Search

This study develops a traffic-responsive control technique for fully-actuated coordinated signals (TCT) to minimize investment in data collection and engineering judgment for signal timing. The operating process of TCT in a day is divided into consecutive cycle sets with N cycles for each. A vehicle detector is placed on every approach lane to detect time headways and actuate the coordinated and uncoordinated phases. Control center creates the background plans for all the intersections once per cycle set. The fully-actuated logic settings are directly determined by the timing parameters of the background plans in signal controllers. Signal controllers operate the fully-actuated logic and yield the expected greens of the 1st through the (N-1)th cycles of the current cycle set for the coordinated and uncoordinated phases. After the Nth cycle starts, the expected greens are sent to control center. Control center processes the expected greens generated in the past cycles of the day and feeds them into Brown's double exponential smoothing to predict the expected base greens of the next cycle set. They pave the way to stepwise creating the new background plan without using any optimization models. The simulation results indicated that the TCT-enabled intersections could reactively vary their vehicle handling capacity to accommodate the variation in the vehicle demand. In contrast to the conventional control technique for fully-actuated coordinated signals, TCT could provide more progression opportunities to the coordinated movement and serve vehicles with less number of stops and equivalent delay from a system-wide perspective.

In this paper, a vehicle center of gravity (CG) height estimation method based on improved You Only Look Once algorithm and AdaBoost regression is proposed by relying on roadside sensors. The CG height of a vehicle plays an important role in the performance evaluation indexes of vehicle handling, ride comfort, and safety. Therefore, the accurate measurement of the CG height is helpful for improving vehicle control and ensuring driving safety. Different from traditional vehicle modeling, in this study, a data-driven roadside estimation method based on machine vision is utilized for the estimation of the vehicle CG height, thereby providing an economic and convenient concept. In terms of vehicle type identification, the improved YOLO algorithm is characterized by flexibility and speed while ensuring high accuracy. This ensures that it can be quickly deployed on roadside equipment and meet real-time requirements. Moreover, through the correlation analysis, parameters including the vehicle’s front track width, rear track width, roof height, and weight, which can be collected by roadside sensors, are selected as input parameters for the regression. An ensemble learning model based on AdaBoost regression realizes the final estimation of the CG height. The test results obtained on the NHTSA experimental data show that the average accuracy of vehicle type identification reaches 97.59% and the regression estimation accuracy of the vehicle CG height reaches 94.64%.

This paper investigates the bandwidth sensitivity of automobile handling, comfort, and stability based on Monte Carlo sensitivity simulations. Performed bandwidth sensitivity simulations include the effects of vehicle geometry and suspension parameters on lateral acceleration, roll angle, front/rear sideslip angles, and yaw rate angle, including both time- and frequency-domain sensitivity analyses. To replicate actual automobile responses, a full-vehicle roll-oriented suspension seven-degree-of-freedom (7-DOF) model was developed and implemented considering a 2-DOF planar two-track model with a nonlinear Pacejka tire model. During the Monte Carlo simulations, 10 mm and 20 mm amplitude sine-wave excitations were used for the left and right sides, respectively, and the frequency was uniformly sampled over the range of 0–30 Hz. Simultaneously, each investigated vehicle parameter varied by ±25% relative to the reference model parameters. These simulations illustrate the sensitivity of the lateral acceleration, roll angle, yaw angle, and sideslip angles to their parameter variations. The results confirm that the road excitation frequency, tire properties, vehicle geometry, and suspension parameters significantly influence the vehicular lateral and roll stabilities when considering the lower and higher peaks and the frequency bandwidths of the lateral and roll stabilities. Interestingly, the longitudinal location of the center of gravity and the tire properties can achieve more significant peak lateral stability responses, as represented by the front and rear sideslip angles and the frequency bandwidth, compared to the other vehicle parameters at high frequencies. Choosing the correct tire properties and vehicle geometry, as well as suspension characteristics, plays an essential role in increasing the vehicular lateral stability and the rollover threshold. Variations in the studied parameters allow for higher vehicular stability when a vehicle is driven on random road surfaces.

Limited slip differential and wings are typical of race cars. Both greatly impact on the vehicle handling (otherwise would not be used). Therefore, the first part of this chapter is devoted to the formulation of a suitable vehicle model, which, in this case, cannot be single track. As a matter of fact, there is a strong interaction between lateral and longitudinal forces. The concept of handling diagram becomes inadequate and must be replaced by the handling surface. This fairly new tool is introduced in the framework of handling of road cars with locked or limited slip differential, The handling of Formula cars is first addressed by means of the handling surface. However, an even more powerful description is given by means of the Map of Achievable Performance (MAP). With this new approach it is possible to better understand the effects of different vehicle set-ups at steady state and also in power-on/off conditions.

In this paper, a new adaptive inverse control (AIC) method is presented to solve vehicle handling inverse dynamics problem and achieve path tracking control for emergency avoidance. The designed AIC system includes two crucial modules: the model identifier and the inverse model controller which are both the nonlinear adaptive filters constituted by neural networks. Firstly, they are both trained offline and connected with the vehicle to be the initial states of AIC system. Then, the back-propagation (BP) algorithm is used to adjust the weight parameters of the model identifier to identify the nonlinear characteristics of vehicle in real time. Simultaneously, the inverse model controller is used to be the controller of AIC system and the controller's weight parameters are tuned by the back-propagation through model (BPTM) algorithm online. A novel adaptive learning rate is introduced into the BP algorithm and the BPTM algorithm to guarantee the stability of neural networks. Finally, the inverse model controller can be regarded as the inverse of vehicle and used to solve required steering wheel angle according to the desired path to realize path tracking. The double lane change (DLC) road is used to be the desired path for emergency avoidance. The simulation results illustrate that the AIC system could realize accurate path tracking although there exist external disturbances and the AIC is an effective method to deal with the handling inverse dynamics problem for emergence avoidance.

Realisation of high-precision trajectory tracking is the key technology to achieve unmanned driving, which has an important impact on vehicle handling stability, safety and comfort. However, many confounding factors seriously restrict tracking performance and pose a great challenge to the design of the controller for tracking the desired trajectory. A comprehensive method that combines feedforward and backstepping sliding mode control is proposed for a four-wheel independent driving–four-wheel independent steering (4WID-4WIS) vehicle, which has the advantages of over-coupling, multiple degrees of freedom and flexible operation. The desired value is the target for the feedforward output of the controller, and the backstepping sliding mode control is used to overcome all kinds of disturbances. A mature and reliable Luenberger observer is designed to achieve good trajectory tracking performance for reducing some sensors. The proposed method is verified via MATLAB/Simulink simulation, which proved that the method has an excellent trajectory tracking performance.

This paper proposes an integrated stability control strategy for tilting vehicles. The work extends the envelope-based lateral stability controller by introducing and enforcing the roll envelope in the optimal control design. The model predictive controller (MPC) scheme is adopted to apply the control effort only when the predicted vehicle states are leaving the safe envelopes. The non-minimum phase problem in active tilting control is handled by utilizing the predictive feature of the controller. It is shown via the simulation in CarSim that, by adopting the envelope-based control scheme, the control effort to maintain the roll stability of narrow vehicles can be greatly reduced. The integrated controller also improves the vehicle handling performance while still guarantees its lateral and roll stability.

This paper focuses on handling improvements enabled through Steer-by-Wire systems, which have increasingly become subject of R&D, as they not only offer the potential for improving vehicle handling but also have many advantages in combination with automated driving. Handling improvements through a steering ratio depending on vehicle speed, as well as steering-wheel angle, are known from Active Front Steering systems. A new overall concept is proposed, that also takes into account lateral and longitudinal acceleration as well as steering rate, which are all available signals in a production car. The overall concept is designed in an optimization process to modify a range of established characteristic parameters known from open-loop maneuvers and the objective evaluation of vehicle handling. In this context, validated models for a vehicle and a Steer-by-Wire system are used to obtain reliable results in simulation. Possibilities for tuning the non-linear steering behavior as well as improvements in the dynamic behavior, especially in yaw damping and response time, are demonstrated.

Chassis is the pat that integrates all components of the vehicle and withstands the load. This load includes the weight of each component and the force that occurs when the vehicle is moving (acceleration, deceleration, and cornering). Chassis should also absorb energy when a collision occurs. The chassis provides a path for the forces that act on it. The suspension pickup points on the chassis are an important parameter in determining the suspension geometry of the vehicle. Torsional Stiffness is determined by the amount of Torque required to deflect the chassis by unit degree. The differences in forces from the suspension linkages that leads to a Twisting Moment. The moment will deflect the chassis about its Roll Axis. Predictable handling of a race car may be achieved by tailoring sis stiffness so that roll stiffness between sprung and un-sprung masses is due almost entirely to the suspension. In this work, the effects of overall chassis flexibility on roll stiffness will be determined using a finite element model (FEM) of a Formula Student Chassis and suspension. The Validation of the model is done by designing and fabricating a test rig to experimentally determine the Torsional Stiffness. The Suspension linkages are replaced with equivalent length solid tubes to eliminate the suspension compression. The test rig will be capable of applying force through one of the front wheel hubs, the other end of the front axle is kept at zero load. The deflection in chassis can be calibrated using a dial gauge. The objective of this project is to Design and optimize the design of the chassis for meeting the Chassis Stiffness target value to obtain the best Lateral Dynamics. Increasing the Torsional Rigidity will reduce the twist in the Chassis, improving vehicle handling by allowing the suspension components to control a larger percentage of a vehicle's kinematics.

Cornering compliance of an automobile influences the transient response of a vehicle and its handling characteristics. The cornering compliance technique provides much better information about the vehicle handling qualities than the understeer coefficient. This paper discusses about the front and rear cornering compliances for a FSAE vehicle. The relationship between the front, rear cornering compliances and the transient response as well as the vehicle dynamic behavior of a FSAE vehicle is analyzed. A bicycle model is considered for the analysis and simulation of the problem. A state space model for the handling behavior is created in MATLAB/Simulink. An in-house test rig was developed to determine the parameters constituting the cornering compliance such as roll steer, roll camber, lateral force deflection steer, etc. The front wheel compliance and rear wheel compliances are determined under static conditions. The FSAE vehicle is dynamically tested for constant radius test, step steer response tests. The experimental data obtained is compared with the simulated data from the state space model.

Electric vehicles with independently controlled drivetrains allow torque-vectoring, which enhances active safety and handling qualities. This paper proposes an approach for the concurrent control of yaw rate and sideslip angle based on a single input single output (SISO) yaw rate controller. With the SISO formulation, the reference yaw rate is firstly defined according to the vehicle handling requirements, and is then corrected based on the actual sideslip angle. The sideslip angle contribution guarantees a prompt corrective action in critical situations such as incipient vehicle oversteer during limit cornering in low tire-road friction conditions. A design methodology in the frequency domain is discussed, including stability analysis based on the theory of switched linear systems. The performance of the control structure is assessed via: i) phase-plane plots obtained with a non-linear vehicle model; ii) simulations with an experimentally validated model, including multiple feedback control structures; and iii) experimental tests on an electric vehicle demonstrator along step steer maneuvers with purposely induced and controlled vehicle drift. Results show that the SISO controller allows constraining the sideslip angle within the predetermined thresholds and yields tire-road friction adaptation with all the considered feedback controllers.

Autonomous Vehicles (AVs) offer significant advantages in terms of traffic and fuel efficiency accident prevention, and reduced travel time. ‘Sense-plan-act’™ cycle of the AV has been designed and implemented to achieve a high level of active safety that considerably reduces the risk to passengers and pedestrians. However, within existing path planning and tracking algorithms, the subject of passenger comfort has received less attention compared to other AV topics. This paper is aimed at characterizing vehicle handling criteria and path profiles configuration in order to identify self-driving requirements for passenger comfort. The emphasis is given to the efficacy and usability of the classical handling analysis methods from a self-driving perspective. To these aims, we initially establish a framework which is defined by comfortable path profiles and a versatile handling model of an AV. Then, we introduce a directional path tracking unit which optimally implements AV’s trajectories using a controller and a speed regulator. The path tracking unit includes a multi-objective optimizer enabling improvement the handling behavior of the AV. The integration of the proposed methodology into the state-of-the-art AVs’ control system can lead to an enhanced comfort level.

Roughness is one of the most important variables affecting the safety of vehicles on the road. Insufficient road surface roughness can lead to loss of vehicle handling, which in turn leads to an increased likelihood of an accident. Roughness as a variable parameter of pavement must be monitored during the life cycle of the road to ensure its operational capability. The article deals with determining the roughness characteristics using three different devices - TWO, British pendulum tester, and SRS. This is the road surface on the section of the D3 highway in the Povazsky Chlmec tunnel, where road maintenance was planned. The main goal was to compare the quality of the pavement before and after road maintenance, where an increase in the coefficient of skid friction was found after the maintenance of the road.

In this work, the authors precisely concentrate on the subject of enhanced vehicle handling performance of the bicycle model with two-degrees-of-freedom via improved-equivalent-input-disturbance and repetitive control technique. To be specific, improved-equivalent-input-disturbance estimator is inserted into the controller design for attenuating the effect of the crosswind in the considered vehicle system with state-delay. A modified two-dimensional repetitive control design is implemented for improving the accurate tracking performance of the considered model. In particular, by combining an improved-equivalent-input-disturbance approach together with two-dimensional modified repetitive control design, steering angles of front and rear wheels of the considered vehicle have been controlled in order to achieve the accurate tracking performance of the vehicle states. The criteria for the robust asymptotic stability on the basis of Lyapunov stability theory is developed by means of the sufficient conditions which are obtained in the form of linear-matrix-inequalities. Simultaneously, through these inequality conditions, the parameters of proposed improved-equivalent-input-disturbance based repetitive control strategy are designed for improving the accurate tracking performance against the crosswind effect. Finally, simulation results are presented to show that the proposed control design is more effective when aperiodic disturbances occur.

This paper contains the design of a testing device, which was constructed for the purposes of checking functional properties of the innovative solutions of variants of electromagnetic locking devices with potentials of replacing current mechanical brakes used for stopping pallets with loaded cars in parking houses developed by the company KOMA - Industry s.r.o. The testing device consists of two positioning tables, whose moveable parts are anchored perpendicular to each other in the frame of the testing device. An electromagnet and a solenoid generating the force needed for stopping the motion of the pallet is connected to the moveable part of the upright positioning table. The brake ramp made of a ferromagnetic material has a hole at its top surface into which the pin of the solenoid is inserted and is attached to the horizontal moveable part of the positioning table. This paper presents holding force values of the electromagnet, which were obtained by experimental measuring on the created testing unit. Web of Science 107 83 73

Desired optimum handling performance of the vehicle hardly be achieved at high vehicle speed due to unpredictable road condition such as uneven surface and slippery road during raining with the existing control algorithm. This paper is focusing on the integration of two robust controller which are Sliding Mode Controller (SMC) and Feedforward controller into the vehicle simulation model to improve the handling performance of the vehicle. Disturbance rejection problem arises from the SMC controller was highlighted and the solution proposed to overcome it. Through the simulation in Simulink, SMC-Feedforward shows average improvement of approximately 30.42 % and 39.41 % for J-Turn and Double Lane Change (DLC) test respectively. The proposed controller has successfully solved the disturbance rejection problem by minimizing the disturbance effect on the vehicle model, which improve the handling performance of the vehicle in terms of yaw rate and sideslip angle.

In order to improve the handling stability of a vehicle, an optimization method of vehicle handling stability based on D-optimal test design was proposed in this paper. The multibody dynamic model was established and verified by experiments. On this basis, a response surface model was established based on D-optimal test design. An improved genetic-particle swarm algorithm was used to optimize the vehicle handling stability. The general evaluation score of vehicle handling stability was taken as the optimization objective. The vehicle structural parameters, tire and spring characteristics were regarded as design variables. The results showed that the multi-body dynamic model was accurate. After optimization, the general evaluation score of vehicle handling stability increased by 8.98 %; the score of the steering returnability and steady static circular test was increased by 20.43 % and 27.31 %, respectively. Then from the sensitivity of the optimization variables to the stability of the vehicle's handling, the rear wheel lateral stiffness has the greatest impact on it, with a sensitivity of 86.9 %; the wheelbase has the smallest impact on it, with a sensitivity of -3.39 %, which can be reduced in future optimization variable to improve design efficiency.

Suspension system is one of the key parts of vehicle, the performance of suspension system has great influence on vehicle handling stability and safety. In order to improve the performance of suspension system, the Macpherson suspension of a vehicle is taken as the research object, the suspension model is established by ADAMS/Car, and carried out parallel wheel travel simulation to analyze the key parameters variation of camber angle, toe angle, caster angle, kingpin inclination angle and scrub radius. Simulation results show that camber angle and scrub radius are beyond normal design range and require optimization. Wheel alignment parameters are determined by sensitivity analysis, and optimized by ADAMS/Insight. Then carried out simulation to analyze the performance of optimized suspension system. Results show that optimized suspension system satisfies the requirements of vehicle stability and safety.

The article presents preliminary results of the comprehensive assessment of the economic effect for the infrastructure owner from transportation by trains composed with the innovation freight cars with axial load of 27 tons at the specific areas (grounds). Comprehensive economic assessment for the infrastructure owner consists in taking into account changes of expenses for improvement of technical properties of the new car, as well as the expenses for changes of the operation properties of the car handling areas, in particular: • one-time expenses for putting infrastructure of the areas of cars handling with the axial load from 25 to 27 tons in compliance with the new technical requirements; • financial results due to increase of carrying-capacity by means of increase of the weight at the permanent train length; • change of the current and one-time expenses for train traction composed of the innovation cars of increased carrying-capacity when changing the locomotive series and the number of section-kilometers per the unit of transportation operations.Calculations performed for the routes Chegdomyn – Vanino and Chelutay – Nakhodka indicated that effect of transportation in the innovation cars can be both positive and negative for the infrastructure owner depending on the operation and economic properties of the handling area (volume of transported freight in the examined cars, maintenance process of the locomotive runs, etc.).Taking into account the one-time costs for putting the superstructure in compliance with the technical requirements, the financial results of JSC “RZD” is getting worse at the examined routes.Obtained results have preliminary nature as more detailed accounting of expenses is required for putting infrastructure of the train handling areas composed from the cars of axial load 27 tons in compliance with the technical requirements.

This paper presents a rear-wheel steering (RWS) control algorithm to enhance the vehicle handling performance without prior knowledge of tire characteristics. A RWS system is a chassis control module that can effectively improve vehicle maneuverability and stability. Since the tire-road friction coefficient is difficult to obtain in real world application, the proposed RWS control algorithm is designed so that it can be implemented without any tire-road information. The proposed RWS control algorithm consists of steady-state and transient control inputs. The steady-state control input is proportional to the driver's steering input for achieving the desired yaw rate gain. The desired yaw rate gain is obtained through an offline optimization that is aimed to minimize the vehicle lateral velocity. The transient control input consists of feedforward and feedback control inputs. The feedforward input is designed to improve transient responses of the yaw rate. Computer simulation studies have shown that a trade-off relationship between overshoot and response time exists when the RWS control input is a sum of the steady-state and feedforward inputs. To compromise this conflict, a feedback input has been designed. The overshoot can be significantly reduced while the response time is slightly changed via the feedback input. The proposed algorithm has been investigated via computer simulations. The simulation has been conducted for step steer and sine with dwell scenarios under various road friction conditions. The performance of a RWS vehicle was evaluated using objective indices. Simulation results show that the proposed algorithm enhances vehicle handling performance.

Vehicle driving safety is the urgent key problem to be solved by an independent automobile development project. And it is also the premise and one of the necessary conditions for active vehicle safety. A new technique for path tracking with minimum time of vehicle handling inverse dynamics is proposed in this paper. Based on a new optimal control method – Adaptive Gauss Pseudospectral Method (AGPM), the optimal control for path tracking with minimum time problem was converted into a nonlinear programming problem which met the boundary condition and a series of path constraints including path constraint, state constraint, control constraint. And then the problem was solved using the sequential quadratic programming (SQP). The simulation results showed that the proposed method was not sensitive to the initial value and the optimization efficiency was higher compared with indirect methods and traditional direct methods. When solving the problem of path tracking with minimum time as per this method, boundary constraints and path constraints were well satisfied. The algorithm was not only precise but it could also shorten the evaluation period of vehicle handling stability and could reduce the tremendous cost for real vehicle testing. So the maneuverability of two different vehicles that complete the pylon course slalom test road with minimum time can be evaluated objectively by utilizing the method. The model correctness is verified through a real vehicle test.

Comfort, safety, high travel speeds, and low fuel consumption are expected characteristics of modern cars. Some of these are in conflict with one other. A solution to this conflict may be time-varying body geometry realized by moving aerodynamic elements and appropriate systems for controlling their motion. This paper presents a review of existing technical solutions and the results of published research on the effects of active flow control around a vehicle on its dynamic properties. Active aerodynamic systems typically adjust certain aerodynamic characteristics based on the vehicle speed, but systems using other information such as acceleration, yaw rate, steering angle, and brake pressure, as well as fully automatic systems, are also considered. This review provides information on historical and current methods, models, and their effectiveness in designing vehicle bodies and the movable aerodynamic elements mounted on them. Technical solutions in which the driver is an element of the control system, automatic systems, their models, models of movable aerodynamic elements, and coupled dynamic-aerodynamic models are presented. A number of types of moving aerodynamic element solutions used for different purposes are considered in this paper and conclusions are presented.

Stability control system plays a significant role in vehicle dynamics to improve the vehicle handling and achieve better stability performance. In order to study and evaluate the performance of the vehicles in addition to how to control it, it is necessary to identify obtain some models related to the dynamics of the vehicle as well as the tire models. This paper presents fundamentals of vehicle dynamics by introducing vehicle models and tire model, which have been widely adopted for vehicle motion control. This helps to get a basic idea of what parameters and states of a vehicle are important in vehicle motion control. This work is separated into four sections: vehicle planar model, full vehicle model, two degrees of freedom vehicle model (bicycle model) to design the controller, and wheel dynamic model.

To achieve the stability for in-wheel suspension system of electric vehicle, the feedback controller gains of proportional-integral, proportional-integral-derivative, and cascaded proportional-integral-proportional-derivative controller are tuned using a meta-heuristic based flower pollination algorithm to obtain the vehicle handling stability and control. Simulations using proposed algorithm are compared with other methods to showcase the effectiveness of the selected algorithm. The results are indicating better stabilization of suspension systems in regard to displacement and acceleration of vehicle body and wheel.

The mechanical linkage of the steering column can ideally be replaced by a bilateral controller-based steer by wire system. This paper presents an intuitive method of designing a bilaterally controlled steer by wire system based on disturbance observers and reaction torque observers. The presented system can overcome the force sensing demerits of traditional force sensors as well as the demerits of existing steer by wire systems based on bilateral control systems. Feedback torque from the steering rack to the steering wheel conveys important data about the road conditions as well as the vehicle conditions to the driver. Hence, accurate feedback to the driver is vital for smooth vehicle handling. The presented method has the capability of tuning the system as per the desire. The validity of the proposed method has been verified through simulations using real-world vehicle and controller data.

Autonomous and Electrical Vehicles are two development trends for automobile industry. Plenty of sensors are demanded to monitor the traffic condition in autonomous vehicle, hence sustainable and reliable power supply for these sensors is a key issue. For the Electrical Vehicles (EVs), the range extension is a core issue, while energy harvesting approach can solve this problem properly. Therefore, the smart shock absorber is proposed with capacity of both road condition monitoring and energy harvesting. The road condition module is based on a rotation triboelectric nanogenerator, voltage signal is utilized to characterize the smooth, pothole or bump road condition by different amplitudes, and finally upload to the big data cloud to support the intelligence transportation systems (ITS). The energy harvesting module is based on an overrun clutch, which drives the generator rotation along one direction, a speed-increasing gearbox ensures that the generator works under high efficiency domain. Damping force can be adjusted by varying the value of external resistor; therefore, stiffness of the whole suspension can be controlled by external circuit to improve the vehicle handling and ride comfort performances. This smart shock absorber has the potential to popularize the Autonomous Vehicle, Internet of Vehicle as well as Electrical Vehicles.

This document evaluates the overall performance of an active hydro-pneumatic suspension system by comparison method for a special purpose vehicle structure. Firstly, the study includes mathematical modeling and simulation of both conventional and hydro-pneumatic suspension systems. The hydro-pneumatic suspension is a non-linear, complex system. The spring and damping characteristics for the system have been separately constructed. The control structure has been chosen to create a multivariate analysis by using the suspension deflection as a reference point to manipulate the active component of the suspension system with Fuzzy Control method. Finally, the study aims to create a better understanding of how the passive conventional, hydro-pneumatic, and active hydro-pneumatic suspension systems differ in means of comfort and vehicle handling issues.