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Modern passenger cars are being equipped with advanced driver assistance systems such as lane departure warning, collision avoidance systems, adaptive cruise control, etc. Testing for operation and effectiveness of these warning systems involves interaction between vehicles. While dealing with multiple moving vehicles, obtaining discriminatory results is difficult due to the difficulty in minimizing variations in vehicle separation and other parameters. This paper describes test strategies involving an automated test driver interacting with another moving vehicle. The autonomous vehicle controls its state (including position and speed) with respect to the target vehicle. Choreographed maneuvers such as chasing and overtaking can be performed with high accuracy and repeatability that even professional drivers have difficulty achieving. The system is also demonstrated to be usable in crash testing.

Steering activity in response to deviations from the intended straight-ahead vehicle path is an important factor of vehicle-driver on-center performance. Traditionally, setting the parameters of vehicle models for stability analysis does not involve vehicle properties that make the vehicle deviate from its intended path with no steering input. However, for closed loop simulations where driver steering activity is considered a fundamental human performance measure, the ability of the vehicle model to faithfully generate path deviations in response to external forces is required for steering performance measures fidelity. Path deviations cause the driver to make small steering angle corrections to keep the vehicle on its intended straight path. It is in fact a natural driving load that should be included in every closed loop simulation before considering any study involving driving loads and driver distractions.

This paper describes an apparatus, called the Inertial Parameter Measurement Device (IPMD), which recently has been developed by the National Highway Traffic Safety Administration at its Vehicle Research and Test Center. The IPMD measures the center of gravity height and the pitch, roll, and yaw moments of inertia of a vehicle. The first section of this paper describes the features, capabilities, limitations, and design of the IFMD. This is followed by a presentation of the vehicle parameters that have been measured by it, to date. The final section of the paper presents several commonly used, and one proposed, rules of thumb for estimating inertial parameters. Data from measurements made by the IPMD are used to show the validity of these rules. Curves obtained by fitting the measured data are also shown for the moments of inertia as functions of the vehicle weight.

This paper discusses the development of the 1997 Jeep Cherokee model for the National Advanced Driving Simulator's planned vehicle dynamics software, NADSdyna. Recursive rigid body formalism called the Real Time Recursive Dynamics (RTRD) developed by the University of Iowa is used to model the front and rear suspension mechanisms. To complement vehicle dynamics for simulator applications, subsystems that include tires, aerodynamics, powertrain, brake, and steering are added to the rigid body dynamics model. These models provide high fidelity driving realism to simulate severe handling maneuvers in real time. The soundness of the model does not only depend on the mathematics of the model, but also on the validity of the parameters. Therefore, this paper discusses thoroughly the methodology of parameters estimation. A generic model of cruise control is included.

The paper discusses the development of a vehicle dynamics model and model validation of the 2003 Ford Expedition in CarSim. The accuracy of results obtained from simulations depends on the realism of the model which in turn depends on the measured data used to define the model parameters. The paper describes the tests used to measure the vehicle data and also gives a detailed account of the methodology used to determine parameters for the CarSim Ford Expedition model. The vehicle model was validated by comparing simulation results with experimental testing. Bounce and Roll tests in CarSim were used to validate the suspension and steering kinematics and compliances. Field test data of the Sine with Dwell maneuver was used for the vehicle model validation. The paper also discusses the development of a functional electronic stability control system and its effect on vehicle handling response in the Sine with Dwell maneuver.

The paper discusses the development of a model of the 2003 Ford Expedition using ADAMS View and its validation with experimental data. The front and rear suspensions are independent double A-arm type suspensions modeled using rigid links and ideal joints. The suspension springs and shock absorbers are modeled as force elements. The plots comparing the experimental tests and the simulation results are shown in this paper. Quasi-static roll and bounce tests are used to validate the suspension characteristics of the model while the Sine with Dwell and Slowly Increasing Steer maneuvers are used to validate the vehicle handling and tire-road interaction characteristics of the model. This paper also details the incorporation of an ESC model, originally developed by Kinjawadekar et al. [2] for CarSim, with the ADAMS model. The ESC is modeled in Simulink and co-simulated with the ADAMS vehicle model. Plots validating the ESC model with experimental data are also included.

This research focused on developing a methodology for a vehicle dynamics model of a passenger vehicle outfitted with an aftermarket Automated Driving System software package using only literature and track based results. This package consisted of Autoware.AI (Autoware ®) operating on Robot Operating System 1 (ROS™) with C++ and Python ®. Initial focus was understanding the basics of ROS and how to implement test scenarios in Python to characterize the control systems and dynamics of the vehicle. As understanding of the system continued to develop, test scenarios were adapted to better fit system characterization goals with identification of system configuration limits. Trends from on-track testing were identified and paired with first-order linear systems to simulate physical vehicle responses to given command inputs. Sub-models were developed and simulated in MATLAB ® with command inputs from on-track testing.

Typical factors that contribute to the coast down characteristics of a vehicle include aerodynamic drag, gravitational forces due to slope, pumping losses within the engine, frictional losses throughout the powertrain, and tire rolling resistance. When summed together, these reactions yield predictable deceleration values that can be related to vehicle speeds. This paper focuses on vehicle decelerations while coasting with a typical medium-sized SUV. Drag factors can be classified into two categories: (1) those that are caused by environmental factors (wind and slope) and (2) those that are caused by the vehicle (powertrain losses, rolling resistance, and drag into stationary air). The purpose of this paper is to provide data that will help engineers understand and model vehicle response after loss of engine power.

A two-degree-of-freedom Roll Simulator has been developed to study the occupant kinematics of Recreational Off-Highway Vehicles (ROVs). To validate the roll simulator, test data was collected on a population of ROVs on the market today. J-turn maneuvers were performed to find the minimum energy limits required to tip up the vehicles. Two sets of tests were performed: for the first set, 10 vehicles were tested, where the motion was limited by safety outriggers to 10-15 degrees of roll; and for the second set, three of these vehicles were re-tested with outriggers removed and the vehicle motion allowed to reach 90 degrees of roll. These quarter-turn rollover tests were performed autonomously using an Automatic Steering Controller (ASC) and a Brake and Throttle Robot (BTR). Lateral and longitudinal accelerations as well as roll rate and roll angle were recorded for all tests.

The tractor trailer models discussed in this paper were for a real-time hardware-in-the-loop (HIL) simulation to test heavy truck electronic stability control (ESC) systems [1]. The accuracy of the simulation results relies on the fidelity and accuracy of the vehicle parameters used. However in this case where hardware components are part of the simulation, their accuracy also affects the proper working of the simulation and ESC unit. Hence both the software and hardware components have to be validated. The validation process discussed in this paper is divided into two sections. The first section deals with the validation of the TruckSim vehicle model, where experimental data is compared with simulation results from TruckSim. Once the vehicle models are validated, they are incorporated in the HIL simulation and the second section discusses the validation of the whole HIL system with ESC.

Validation was performed on an existing heavy truck vehicle dynamics computer model with roll stability control (RSC). The first stage in this validation was to compare the response of the simulated tractor to that of the experimental tractor. By looking at the steady-state gains of the tractor, adjustments were made to the model to more closely match the experimental results. These adjustments included suspension and steering compliances, as well as auxiliary roll moment modifications. Once the validation of the truck tractor was completed for the current configuration, the existing 53-foot box trailer model was added to the vehicle model. The next stage in experimental validation for the current tractor-trailer model was to incorporate suspension compliances and modify the auxiliary roll stiffness to more closely model the experimental response of the vehicle. The final validation stage was to implement some minor modifications to the existing RSC model.

This paper presents an evaluation of a vehicle dynamics model intended to be used for the National Advanced Driving Simulator (NADS). Dynamic validation for high performance simulation is not merely a comparison between experimental and simulation plots. It involves strong insight of vehicle's subsystems mechanics, limitations of the mathematical formulations, and experimental predictions. Lateral, longitudinal, and ride dynamics are evaluated using field test data, and analytical diagnostics. The evaluation includes linear and non-linear range of vehicle dynamics response.

This paper documents the vehicle response of a tractor-semitrailer following a sudden air loss (Blowout) in a steer axle tire while traveling at highway speeds. The study seeks to compare full-scale test data to predicted response from detailed heavy truck computer vehicle dynamics simulation models. Full-scale testing of a tractor-semitrailer experiencing a sudden failure of a steer axle tire was conducted. Vehicle handling parameters were recorded by on-board computers leading up to and immediately following the sudden air loss. Inertial parameters (roll, yaw, pitch, and accelerations) were measured and recorded for the tractor and semitrailer, along with lateral and longitudinal speeds. Steering wheel angle was also recorded. These data are presented and also compared to the results of computer simulation models. The first simulation model, SImulation MOdel Non-linear (SIMON), is a vehicle dynamic simulation model within the Human Vehicle Environment (HVE) software environment.

This paper examines variability of two static rollover metrics, Static Stability Factor (SSF) and Tilt Table Ratio (TTR), due to vehicle loading and vehicle-to-vehicle variation. Variability due to loading was determined by measuring SSF and TTR for 14 vehicles/configurations at multiple loadings. Up to five loadings were used per vehicle/configuration tested. Vehicle-to-vehicle variability was studied by measuring SSF and TTR for ten unmodified vehicles of each of four make/models. Five baseline vehicles, as similar as was feasible, were tested. The other five test vehicles spanned the range of submodels and options available. In general, both SSF and TTR decreased as occupants were added to a vehicle. The change in SSF and TTR per occupant was fairly consistent, with changes in TTR being more consistent. Placing ballast on the floor of the cargo compartment had a mixed effect on SSF, raising it for some vehicles and lowering it for others.

This paper discusses the importance of having an adequate model for the dynamic response characteristics of tire lateral force to steering inputs. Computer simulation and comparison with experimental results are used to show the importance of including appropriate tire dynamics in simulation tire models to produce accurate predictions of vehicle dynamics. Improvements made to the tire dynamics model of an existing vehicle stability and control simulation, the Vehicle Dynamics Analysis, Non-Linear (VDANL) simulation, are presented. Specifically, the improvements include changing the simulation's tire dynamics from first-order system tire side force lag dynamics to second-order system tire slip angle dynamics. A second-order system representation is necessary to model underdamped characteristics of tires at high speeds. Lagging slip angle (an input to the tire model) causes all slip angle dependent tire force and moment outputs to be lagged.

The intent of this research is to understand the effects worn dampers have on vehicle stability and safety through dynamic model simulation. Dampers, an integral component of a vehicle's suspension system, play an important role in isolating road disturbances from the driver by controlling the motions of the sprung and unsprung masses. This paper will show that a decrease in damping leads to excessive body motions and a potentially unstable vehicle. The concept of poor damping affecting vehicle stability is well established through linear models. The next step is to extend this concept for non-linear models. This is accomplished through creating a vehicle simulation model and executing several driving maneuvers with various damper characteristics. The damper models used in this study are based on splines representing peak force versus velocity relationships.

This paper discusses the improvement of a heavy truck anti-lock brake system (ABS) model currently used by the National Highway Traffic Safety Administration (NHTSA) in conjunction with multibody vehicle dynamics software. Accurate modeling of this complex system is paramount in predicting real-world dynamics, and significant improvements in model accuracy are now possible due to recent access to ABS system data during on-track experimental testing. This paper focuses on improving an existing ABS model to accurately simulate braking under limit braking maneuvers on high and low-coefficient surfaces. To accomplish this, an ABS controller model with slip ratio and wheel acceleration thresholds was developed to handle these scenarios. The model was verified through testing of a Class VIII 6×4 straight truck. The Simulink brake system and ABS model both run simultaneously with TruckSim, with the initialization and results being acquired through Matlab.

This paper describes the design of a vehicle inertia measurement facility (VIMF): a facility used to measure vehicle center of gravity position; vehicle roll, pitch, and yaw mass moments of inertia; and vehicle roll/yaw mass product of inertia. The rationale for general design decisions and the methods used to arrive at the decisions are discussed. The design is inspired by the desire to have minimal measurement error and short test time. The design was guided by analytical error analyses of the contributions of individual system errors to the overall measurement error. A National Highway Traffic Safety Administration (NHTSA) database of center of gravity position and mass moment of inertia data for over 300 vehicles was used in conjunction with the error analyses to design various VIMF components, such as the roll and yaw spring sizes.

This paper describes the theory and design of an apparatus, the Suspension Parameter Measurement Device (SPMD), which has been developed to measure the displacements and forces which occur at the road wheels of a vehicle as the body moves, or as lateral and/or longitudinal forces are applied at the tire/road interface. Wheel movements resulting from the bounce, pitch, or roll motions of the vehicle body in the absence of lateral and longitudinal forces at the tire/road interface are the kinematic characteristics of the suspension. Wheel displacements caused by the application of forces in the plane of the road are defined as the compliance characteristics, while those resulting from motions of the steering wheel are the steering characteristics. The purpose of the SPMD is to measure all of these characteristics, thereby providing data for use in the simulation of the performance of cars and light trucks.

This paper describes the mechanical design of a Suspension Parameter Identification Device and Evaluation Rig (SPIDER) for wheeled military vehicles. This is a facility used to measure quasi-static suspension and steering system properties as well as tire vertical static stiffness. The machine operates by holding the vehicle body nominally fixed while hydraulic cylinders move an “axle frame” in bounce or roll under each axle being tested. The axle frame holds wheel pads (representing the ground plane) for each wheel. Specific design considerations are presented on the wheel pads and the measurement system used to measure wheel center motion. The constraints on the axle frames are in the form of a simple mechanism that allows roll and bounce motion while constraining all other motions. An overview of the design is presented along with typical results.