state observer. The experimental data, such as slip rate, using the improved tire model, is based on the recursive least squares method with forgetting factor and fuzzy logic algorithm real-time of tire-road friction coefficient estimation. The results show that the observer can effectively observe utilisation adhesion coefficient, and both control algorithms can estimate the road adhesion coefficient in real-time, effectively and quickly. On different roads, the use of the recursive least squares algorithm resulted in higher estimation accuracy, better robustness, and better control effect than using a fuzzy logic algorithm. [ABSTRACT FROM AUTHOR]

This paper proposes a novel prioritisation model predictive control for improving the handling and stability of all-wheel-drive vehicles configured with an electric motor and an open differential per axle with differential braking capability. The configuration of the powertrain provides a significant handling improvement by optimising front/rear torque distribution. The controller gives a high priority to front/rear torque distribution and, if needed, activates the differential braking. A coupled force prediction model of the vehicle handling dynamics is developed to capture the interaction of longitudinal and lateral tyre forces. Since differential braking causes speed drop, energy waste, and noise, two control actuations are prioritised: (1) front/rear torque shifting, (2) differential braking. Appropriate stability constraints are defined for the vehicle yaw rate and sideslip, dividing the sideslip-yaw rate phase plane into three regions – stable, marginal, unstable – based on which three control objectives are defined. Then, the priorities of the control actuations and the control objectives are combined, and a model predictive control structure is developed for this multi-objective multi-actuation control problem. The predictive controller prioritises the objectives and actuations through the prediction horizon. The performance of the proposed controller is thoroughly evaluated through numerical and full vehicle experimental studies. [ABSTRACT FROM AUTHOR]

Step increase of electric motor torque results in wheel slip during the acceleration of battery electric vehicle (BEV), making vehicle body instability paramount. This is particularly challenging for regulating the torque of electric motor to keep stability in the process of acceleration, for which regulating the wheel slip to an ideal set-point is difficult for the central driving powertrain that adopts one electric motor to drive both left and right wheels by a differential. While much of the research on acceleration slip regulation has focused on solving the wheel anti-slip of internal combustion powertrain by electronic stability programme, comparatively little is known about the wheel slip control by electric motor torque of the central driving powertrain that is the most common style of driveline in the market of BEV currently. Here we discuss a series of studies on the acceleration slip regulation by electric motor torque that, collectively, design an approach of how the nonlinear model predictive controller based on a novel driving dynamics model regulates the wheel slip to an ideal set-point from the ideal slip ratio curve. Testing and validating this approach embedded into vehicle control unit are carried out in a BEV to fully realise the wheel slip control by electric motor torque during the acceleration. [ABSTRACT FROM AUTHOR]

As racing vehicles become more complex, optimising the interaction between subsystems becomes critical for racing performance. In this work, we incorporate two such subsystems into a vehicle model. We investigate the performance benefits of a four-wheel-drive vehicle with independent control over its in-hub motors and active control on the rear wing flap rotation. The performance is evaluated by solving minimum lap time optimal control problems (OCP) for various vehicle configurations. The OCP is transformed into a nonlinear programming problem through direct collocation and is solved by an interior point method. The four-wheel-drive configuration performs better than rear-wheel drive in terms of lap time, finishing the Barcelona circuit 4 % faster. The benefits come mainly from higher longitudinal accelerations. Active aerodynamic control improves performance regardless of the propulsion configuration, leading to another 1 % of lap time improvement on the Barcelona circuit. The optimal aerodynamic control strategy is different between propulsion configurations, particularly on corner exits. This model enables the exploration of optimal torque vectoring controls and their interaction with a vehicle's active aerodynamics. This is needed to guide the design of the increasingly complex racing vehicle controllers of the future. [ABSTRACT FROM AUTHOR]

The introduction of more automation into our vehicles is increasing our ability to avoid or mitigate the effects of collisions. Early systems could brake when a likely collision was detected, while more advanced systems will be able to steer to avoid or reconfigure a collision during the same circumstances. This paper addresses how the post-impact motion of an impacted vehicle could be included in the decision-making process of severity minimisation motion planning. A framework is proposed that builds on previous work by the authors, combining models from motion planning, vehicle dynamics, and accident reconstruction. This framework can be configured for different contexts by adjusting its cost function according to relevant risks. Simulations of the unified system are carried out and analysed from the perspective of vehicle model complexity and collision parameters sensitivity. Additionally, effects are highlighted concerning different modelling decisions, with respect to vehicle dynamics models and collision models, that are important to consider in further research. [ABSTRACT FROM AUTHOR]

As the greenhouse gas emission regulations have strengthened, establishing a sustainable transportation system has become more essential. Thus, studies on the transportation system using electric vehicles have received more research attention. However, operation using electric vehicles has obstacles such as technical limitations of vehicle batteries and insufficient number of charging stations, which can be much affected by the traffic flow changes. Therefore, we propose a robust electric vehicle routing model under road traffic flow uncertainty. An arc segmentation method is used to apply the road traffic flow uncertainty more realistically and mitigate the conservativeness of the solutions. We also use the genetic algorithm with three-layer chromosome encoding schemes. Three-layer chromosome encoding schemes guarantee the feasibility of the solutions by checking the product and battery capacity of electric vehicles. The experiments show that the solutions of the robust electric vehicle routing model tend to visit charging stations more often due to the uncertain road traffic flow. However, simulation experiments show that the robust electric vehicle routing model provides better performance. [ABSTRACT FROM AUTHOR]

Efficient path tracking plays a key role in the overall ride experience of Autonomous Vehicles (AVs). Model Predictive Control (MPC) is one of the most competent techniques which is capable of handling multiple variables and constraints. The performance of this controller heavily relies on the proper choice of the vehicle model used to predict future states. This work proposes a novel MPC framework for the effective adoption of vehicle models to achieve a compromise between MPC's performance and computational cost. To this aim, a Switched MPC (SMPC) using vehicle models with different levels of complexity and fidelity is developed. The SMPC uses a novel supervision scheme to adopt the appropriate vehicle model based on the models' prediction error and MPC's solution time. Two different configurations of SMPC are implemented: (1) A Fuzzy Logic System (FLS), and (2) An adaptive switching supervisor. The outcomes show that both approaches can perform path tracking accurately on roads with varying curvatures for different AV speeds. Moreover, comparisons with the conventional MPCs show that the proposed controllers can perform comparably with selective use of a complex vehicle model. Notably, they benefit from a higher computation efficiency from sidestepping the most complex models during path tracking. [ABSTRACT FROM AUTHOR]

Active steering technology can effectively solve the contradiction between the running stability and curving performance of traditional bogies. However, the execution deviations between the actual and theoretical steering actions, which expressed in this paper as equivalent curvature differences, would occur when mileage error or other abnormal operating conditions happens. In this study, the influence of equivalent curvature differences on running safety was studied, and a steering efficiency evaluation method was proposed. First, the equivalence between the wheel–rail relationship in the under- and over-steering states and that in the passive state was demonstrated by combining analytical and numerical simulation methods. It was concluded that under- and over-steering states do not worsen the running safety of rail vehicles. Then, the formula for wear number with the equivalent curvature difference as the independent variable was derived based on the linear model of the rail vehicle, and the accuracy of the formula was verified using the nonlinear model. Finally, a steering efficiency evaluation method was established, and a steering efficiency evaluation under different equivalent curvature differences and steering rates was conducted. The results of this study can provide a reference for engineering active steering systems. [ABSTRACT FROM AUTHOR]

We present a general approach to model the motion of a rigid body ground vehicle on a smooth nonplanar road surface. We generalise planar control-oriented models while preserving standard model states, inputs and outputs. We derive our approach from first principles, apply it to existing vehicle modelling approaches and test it through real-world experiments. We demonstrate that our approach improves upon the prediction accuracy of planar models. [ABSTRACT FROM AUTHOR]

This paper deals with the control of a hydraulically interconnected suspension system to improve the handling performance of the vehicle. A seven-degrees-of-freedom MATLAB/Simulink vehicle model and an Adams/Car model are used for simulation purposes. A Simscape model for analysing the hydraulic subsystem is also employed. It was observed that the yaw rate and roll responses of the vehicle are influenced to a large extent by the flow control valve opening values. The handling performance of the vehicle was investigated by the control of the orifice valves and their adjustment according to the lateral acceleration inputs. Considerable improvements were obtained in the handling qualities without sacrificing the ride responses, compared to the responses of a passive interconnected suspension. [ABSTRACT FROM AUTHOR]

In this work, we report a novel controller to solve (globally) the position and orientation consensus-based formation problem of multiple nonholonomic vehicles modelled as differential drive robots affected by external disturbances. The controller has the structure of a simple to implement Proportional Integral Derivative (PID) scheme. In order to satisfy the well-known Brocket stabilisation theorem for nonholonomic systems, we also incorporate a time-varying persistency of excitation term in the angular velocity dynamics. Our proposal reports the first solution to the robust formation problem using a smooth time-varying controller. Simulations are shown to evidence the theoretical findings of this work. [ABSTRACT FROM AUTHOR]

Pedestrians who use wheelchairs (seated pedestrians) report 36% - 75% higher mortality rates than standing pedestrians in car-to-pedestrian collisions but the cause of this mortality is unknown. This is the first study to investigate the cause of seated pedestrian mortality in vehicle impacts using finite element simulations. In this study a manual wheelchair model was developed using geometry taken from publicly available CAD data, and was tested to meet ISO standards. The GHBMC 50th percentile male simplified occupant model was used as the seated pedestrian and the EuroNCAP family car and sports utility vehicle models were used as the impacting vehicles. The seated pedestrian was impacted by the two vehicles at three different locations on the vehicle and at 30 and 40 km/h. In 75% of the impacts the pedestrian was ejected from the wheelchair. In the rest of the impacts, the pedestrian and wheelchair were pinned to the vehicle and the pedestrian was not ejected. The underlying causes of seated pedestrian mortality in these impacts were head and brain injury. Life-threatening head injury risks (0.0% - 100%) were caused by the ground-pedestrian contact, and life-threatening brain injury risks (0.0 - 97.9%) were caused by the initial vehicle-wheelchair contact and ground-pedestrian contact. Thoracic and abdominal compression reported no risks of life-threatening injuries, but may do so in faster impacts or with different wheelchair designs. Protective equipment such as the wheelchair seatbelt or personal airbag may be useful in reducing injury risks but future research is required to investigate their efficacy. [ABSTRACT FROM AUTHOR]

The present research aims to understand the safety over the midblock road sections and proposes a safety framework using the conventional Time to Collision (TTC) measure. In the present work, the safety framework underlines a supporting structure connecting the actions of the surrounding vehicles and assesses the collisions changes for a given subject vehicle. The Framework principally checks the likelihood of lateral overlap and the time gap between the subject vehicle and its surrounding vehicles. Later, for the trajectory data development, an automated trajectory data development tool is built with the help of image processing for generating the trajectory data from the study sections. In supporting the developed safety framework, the lateral movement of the vehicles is modeled precisely with the help of deep learning. Further, the conceptualized safety framework is tested with the developed trajectory data sets over the study sections. From the results, it is observed that, in mixed traffic, the collision points are over the entire geometry of the study section. In the case of homogeneous traffic, the collision instincts are clustered toward the median lanes. With the advancement of technology, trajectory data development can be a real-time exercise, and the safety framework can be implemented. By applying the study methodology, the critical spots over the road network can be flagged for better treatment and improve safety over the sections. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to identify the potential of electric vehicles in current car mobility scenarios. Firstly, distances traveled daily are analyzed to understand if the car usage observed can be satisfied by the expected range of electric vehicles. Secondly, idle times between trips are studied to assess vehicle needs and identify the requirements for electric charging stations to support the trip-chains observed. The datasets were derived from floating car data recorded for 365 days and include more than 30 million trips crossing the Metropolitan City of Turin (Italy). Approximately 70,000 km were observed daily for more than 10,000 vehicles for 400 different vehicle models to identify their activities over 24 hours. This daily activity in the observation period can be considered a reference scenario, in synergy with the battery range, to plan charging points in road networks. Results show that 98% of daily VKT (vehicle kilometers traveled) are lower than 300 km, over a year of observation. Cars are also classified according to their market segment to identify specific vehicle usage, defining a data dictionary to relate the models and segments. For instance, daily VKT values estimated for segment A (city cars) average 34 km, whereas for segment E (executive cars) the average is 75 km. The spatial analysis of idle times reveals a higher number of shorter breaks in the city center compared to peripheral districts, suggesting that recharging solutions should be adapted to zones according to how they are used for parking. [ABSTRACT FROM AUTHOR]

This investigation integrates an alternative fully-parameterized approximation of nonlinear wheel/rail interaction into a simplified vehicle model, and a two-parameter Hopf bifurcation analysis is conducted to reveal the influence of the wheel/rail contact geometry and secondary suspension parameters for high-speed rail vehicles. The bifurcation diagram is compared among the 6 DOFs bogie model, linear and nonlinear 7 DOFs vehicle model, nonlinear 17 DOFs vehicle model, and 3D full DOFs vehicle model. It shows that the nonlinear 7 DOFs vehicle model can meet the requirement of both carbody hunting and bogie hunting simulations. 6 DOFs bogie model can only be used in bogie hunting bifurcation analysis. Linear vehicle model would bring errors in either critical speed or limit circle magnitude. The divergences in the linear terms of rolling radius and contact angle polynomials are significant enough in field operation to cause a noticeable difference in Hopf bifurcation speed. Attention shall be paid to the shape of equivalent conicity and contact angle curve. The crucial parameters to the Hopf bifurcation include the series stiffness and damping coefficient of the yaw damper and the lateral damper damping. However, the requirement of suspension parameters for stability can conflict in carbody hunting and bogie hunting cases. [ABSTRACT FROM AUTHOR]

Under the trend of promoting economy, environmental protection and high efficiency in the urban rail transit industry, this paper proposes a new type of straddle-type rapid transit system. Compared with most straddle-type monorail systems, it has the advantages of low construction cost and low operating cost, which makes it more suitable for urban rail transit system in small and medium-sized cities. In the process of vehicle development and design, in order to achieve the coordination and matching of tire systems and reduce the wear of tire systems, this work uses a multi-objective optimisation method to reduce the guiding torque of each tire system when the vehicle passes through the curve. Based on the vehicle dynamics model, the multi-body dynamics simulation model of the vehicle is established. The guiding torque of each tire system is taken as the optimisation objective, and the position and dynamic parameters of each tire system are taken as the optimisation parameter. Based on the NSGA-II algorithm, the ISIGHT and SIMPACK software are used for co-simulation. Finally, the guiding torque of each tire system is effectively reduced, and the coordination and matching of tire system is realised. [ABSTRACT FROM AUTHOR]

This study investigates the impacts of the sharing economy and vehicle automation on household vehicle ownership by considering the earning potential of household vehicles. While many studies have examined the impact of the sharing economy (namely ridesourcing) on vehicle ownership of ridesourcing customers, there is a gap in understanding its impact on vehicle ownership among ridesourcing suppliers. Data from an original survey are used to develop discrete choice models that evaluate the effects of earning potential, automation, and shared autonomous vehicle services on vehicle transaction decisions. The estimated models are applied to perform national-level simulations. It is found that, in comparison to a non-sharing economy context, individuals in the sharing economy tend to purchase more vehicles in times of income gain, and to preserve their fleets more readily in times of income loss. This study provides evidence that the sharing economy incentivizes some individuals to own more – not fewer – vehicles.. [ABSTRACT FROM AUTHOR]

The extremely broad flight envelope brings remarkable uncertainties to hypersonic vehicles. This paper investigates the longitudinal control problem of hypersonic vehicles with synthetical considerations on multiple modelling uncertainties, especially on time-varying aerodynamic coefficients. To overcome the efficiency loss of aerodynamic control surfaces (ACS), the reaction control system (RCS) is employed to assist the attitude control. An adaptive ACS-RCS compound control is proposed, which deals with uncertain RCS parameters, simultaneously. Other factors including scramjet input saturation, variable geometry inlet, external disturbances and structural flexibilities are also taken into account. Analysis and simulation indicate that preset references can be well tracked with prescribed performances. [ABSTRACT FROM AUTHOR]

This study proposes an approach to the yaw and lateral stability of the vehicle that considers their steady-state trend. This study designs a new linear time-varying model predictive control (LTV-MPC) method based on the 2DOF vehicle model. The tire model curve of the magic formula is simplified into two straight lines to replace the nonlinear characteristic of tires and reduce the solution time of the controller under the premise of a good tracking effect. The lateral stiffness of tires is selected according to the predicted trend of stable state of the vehicle. Simulation results show that, under extreme conditions, the proposed method can effectively track the reference vehicle sideslip angle and yaw rate. The real-time performance of the controller is substantially improved compared with NMPC. [ABSTRACT FROM AUTHOR]

This paper addresses the on-line minimum-time motion planning and control of a black-box racing vehicle model. We present a hierarchical control framework, composed of a high-level non-linear model predictive controller (NMPC) based on an advanced kineto-dynamical vehicle model, a low-level neural network to compute the inverse steering dynamics and a longitudinal controller for the low-level tracking of speed profiles. An off-line identification procedure, consisting of simulated manoeuvres, is defined to learn the high-level and low-level models. A closed-loop simulation is setup to control the black-box vehicle near the limits of handling along a racetrack. Simulation results are compared with the off-line solution of a minimum-time-optimal control problem. [ABSTRACT FROM AUTHOR]

This paper proposes the dissipation of the energy analysis approach for vehicle plane motion stability analysis. The vehicle uses a three-degree-of-freedom vehicle model, and a unified tire-sideslip-angle model suitable for large tire-sideslip-angle and wheel reverse rotation conditions. Two calculation methods of total dissipation of energy are proposed: the integral calculation method and the energy difference calculation method. This paper analyses the system stability of the vehicle model, using the total dissipation of the energy indicator and compares the results with the Lyapunov exponent indicator. It shows that the dissipation of the energy analysis approach has a fast calculation speed, strong interpretability and high calculation accuracy, which can intuitively and quantitatively reveal the global stability characteristics of vehicle plane motion. [ABSTRACT FROM AUTHOR]

As the widespread usage of autonomous vehicles is closer to becoming a reality, substantial consideration should be paid to the extent to which individuals choose vehicular mobility tools. The purpose of this study is to examine vehicle ownership models to better understand the adoption of vehicles by considering some factors such as liability issues, cost, safety, and environmental characteristics. 323 respondents were recruited from Istanbul, Turkey to complete the stated choice experiment through a web-based survey. Multinomial logit and Heteroskedastic mixed logit models were estimated to unravel users' preferences concerning the selection of autonomous vehicles with distinction among private, shared, and ride-hailing vehicles. Results indicate that the adoption of those vehicles varied concerning the aforementioned characteristics, and these findings could help decision-makers to develop a vehicular mobility system for future transportation dynamics. [ABSTRACT FROM AUTHOR]

The present study focuses on modeling roundabout in heterogeneous condition and understanding the effect of change in two-wheeler composition on the entry capacity using microscopic simulation technique. A four-legged roundabout of 25m diameter, located in the city of Chandigarh, India was considered as the study area. As Indian traffic flow is highly heterogeneous due to the presence of vehicles with varying physical and operational characteristics, each vehicle modelled separately in PTV VISSIM. Model calibrations were performed using speed distributions, conflict areas, priority rules, and driving behavior parameters. Comparison with the field data obtained from the study roundabout (indicates the applicability of the developed simulation model in assessing the hypothetical scenarios. Study results indicate that the PCU values remain steady under varying compositions of two-wheelers in the traffic stream. In addition, the effect of two-wheeler proportion on roundabout capacity is insignificant in the study area. [ABSTRACT FROM AUTHOR]

A control strategy based on H ∞ -type static output feedback combined with dynamic feed-forward is proposed to improve the high-speed lateral performance of an A-double combination vehicle(tractor–semitrailer–dolly–semitrailer) using active steering of the front axle of the dolly. Both feedback and feed-forward syntheses are performed via Linear Matrix Inequality (LMI) optimisation. From a practical point of view, the proposed controller is simple and easy to implement, despite its theoretical complexity. In fact, the measurement of the driver steering angle and only one articulation angle are required for the feed-forward and the feedback controllers, respectively. The results are verified using a high-fidelity vehicle model and confirm a significant reduction in yaw rate and lateral acceleration rearward amplification and also high-speed transient off-tracking, and subsequently improving the lateral stability and performance of the A-double combination vehicle during sudden lane change manoeuvres. [ABSTRACT FROM AUTHOR]

Owing to the significant contribution of flexible modals in rigid-flexible multiple body system (MBS) dynamics, model updating before flex-body generation is necessary. Herein, a model-updating method based on the measured frequency response function (FRF) is proposed to modify the finite element model (FEM). To address the complexity of multiple measured responses and high cost of computation, the Kriging surrogate model with a multi-objective function considering the magnitude and shape of each measured curve is proposed. Thereafter, the surrogate model parameters are optimised to calibrate the FEM with the updated values. The model-updating results demonstrate that the simulated FRFs tend to coincide with the experimental FRFs. Moreover, the dynamic performance error of the calibrated model was validated in a rigid-flexible MBS model by comparing the calculated results of the vibration spectrum and ride comfort index with the test results. The results demonstrate that the updating procedure results in variations in the vibration response and ride comfort index, and the prediction of the updated MBS model is closer to the experimental results. The proposed method will improve the efficiency and precision of the MBS model in vehicle dynamics and other structure dynamics. [ABSTRACT FROM AUTHOR]

Lap-time optimisation programs utilising Quasi-Steady-State (QSS) vehicle models are computationally efficient, though inherent simplifications produce inaccuracies. An analysis of the prediction capabilities of a new QSS lap-time optimisation method is presented. A transient vehicle model is formulated with seven degrees-of-freedom (DOF) dynamics. The QSS vehicle model utilises point-mass dynamics, where accelerations are constrained by a bi-quintic piecewise spline surface produced with an identical transient vehicle model. Notable changes to the development of the new QSS model include, evaluation of the acceleration envelope in natural coordinate frame, and the implementation of a normal jerk limit which acts to artificially mimic the yaw inertia resistance during change of direction manoeuvres. Results of the minimum time solution are shown for 90 ∘ left-hand turn, double lane change and full circuit analysis based on Adria International Raceway. An accuracy improvement against previous QSS models is presented. Minimum time results for the new QSS model are within 0.14 % for left turn, 0.24 % for Adria full circuit, and 0.1 % for double lane change. Optimal accelerations, track centreline offset and velocities are presented and compared. [ABSTRACT FROM AUTHOR]

Among other variables, smart tyre systems are capable of determining tyre contact forces. Combining this information with the signals obtained from conventional vehicle sensors, e.g. inertial measurement units, wheel speed sensors and steering wheel angle sensors, improves the estimation accuracy of the states used by the vehicle dynamics controllers of production cars. This study assesses the performance improvement brought by the vertical and longitudinal tyre contact force signals, obtained through smart tyres, to an unscented Kalman filter (UKF) for vehicle speed and sideslip angle estimation, based on a nonlinear vehicle dynamics model. Two UKF designs, excluding and including smart tyre information, are compared by using experimental data from a purposely sensorised high-performance passenger car, along a comprehensive set of manoeuvres. The results show average ∼60% and ∼37% reductions of the root mean square values of the normalised vehicle speed and sideslip angle estimation errors for the filter design receiving the smart tyre information. In comparison with the more conventional UKF design without tyre force inputs, the smart tyre based estimator is also characterised by significantly enhanced robustness and adaptability to typical variations of vehicle and tyre parameters, such as the tyre-road friction coefficient. [ABSTRACT FROM AUTHOR]

Starting from the earliest phases of design of the vehicle and its control systems, the understanding of tyres is of fundamental importance to govern the overall vehicle dynamics. A properly characterised tyre–road interaction model is essential to achieve a reliable vehicle dynamics model on which more design variations can be studied directly in simulation environment optimising both cost and time. The possibility to count on computationally efficient and reliable formulations represents nowadays a great advantage, and the multiphysical Pacejka's Magic Formula (MF-evo) tyre model presented is one of the best trade-off solutions to meet the strict real-time requirements and to reproduce multiphysical variations of the tyre dynamic behaviour towards temperature, pressure and wear effects. A specific methodology has been developed to characterise and to identify the MF-evo parameters with a high grade of accuracy and reliability directly from experimental data. The proposed technique is based on a pre-processing procedure to remove non-physical outliers and to cluster the data, which allows to optimise the multidimensional parameterisation process. To the purpose of validation of the parametrisation routine, data from a motorsport case, exceptionally difficult to reproduce in simulation due particularly significant variations of the tyre dynamics during a single test, have been employed demonstrating the MF-evo model potential and robustness. [ABSTRACT FROM AUTHOR]

The superconducting electrodynamic suspension (EDS) train, which has reached a manned speed of 603 km/h in 2015, and is therefore regarded as one of the most attractive technologies for the higher speed train. In the superconducting EDS train, the discrete layout of ground null-flux coils causes the additional electromagnetic ripples towards the bogies, making the vibration control more essential to ensure the running performance. In this work, a fourteen-degree-of-freedom dynamics model of superconducting EDS train, was established to explore the effective strategy for vibration reduction. This model uses the time domain wave of track irregularity spectrum as the input of vehicle system. MATLAB/Simulink and "Zhai's method" are both adopted to solve the vehicle dynamic model and validate the model. Using these models, the effectiveness of the proportional force and maximum force for the primary suspension was examined. The results show that the maximum force strategy has advantage over the proportional force strategy in terms of energy consumption and vibration sensitiveness. However, the electromagnetic damping control can only suppress the vibration of bogie. To achieve an overall vibration control, the "ON-OFF" sky-hook damping was further introduced to the secondary suspension to suppress the vibration of car body. We find that, the control effect is preferable with the damping value being between 5 kN·s/m and 10 kN·s/m. Therefore, the cooperative control, considering both the primary and secondary suspensions, is necessary to meet the Urban Tracked Aircushion Vehicle Standard and provide theoretical supports for the suspension design of superconducting EDS train. [ABSTRACT FROM AUTHOR]

Visualising the complex assembly in a large CT volume is a difficult task due to the existence of components made of materials with similar X-ray attenuation factors. To resolve the difficulty, we propose a degree of local symmetry (DLS), a new voxel attribute to visualise specific parts based on their local geometric features. The DLS represents a dimensionality of the manifold around a voxel (e.g. the DLS for a local surface will be 2). For a given CT volume, we first extract an isosurface of the target assembly imaged by an X-ray CT device and compute the medial axes of the isosurface. We then compute the DLS values for voxels on the medial axes. Finally, the DLS values are propagated from the voxels on the medial axes to the entire voxels of the input volume. We demonstrate that the DLS works well to selectively visualise the parts in various assemblies, including a simple artificial assembly of several primitive shapes and more complicated vehicle models. [ABSTRACT FROM AUTHOR]