Search Results

Sudden tire deflation, or blow-out, is sometimes cited as the cause of a crash. Safety researchers have previously attempted to study the loss of vehicle control resulting from a blow-out with some success using computer simulation. However, the simplified models used in these studies did little to expose the true transient nature of the handling problem created by a blown tire. New developments in vehicle simulation technology have made possible the detailed analysis of transient vehicle behavior during and after a blow-out. This paper presents the results of an experimental blow-out study with a comparison to computer simulations. In the experiments, a vehicle was driven under steady state conditions and a blow-out was induced at the right rear tire. Various driver steering and braking inputs were attempted, and the vehicle response was recorded. These events were then simulated using EDVSM. A comparison between experimental and simulated results is presented.

SIMON is a new vehicle dynamic simulation model. Applications for SIMON include single- and multi-unit vehicle handling simulation in severe limit maneuvers (including rollovers) and 3-dimensional environments. Applications also include vehicle-to-vehicle and vehicle-to-barrier collisions. This paper provides the technical background for the SIMON engineering model. The 3-dimensional equations of motion used by the model are presented and explained in detail. The calculations for suspension, tire, collision, aerodynamic and inter-vehicle connection forces and moments are also developed. The integration of features available in the HVE Simulation Environment, such as DyMESH, the Driver Model, Brake Designer and Steer Degree of Freedom, is also explained. Finally, assumptions and limitations of the model are presented.

Most vehicles built today are fitted with anti-lock braking systems (ABS). Accurate simulation modeling of these vehicles during braking as well as combined braking and steering maneuvers thus requires the effects of the ABS to be included. Simplified, lump parameter models are not adequate for detailed, 3-dimensional vehicle simulations that include wheel spin dynamics. This is especially true for simulating complex crash avoidance maneuvers. This paper describes a new ABS model included in the HVE simulation environment. It is a general purpose model and is available for use by any HVE-compatible vehicle simulation model. The basic operational and control characteristics for a typical ABS system are first reviewed. Then, the specific ABS model and its options as implemented in the HVE simulation environment and employed by the SIMON vehicle simulation model are described. To validate the model, pressure cycles produced by the model are compared with stated engineering requirements.

This paper presents an example application for vehicle dynamics simulation software. This example investigates the validity of the vehicle motion presented in the famous car chase scene from the 1968 movie Bullitt. In this car chase, a 1968 Ford Mustang, driven by Det. Frank Bullitt of the San Francisco Police Department, is chasing a criminal driving a 1968 Dodge Charger through the streets of the Russian Hill district of San Francisco. The purpose of the simulation was to reconstruct the chase scene to determine the level of realism in the movie, in terms of conformance to Newton’s Laws of motion. To produce the simulation, several city blocks of the pertinent area of the city were surveyed and exemplar vehicles were measured and inspected. Three-dimensional computer models of the scene and vehicles were built. The movie footage was analyzed to determine vehicle speeds and driver inputs. The event was then simulated using three-dimensional vehicle dynamics simulation software.

A substantial programming effort is required to develop a human or vehicle dynamics simulator. More than half of this effort is spent designing and programming the user interface (the means by which the user supplies program input and views program output). This paper describes a pre-programmed, 3-dimensional (3-D), input/output window-type interface which may be used by developers of human and vehicle dynamics programs. By using this interface, the task of input/output programming is reduced by approximately 50 percent, while simultaneously providing a more robust interface. This paper provides a conceptual overview of the interface, as well as specific details for writing human and vehicle dynamics programs which are compatible with the interface. Structures are provided for the human, vehicle and environment models. Structures are also provided for events, interface variables, and the output data stream.

Developers of human dynamics simulation software inherently use a mathematical/physical model to represent the human. This paper describes a pre-programmed, object-oriented human model for use in human dynamics simulations. This human model is included as part of an integrated simulation environment, called HVE (Human-Vehicle-Environment), described in previous research. The current paper first provides a general overview of the HVE user and development environments, and then provides detailed specifications for the HVE Human Model. These specifications include definitions for model parameters (supported human types and human properties, such as dimensions, inertias, joints and injury tolerances). The paper also provides detailed specifications for the HVE time-dependent human output group parameters (kinematics, joints, contacts, belts and airbags).

Developers of vehicle dynamics simulation software inherently use a mathematical/physical model to represent the vehicle. This paper describes a pre-programmed, object-oriented vehicle model for use in vehicle dynamics simulations. This vehicle model is included as part of an integrated simulation environment, called HVE (Human-Vehicle-Environment), described in previous research [1,2] *. The current paper first provides a general overview of the HVE user and development environments, and then provides detailed specifications for the HVE Vehicle Model. These specifications include definitions for model parameters (supported vehicle types; vehicle properties, such as dimensions, inertias, suspensions; tire properties, such as dimensions and inertias, mu vs slip, cornering and camber stiffnesses; driver control systems, such as engine, transmission/differential, brakes and steering; restraint systems, such as belts and airbags).

This paper describes the use of 3-D technologies for reconstructing and simulating motor vehicle accidents involving humans (occupants and pedestrians) and vehicles (passenger cars, pickups, vans, multi-purpose vehicles, on-highway trucks and vehicle-trailers). All examples involve three-dimensional environments, including road crowns, hills, curbs and embankments - any geometrical feature resulting in three-dimensional motion. Various reconstruction and simulation models are illustrated. The features and limitations of each model are addressed. Issues involving data requirements, preparation of 3-D models and presentation techniques (numeric, graphic and video animation) are also explored.

EDVSM is a 3-dimensional vehicle simulator developed for the HVE simulation environment. The EDVSM vehicle model was based on the original HVOSM model, developed at Calspan for the Federal Highway Administration. This paper describes the vehicle and tire models used by EDVSM. The basic model is unchanged from the original HVOSM model, however, tire-road modeling has been substantially improved by the model's integration into the HVE environment. This paper provides the details of the integration procedure. The paper also includes a validation study, comparing results between EDVSM, HVOSM and real-world handling studies. Comparison reveals the results are substantially similar. Finally, applications and limitations of the model are addressed.

The EDSMAC personal computer program for use by accident investigators is described. The input data requirements are reviewed. The general calculation procedures are discussed and the specific procedures for computing delta-V are explained in detail. The method, based on equalizing the force between the vehicles at all times during the impact phase, is seen to be simple in concept but extremely complex in practice. The numerical and graphical output and warning messages are reviewed. Applications of the program are illustrated. The major benefit of EDSMAC is the ability, using graphics, to provide an analytical method illustrating how an accident may, or may not, have occurred.

A new three-dimensional collision simulation algorithm, called DyMESH (Dynamic MEchanical SHell) was recently introduced.[1]* This paper presents a validation of DyMESH for vehicle vs. barrier collisions. The derivation of the three-dimensional force vs. crush relationship was described previously.[1] Here the application of three-dimensional force vs. crush curves using the outlined methodology is shown to be effective. Nonlinear force versus crush relationships are introduced for use in DyMESH. Included are numerous DyMESH collision simulations of several types of vehicles (e.g., light and heavy passenger car and sport utility) compared directly with experimental collision test results from various types of barrier tests (e.g., full frontal, angled frontal, and offset frontal). The focus here is not on the vehicle’s change in velocity, but on the acceleration vs. time history.

A new, systematic approach to the design-evaluation-test product development cycle is described wherein the vehicle design and simulation environments are integrated. This methodology is applied to brake mechanical design and material selection. Time-domain computations within a vehicle dynamic simulation environment account for brake and lining geometry and material properties, actuator properties, and temperature effects. Two examples illustrate the utility of this approach by examining: the effect of varying hydraulic cylinder diameter on passing federally mandated stopping distance tests, and the effect of S-cam actuator adjustment on the performance of air brakes on a tractor-trailer. The simulation results are compared with experimental vehicle stopping distance tests to assess the validity of the simulations.

Traditional vehicle simulations use two methods of modeling driver inputs, such as steering and braking. These methods are broadly categorized as “Open Loop” and “Closed Loop”. Open loop methods are most common and use tables of driver inputs vs time. Closed loop methods employ a mathematical model of the driving task and some method of defining an attempted path for the vehicle to follow. Closed loop methods have a significant advantage over open loop methods in that they do not require a trial-and-error approach normally required by open loop methods to achieve the desired vehicle path. As a result, closed loop methods may result in significant time savings and associated user productivity. Historically, however, closed loop methods have had two drawbacks: First, they require user inputs that are non-intuitive and difficult to determine. Second, closed loop methods often have stability problems.

Motor vehicle safety researchers have used the Phase 4 vehicle simulation model for several years. Because of its popularity and ability to simulate the 3-dimensional dynamics of commercial vehicles (large trucks and truck tractors towing up to three trailers), the Phase 4 model was ported to the HVE simulation platform. The resulting model is called EDVDS (Engineering Dynamics Vehicle Dynamics Simulator). This paper describes the procedures used in porting Phase 4 to the HVE platform. As a result of several assumptions made during the development of Phase 4, the port to EDVDS required substantial changes. The most significant modeling difference is the removal of the small angle assumption, allowing researchers to study complete vehicle rollover. Also significant is EDVDS’s use of HVE’s Get Surface Info () function, allowing the vehicles’ tires to travel over any 3-D terrain of arbitrary complexity. These and other changes in the model are described in the paper.

SIMON is a new 3-dimensional vehicle dynamic simulation model. The capabilities of the model include non-linear handling maneuvers and collision simulation for one or more vehicles. As a new model, SIMON must be validated by comparison against actual handling and collision experiments. This paper provided that comparison. Included in the validation were lane-change maneuvers, alternate ramp traversals, limit maneuvers with combined braking and steering, vehicle-to-vehicle crash tests and articulated vehicle handling tests. Comparison against other models were included. No metric was provided for handling test comparisons. However, statistical analysis of the collision test results revealed the average path range error was 6.2 to 14.8 percent. The average heading error was -4.7 to 0.7 percent. Delta-V error was -1.6 to 7.5 percent. VEHICLE SIMULATION has many uses in the vehicle design and safety industries.

Vehicle crashes often involve rollover. A vehicle rollover is a complex, 3-dimensional event that is quite difficult to model successfully. As a result, crash investigators often make simplifying assumptions that compromise the quality of the information learned from the analysis. Advances in vehicle simulation modeling have greatly reduced the amount of work required to perform rollover simulations. Rollover simulation holds promise as a tool to learn more about crashes involving rollover. This paper describes how the EDVSM simulation model calculates 3-dimensional forces and moments on the sprung mass (i.e., body exterior) and how these forces and moments are integrated into the equations of motion. The paper also provides some examples of the use of rollover simulation. Finally, the paper addresses the practical and theoretical limitations of rollover simulation as a tool for routine reconstruction of on-road and off-road crashes. VEHICLE ROLLOVER is a significant safety problem.

The EDSMAC simulation model has been in widespread use by vehicle safety researchers since its introduction in 1985. Several papers have been published that describe the model and provide validations of its use. In 1997, the collision and vehicle dynamics models were extended significantly. The main control logic was also extended and generalized. The resulting model was named EDSMAC4. This paper describes the EDSMAC4 model with particular attention to the extensions to the original algorithms. The paper also provides a validation of the new model by direct comparison to staged collision experiments and the results from the previous EDSMAC model.

The two procedures, DAMAGE and OBLIQUE IMPACT, which are used by EDCRASH for computing delta-V, are described in detail. Enhancements in EDCRASH Version 4 which improve the DAMAGE method of computing delta-V are also described. The advantages and disadvantages of each method are explored, and the numerical and graphical output and use of warning messages are reviewed. In general, it was found the two methods are complimentary: The DAMAGE procedure is best-suited for the conditions in which the OBLIQUE IMPACT procedure is least-suited, and vice-versa.

When an automobile is driven on wet roads, its tires must remove water from between the tread and road surfaces. It is well known that the ability of a tire to remove water depends heavily on tread depth, water depth and speed, as well as other factors, such as tire load, air pressure and tread design. It is less well known that tire tread depth combined with placement can have an adverse effect on vehicle handling on wet roads. This paper investigates passenger car handling on wet roads. Flat bed tire testing, three-dimensional computer simulation and skid pad experimental testing are used to determine how handling is affected by tire tread depth and front/rear position of low-tread-depth tires on the vehicle. Some skid pad test results are given, along with corresponding simulations. A literature review also is presented. Significant changes in tire-road longitudinal and lateral friction are shown to occur as speed, tread depth and water depth vary, even before hydroplaning occurs.