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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.

Advanced Driver Assistance System (ADAS) has become a common standard feature assisting greater safety and fuel efficiency in the latest automobiles. Yet some ADAS systems fail to improve driving comfort for vehicle occupants who expect human-like driving. One of the more difficult situations in ADAS-assisted driving involves instances with cut-in vehicles. In vehicle control, determining the moment at which the system recognizes a cut-in vehicle as an active target is a challenging task. A well-designed comprehensive threat assessment developed for cut-in vehicle driving scenarios should eliminate abrupt and excessive deceleration of the vehicle and produce a smooth and safe driving experience. This paper proposes a novel methodology for threat assessment for driving instances involving a cut-in vehicle. The methodology takes into consideration kinematics, vehicle dynamics, vehicle stability, road condition, and driving comfort.

Recent studies evaluating motorcycle lean angle have compared theoretical lean angle equations with real-world-tested motorcycle lean angles. These studies have considered several factors affecting lean angle, including the simplified assumptions made when calculating theoretical lean angles, the speed of the motorcycle around a curve, and the geometry of the roadway/curve. This study further evaluates motorcycle lean angle as a function of speed, but primarily focuses on the effects of different travel paths selected by the rider around the same constant radius curve. The testing incorporates nine passes around the same curve traveling three different paths at three different speeds. The real-world-tested lean angles were compared to the predicted calculated lean angles for each tested travel path and speed.

In the view point of driving safety, the crosswind sensitivity of a vehicle becomes more important, as the driving speed in highway gets higher in these days. The sensitivity of a vehicle to crosswind depends on many factors, including the design of the suspension and aerodynamics of the body, etc. However, the knowledge about this phenomenon has still to be improved, in order to develop vehicle with optimum characteristics for crosswind stability. In this research, the physics behind the sensitivity of a vehicle is discussed in detail through various kinds of virtual test using computer aided engineering (CAE) simulation scheme. In the first, a reliable simulation model for vehicle, driver, wind generator and interactions among them is built. This simulation model is verified by comparison with test results of real vehicle. Then, the sensitivity analysis is carried out to find out the most influential design parameters.

The (Vehicle Inertia Parameter Evaluation Rig) VIPER II is a full vehicle mass and inertia parameter measurement machine. The VIPER II expands upon the capabilities of its predecessor and is capable of measuring vehicles with a mass of up to 45,360 kg (100,000 lb), an increase in capacity of 18,100 kg (40,000 lb). The VIPER II also exceeds its predecessor in both the length and width of vehicles it can measure. The VIPER II's maximum vehicle width is 381 cm (150 in) an increase of 76 cm (30 in) and maximum distance from the vehicle CG to the outer most axle is 648 cm (255 in) an additional 152 cm (60 in) The VIPER II is capable of performing measurements including vehicle CG height, pitch, roll, and yaw moments of inertia and the roll/yaw cross product of inertia. While being able to measure both heavier and larger vehicles, the VIPER II is designed to maintain a maximum error of 3% for all inertia measurements and 1% for CG height.

A Software-in-the-Loop (SIL) simulation is presented here wherein control algorithms for the Anti-lock Braking System (ABS) and Roll Stability Control (RSC) system were developed in Simulink. Vehicle dynamics models of a 6×4 cab-over tractor and two trailer combinations were developed in TruckSim and were used for control system design. Model validation was performed by doing various dynamic maneuvers like J-Turn, double lane change, decreasing radius curve, high dynamic steer input and constant radius test with increasing speed and comparing the vehicle responses obtained from TruckSim against field test data. A commercial ESC ECU contains two modules: Roll Stability Control (RSC) and Yaw Stability Control (YSC). In this research, only the RSC has been modeled. The ABS system was developed based on the results obtained from a HIL setup that was developed as a part of this research.

Numerous studies have validated SIMON and DyMESH with respect to vehicle dynamics and crash analysis for accident reconstruction. The impetus for this paper is to develop an accessible methodology for calculating three-dimensional stiffness coefficients for HVE-SIMON and DyMESH. This method uses acceleration-time data (crash pulse) from a vehicle crash test, data that is widely available through the National Highway Traffic Safety Administration (NHTSA). The crash pulse, along with vehicle mass and impact speed, are used to calculate the force acting on the vehicle and the associated vehicle deflection time history. A technique for determining the area-deflection function is created from a computer model of the vehicle, HVE-SIMON, and basic photo-editing software. The calculated force divided by the associated area function (F/A) is plotted versus deflection and a third-order polynomial is then fit to the curve.

This paper presents a feedback linearization control technique as applied to a Roll Simulator. The purpose of the Roll Simulator is to reproduce in-field rollovers of ROVs and study occupant kinematics in a laboratory setting. For a system with known parameters, non-linear dynamics and trajectories, the feedback linearization algorithm cancels out the non-linearities such that the closed-loop dynamics behave in a linear fashion. The control inputs are computed values that are needed to attain certain desired motions. The computed values are a form of inverse dynamics or feed-forward calculation. With increasing system eigenvalue, the controller exhibits greater response time. This, however, puts a greater demand on the translational actuator. The controller also demonstrates that it is able to compensate for and reject a disturbance in force level.

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.

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 presents the results of an in-depth study of the measurement of occupant kinematic response on the S-E-A Roll Simulator. This roll simulator was built to provide an accurate and repeatable test procedure for the evaluation of occupant protection and restraint systems during roll events within a variety of occupant compartments. In the present work this roll simulator was utilized for minimum-energy, or threshold type, rollover events of recreational off-highway vehicles (ROVs). Input profiles for these tests were obtained through a separate study involving autonomous full vehicle tests [1]. During simulated roll events anthropomorphic test device (ATD) responses were measured using on-board high speed video, an optical three-dimensional motion capture system (OCMS) and an array of string potentiometers.

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.

Vehicle dynamics models employed in heavy truck simulation often treat the semitrailer as a torsionally rigid member, assuming zero deflection along its longitudinal axis as a moment is applied to its frame. Experimental testing, however, reveals that semitrailers do twist, sometimes enough to precipitate rollover when a rigid trailer may have remained upright. Improving the model by incorporating realistic trailer roll stiffness values can improve assessment of heavy truck dynamics, as well as an increased understanding of the effectiveness of stability control systems in limit handling maneuvers. Torsional stiffness measurements were conducted by the National Highway Traffic Safety Administration (NHTSA) for eight semitrailers of different types, including different length box vans, traditional and spread axle flat beds, and a tanker.

This research focuses on the development and performance of analytical models to simulate a tractor-semitrailer in straight-ahead braking. The simulations were modified and tuned to simulate full-treadle braking with all brakes functioning correctly, as well as the behavior of the tractor-semitrailer rig under full braking with selected brakes disabled. The models were constructed in TruckSim and based on a tractor-semitrailer used in dry braking performance testing. The full-scale vehicle braking research was designed to define limits for engineering estimates on stopping distance when Class 8 air-braked vehicles experience partial degradation of the foundation brake system. In the full scale testing, stops were conducted from 30 mph and 60 mph, with the combination loaded to 80,000 lbs (gross combined weight or GCW), half payload, and with the tractor-semitrailer unladen (lightly loaded vehicle weight, or LLVW).

Investigators of vehicular incidents often seek to recover data stored within on-board computer systems. For commercial vehicles, the primary source for this information is the engine control module (ECM). The data stored in these modules, not unlike passenger vehicles, varies widely among manufacturers, as do the hardware and software required to recover such data. Further, the options, and associated risks, involved with attempting to recover this data has a similarly wide variance relative to the engine manufacturer, incident related circumstances, and the tools currently available to perform such downloads. There are two primary paths available to obtain this data: (1) via the vehicle data bus (e.g. SAE J1939 or J1708 ) or (2) direct-to-module (DTM) connection. When using the DTM method, power is applied to an ECM, and the module measures the various engine control and monitoring components for validity.

Torsional stiffness properties were developed for both a 53-foot box trailer and a 28-foot flatbed control trailer based on experimental measurements. In order to study the effect of torsional stiffness on the dynamics of a heavy truck vehicle dynamics computer model, static maneuvers were conducted comparing different torsional stiffness values to the original rigid vehicle model. Stiffness properties were first developed for a truck tractor model. It was found that the incorporation of a torsional stiffness model had only a minor effect on the overall tractor response for steady-state maneuvers up to 0.4 g lateral acceleration. The effect of torsional stiffness was also studied for the trailer portion of the existing model.

In 2007, a software model of a Roll Stability Control (RSC) system was developed based on test data for a Volvo tractor at NHTSA's Vehicle Research and Test Center (VRTC). This model was designed to simulate the RSC performance of a commercially available Electronic Stability Control (ESC) system. The RSC model was developed in Simulink and integrated with the available braking model (TruckSim) for the truck. The Simulink models were run in parallel with the vehicle dynamics model of a truck in TruckSim. The complete vehicle model including the RSC system model is used to simulate the behavior of the actual truck and determine the capability of the RSC system in preventing rollovers under different conditions. Several simulations were performed to study the behavior of the model developed and to compare its performance with that of an actual test vehicle equipped with RSC.

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 is a printed listing of public domain vehicle center-of-gravity (CG) location measurements conducted on behalf of the National Highway Traffic Safety Administration (NHTSA). This paper is an extension of the 1999 SAE paper titled “Measured Vehicle Inertia Parameters - NHTSA's Data Through November 1998” ( 1 ). The previous paper contained data for 496 vehicles. This paper includes data for 528 additional vehicles tested as part of NHTSA's New Car Assessment Program (NCAP) for year 2001 through year 2008 ( 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 ). The previous data included center-of-gravity location and mass moments-of-inertia for nearly all of the entries. The NCAP involves only the CG location measurements; so the vehicles listed in this paper do not have inertia data. This paper provides a brief discussion of the entries provided in the tabular listings as well as the accuracy of CG height measurements.

This research was performed using a designed experiment to evaluate the loss of dry surface braking performance and stability that could be associated with the disablement of specific brake positions on a tractor-semitrailer. The experiment was intended to supplement and update previous research by Heusser, Radlinski, Flick, and others. It also sought to establish reasonable limits for engineering estimates on stopping performance degradation attributable to partial or complete brake failure of individual S-cam air brakes on a class 8 truck. Stopping tests were conducted from 30 mph and 60 mph, with the combination loaded to GCW (80,000 lb.), half-payload, and with the flatbed semitrailer unladen. Both tractor and semitrailer were equipped with antilock brakes. Along with stopping distance, brake pressures, longitudinal acceleration, road wheel speed, and steering wheel position and effort were also recorded.