Real-time Vehicle Dynamics Research Articles

Enhancing Autonomous Vehicle Navigation with a Clothoid-Based Lateral Controller

This study introduces an advanced lateral control strategy for autonomous vehicles using a clothoid-based approach integrated with an adaptive lookahead mechanism. The primary focus is on enhancing lateral stability and path-tracking accuracy through the application of Euler spirals for smooth curvature transitions, thereby reducing passenger discomfort and the risk of vehicle rollover. An innovative aspect of our work is the adaptive adjustment of lookahead distance based on real-time vehicle dynamics and road geometry, which ensures optimal path following under varying conditions. A quasi-feedback control algorithm constructs optimal clothoids at each time step, generating the appropriate steering input. A lead filter compensates for the vehicle’s lateral dynamics lag, improving control responsiveness and stability. The effectiveness of the proposed controller is validated through a comprehensive co-simulation using TruckSim® and Simulink®, demonstrating significant improvements in lateral control performance across diverse driving scenarios. Future directions include scaling the controller for higher-speed applications and further optimization to minimize off-track errors, particularly for articulated vehicles.

Vehicle dynamics response due to the adjustment of K&C parameters with the aid of a dynamic simulator with 9 DOF and a correlated virtual model

Given the increasing use of virtual simulation in automotive vehicle designs, the correlation of virtual models is a fundamental part of the process. The present work seeks to develop a methodology for the development of virtual vehicle dynamics models correlated with kinematics and compliance (K&C) parameters for use in a real-time vehicle dynamics simulator. Aiming this and with the aid of an SPMM 5000e to obtain data from the physical vehicle and from the ADAMS/Car and VI-CarRealTime (VI-CRT) software to the development and simulation and from MATLAB to the correlation, a multibody virtual model correlated in K&C to a hatchback car, with McPherson strut and twist-beam front and rear suspensions, respectively, is developed. At the end of the work, it was observed that the correlation between the virtual model and the test vehicle was found successfully and that, therefore, the virtual simulation allows to find reliable results regarding the vehicle’s suspension and steering system behavior. Subsequently, with the tests carried out with a driver in a VI-Grade DiM 150, a real-time driver-in-the-loop simulator with 9 degrees of freedom (DOF), the model and thus the methodology is validated through the steering ratio analysis: The lateral acceleration analysis in the vehicle’s center of gravity in different maneuvers allowed to observe that the model with higher steering ratio requires greater steering wheel angle values about the model with the lowest steering ratio so that the same maneuver is performed.

Simultaneous real-time assessment of sportive pilots' stress and performance related to vehicle behavior, during racing with the DIM professional simulator

Abstract Background Sports motoring and racing imply high physical and psychological stress, during pre-competition phases and the competition itself. Therefore, there is growing interest of racing teams for new technologies providing real-time monitoring of psychophysiological reactions of pilots to highly-demanding driving and vehicle dynamics, to improve personalized training, while reducing human risks and costs. Professional Driving Simulators (PDS) are ideal to assess in real-time vehicle dynamics under any kind of programmable virtual driving conditions, but a direct connection with the driver's physiology is still limited. A novel wearable system and software have been developed, providing simultaneous assessment of pilot's stress reactions, by real-time calculation and monitoring of time-variant heart rate variability (TV-HRV) spectral parameters (SP) and of skin potential response (SPR), in correlation with vehicle's dynamics. Purpose This study aimed to demonstrate the reliability of the method in detecting the pilot's stress induced by different driving demands. Methods 10 volunteers (age 26±2.3 years) were enrolled to pilot a racing car under realistic conditions simulated by the DIM® PDS (Vi-grade). The study protocol consisted of 5-minutes baseline rest, sitting in the cockpit; 5-minutes driving along a straight highway without obstacles; 6-minutes of medium-stress slalom between cones, avoiding collision; 8-minutes racing 4 laps on a race track, at maximum possible speed, but avoiding crashes. ECG and SPR signals were acquired (1 Khz sample rate), with the Vi-BioBox connected to textile wearable sensors. A proprietary software was developed to analyze and stream the TV-HRV and SPR data in real-time to WINTAX4 data logging software for automotive racing industry. Real-time assessment of the pilot's stress was based on the integration of transient changes of HRV-SP and of the Root Mean Square value of two SPR signals (SPRRMS). To validate the accuracy of the real-time HRV analysis, all data were analyzed also off-line with Kubios Premium 3.4.1. software. Results The Vi-BioBox signals were adequate for real-time calculation and monitoring of transient variations of HRV-SP. A good correlation was found between transient stress-induced increment of pilots' SPRRMS values and the occurrence of driving errors (pink-red spots automatically transferred onto the race track – Figure 1). A good match was found between the real-time HRV values calculated by the VI-BioSoft and their off-line calculation with Kubios (v. 3.4.1 Premium). Two pilots, suffering simulator sickness, had prodromal alteration of cardiac autonomic modulation. Conclusion The integration of a Vi-grade PDS with the novel system for real-time calculation and telemetric monitoring of time-variant HRV and SPRRMS provides immediate information about pilot's autonomic response to driving demands and emotional reaction to vehicle's dysfunction, driving errors and bad performance. Funding Acknowledgement Type of funding sources: None. Figure 1

Research on vehicle performance test based on DirectInput data acquisition

Aiming at the high cost of high-performance driving simulator at present, a low-cost vehicle simulation system with universal applicability was developed based on Microsoft Visual C++6.0 software platform. A data acquisition interface program based on DirectInput components and the real-time data acquisition program of driving operation was designed. Based on the dynamic model of vehicle simulation, a data output conversion model was established for the driver operation input collected in real time. For real-time vehicle dynamics simulation model, the real-time simulation control process was realized, the simulation description and decoding quality of the ground, hanging, no suspension quality coordinate system and the real-time simulation for buses with nine degrees of freedom dynamic model were established. Finally, the real-time and reliability of the simulation system were verified through the simulation test. The experiment results show that the average response time of the simulation system is 11.465ms. Emergency braking time is 4.40s with an error of 4.762%. The braking distance is 70.145m and the error is 5.959%.

Eco-Driving at Signalized Intersections: A Multiple Signal Optimization Approach

Consecutive traffic signalized intersections can increase vehicle stops, producing vehicle accelerations on arterial roads and potentially increasing vehicle fuel consumption levels. Eco-driving systems are one method to improve vehicle energy efficiency with the help of vehicle connectivity. In this paper, an eco-driving system is developed that computes a fuel-optimized vehicle trajectory while traversing more than one signalized intersection. The system is designed in a modular and scalable fashion allowing it to be implemented in large networks without significantly increasing the computational complexity. The proposed system utilizes signal phasing and timing (SPaT) data that are communicated to connected vehicles (CVs) together with real-time vehicle dynamics to compute fuel-optimum trajectories. The proposed algorithm is incorporated in the INTEGRATION microscopic traffic assignment and simulation software to conduct a comprehensive sensitivity analysis of various variables, including: system market penetration rates (MPRs), demand levels, phase splits, offsets and traffic signal spacings on the system performance. The analysis shows that at 100\% MPR, fuel consumption can be reduced by as high as 13.8\%. Moreover, higher MPRs and shorter phase lengths result in larger fuel savings. Optimum demand levels and traffic signal spacings exist that maximize the effectiveness of the algorithm. Furthermore, the study demonstrates that the algorithm works less effective when the traffic signal offset is closer to its optimal value. Finally, the study highlights the need for further work to enhance the algorithm to deal with over-saturated traffic conditions.

Real-time vehicle dynamics analysis based on analysis method with numerical dissipation

Real-time vehicle dynamics analysis based on analysis method with numerical dissipation

Toward a Comfortable Driving Experience for a Self-Driving Shuttle Bus

The convergence of mechanical, electrical, and advanced ICT technologies, driven by artificial intelligence and 5G vehicle-to-everything (5G-V2X) connectivity, will help to develop high-performance autonomous driving vehicles and services that are usable and convenient for self-driving passengers. Despite widespread research on self-driving, user acceptance remains an essential part of successful market penetration; this forms the motivation behind studies on human factors associated with autonomous shuttle services. We address this by providing a comfortable driving experience while not compromising safety. We focus on the accelerations and jerks of vehicles to reduce the risk of motion sickness and to improve the driving experience for passengers. Furthermore, this study proposes a time-optimal velocity planning method for guaranteeing comfort criteria when an explicit reference path is given. The overall controller and planning method were verified using real-time, software-in-the-loop (SIL) environments for a real-time vehicle dynamics simulation; the performance was then compared with a typical planning approach. The proposed optimized planning shows a relatively better performance and enables a comfortable passenger experience in a self-driving shuttle bus according to the recommended criteria.

Real-time vehicle dynamics analysis based on generalized-alpha scheme

Real-time vehicle dynamics analysis based on generalized-alpha scheme

Iterative Refinement of Accelerations in Real-Time Vehicle Dynamics

A number of strategies can be followed for the real-time simulation of multibody systems. The main contributing factor to computational efficiency is usually the algorithm itself (the number of equations and their structure, the number of coordinates, the time integration scheme, etc.). Additional (but equally important) aspects have to do with implementation (linear solvers, sparse matrices, parallel computing, etc.). In this paper, an iterative refinement technique is introduced into a semirecursive multibody formulation. First, the formulation is summarized and its basic features are highlighted. Then, the basic goal is to iteratively solve the fundamental system of equations to obtain the accelerations. The iterative process is applied to compute corrections of the solution in an economic way, terminating as soon as a given precision is reached. We show that, upon implementation of this method, the computation time can be reduced at a very low implementation and accuracy costs. Two vehicles are simulated to prove the numerical benefits, namely a 16-degrees-of-freedom (DOF) sedan vehicle and a 40-degrees-of-freedom semitrailer truck. In short, a simple method to iteratively solve for the accelerations of vehicle systems in an efficient way is presented.

Development and validation of an advanced motorcycle riding simulator

This paper illustrates and discusses the main features of the motorcycle riding simulator designed and built at the University of Padua over recent years. The simulator has been developed for a variety of purposes: to develop and test electronic devices aimed at improving rider safety and vehicle performance (antilock braking systems, traction control systems, etc.), to investigate different design choices and parameter effects on vehicle dynamics, to train riders, and to study their behaviours in different scenarios (normal riding, dangerous situations, etc.). Within the simulator the rider sits on a motorcycle mock-up provided with all the inputs available on a real motorcycle (throttle, clutch, brakes, etc.). These controls are used as inputs for an advanced virtual motorcycle model which computes the real-time vehicle dynamics. With the aim of giving the rider a proper motion cue, a washout filter converts the motion of the virtual motorcycle into the proper motion of a five-degrees-of-freedom motorcycle mock-up. Finally the audiovisual cues are delivered with a 180° panel and 5.1 surround sound system. To validate the simulator, a specific protocol which includes both an objective evaluation and a subjective evaluation was designed and carried out. External devices such as advanced rider assistant systems, on-bike information systems, and human–machine interfaces can be easily integrated into the simulator by means of a standard controller area network.

Virtual Test Research of Vehicle Driving Based on TESIS DYNAware

In Matlab/Simulink,basing on the real-time vehicle dynamics simulation software TESIS DYNAware,and by using dSPACE single board DS1103,hardware control signals are connected to the model vedyna_traffic;Selecting "Standard" version of vehicle dynamics model veDYNA in DYNAware,and changing this model by the veDYNA module embedded in Simulink,a virtual experiment system based on DYNAware is established.The simulation control strategy of the adaptive cruise(AC) is analysed,the control model in a ".mdl" mode is integrated into the experiment system.In the main working interface of veDYNA,data of the simulated type vehicle are input through the graphical editor of parameter file and ".m" interface of text editor,and the controllable items of simulation control and the user procedures are set respectively.By veDYNA,simulation traffic module and animation tool module playing their role together,the virtual tests of vehicle AC are carried out in the control of hardware signals,the related parameters are traced and their corresponding curves are compared with the curves which are acquired from the simulated type vehicle having AC function in quality.The results show that this method of AC virtual test research is a good research method.

Systems architecting for real-time vehicle controls evaluation

Evaluation systems for Real-Time (RT) vehicle chassis controls as test enabling subsystems are architected and designed using the process for system architecture and requirements engineering. Based on the architecture, plus a few technically ensured subsystem modules, two example test-benches are designed and used for accurate RT Hardware-In-the-Loop Simulations (HILS). The architecture has both common modules, for example RT computer, RT vehicle dynamics model and Graphic User Interface (GUI), and application-dependent modules. Architected test evaluation subsystems are flexible to apply other kinds of vehicle control systems and may be useful for accelerated vehicle development process.

Preliminary experiments in model-based thruster control for underwater vehicle positioning

This paper reports comparative experiments with two novel and one conventional thrust control algorithms for the unsteady (transient) control of thrust generated by conventional bladed-propeller marine thrusters. First, comparative experiments with three different thrust control algorithms over a wide range of unsteady operating conditions suggest that model-based control algorithms offer transient thrust-control performance superior to that of their nonmodel-based counterpart. Second, hybrid simulations combining actual real-time experimental thruster responses with simulated one-dimensional real-time vehicle dynamics suggest that model-based thrust control algorithms offer vehicle position control superior to that of its nonmodel-based counterpart.