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Modeling retroreflective material in a three-dimensional computer modeling and Physically Based Rendering (PBR) engine is extremely difficult without fully understanding the physics behind how the light rays interact and behave with the retroreflective materials. Without the proper engineering and physics understanding, incorrect, inaccurate and unfair animations can be created that attempt to show the visibility of retroreflective materials. In this paper we will discuss the engineering and physics of retroreflective materials and how light interacts with these materials. We will also describe how to incorporate the engineering and science of retroreflective materials into a PBR engine to create a fair and accurate light simulation displaying the visibility of the retroreflective materials.

Retroreflection occurs when a light ray incident on a surface is reflected back towards the light source. The performance of a retroreflective material is of interest to accident reconstructionist, human factors professionals, lighting professionals, and roadway design professionals. The retroreflective effect of a material can be defined by the coefficient of retroreflection, which is a function of the light’s entrance angle and the viewer’s observation angle. The coefficient of retroreflection of a material is typically measured in a laboratory environment or in the field with a retroreflectometer. Often the material in question cannot be taken to a laboratory for testing and commercially available portable retroreflectometers are limited to entrance angles of 45 degrees or less and may be cost prohibitive in some cases.

Mapping a light source, any light source, is of broad interest to accident reconstructionists, human factors professionals and lighting experts. Such mappings are useful for a variety of purposes, including determining the effectiveness and appropriateness of lighting installations, and performing visibility analyses for accident case studies. Currently, mapping a light source can be achieved with several different methods. One such method is to use an illuminance meter and physically measure each point of interest on the roadway. Another method utilizes a goniometer to measure the luminous intensity distribution, this is a near-field measurement. Both methods require significant time and the goniometric method requires extensive equipment in a lab. A third method measures illumination distribution in the far-field using a colorimeter or photometer.

Vision is the primary sense used to navigate through this world when driving, walking, biking, or performing most tasks. and thus visibility is a critical concern in the design of roadways, pathways, vehicles, buildings, etc. and the investigation of accidents. In order to assess visibility, the accident scene can be documented under similar conditions. Geometric and photometric measurements can be taken for later analysis. Calibrated photographs or video of a recreated scene can be captured to illustrate the visibility at a later time. This process can often require significant coordination of the physical features at the scene. It can be difficult to precisely control the motion and timing of moving features such as pedestrians and vehicles. The result is fixed in that you capture specific scenarios with specific conditions with the selected field of view and perspective of the cameras used.

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.

Bobtail testing data published in the literature are limited and the difference in deceleration of a bobtail configuration compared to a tractor-trailer has not been fully evaluated in the past. The authors seek to increment and update previous research on the topic. This paper presents detailed braking characteristic information obtained from full scale instrumented testing of a bobtail vehicle at various speeds. Brake timing is analyzed for the tested condition to determine the overall braking characteristics. The findings of this study are compared to 1) other testing performed with the same tractor configured with a trailer at different loading conditions and 2) to results published in literature for both bobtail vehicles and other loading conditions for both 6×4 and 4×2 tractor axle configurations.

Accident reconstruction specialists have long relied on post-crash deformation and energy equivalence calculations to determine impact severity and the experienced change in velocity during the impact event. In order to utilize post-crash deformation, information must be known about the vehicle's structure and its ability to absorb crash energy. The Federal Motor Vehicle Safety Standards (FMVSS), the New Car Assessment Program (NCAP), and the Insurance Institute of Highway Safety (IIHS), have created databases with crash testing data for a wide range of vehicles. These crash tests allow reconstruction specialists to determine a specific vehicle's ability to absorb energy as well as to generalize the energy absorption characteristics across vehicle classes. These methods are very well publicized.

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 and analyzes braking test data and braking marks for a sport, sport-touring, and cruiser type motorcycle. The best-effort braking tests were performed using three motorcycles, three riders, and three initial speeds. All tests were performed on dry asphalt, with the exception of one set of runs for a sport touring motorcycle on wet asphalt. Three braking strategies were used; front-brake-only, rear-brake-only, and front-and-rear brakes used together. From these data, engineers can evaluate the following effects on braking performance: rider, speed, pavement condition, braking strategy, and motorcycle type. This paper should also serve to assist the vehicle accident reconstructionist in complementing the existing data on motorcycle braking performance.

The ability of a simulation model to accurately predict vehicle response is investigated in this paper. This study seeks to compare full-scale tractor-semitrailer straight-line braking test data to predicted response from a detailed heavy truck computer vehicle dynamics simulation model. The model, Simulation MOdel Non-linear (SIMON), is a vehicle dynamic simulation model within the Human Vehicle Environment (HVE) software environment. This computer program includes a vehicle dynamic model capable of simulating vehicle motion in 3-dimensional environments and includes Brake Designer and ABS Simulation Models. The results of several days of full scale instrumented testing of a tractor-semitrailer performed at the Transportation Research Center, in East Liberty, Ohio are presented.

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.

The timing and associated levels of braking between initial brake pedal application and actual maximum braking at the wheels for a tractor-semitrailer are important parameters in understanding vehicle performance and response. This paper presents detailed brake timing information obtained from full scale instrumented testing of a tractor-semitrailer under various conditions of load and speed. Brake timing at steer, drive and semitrailer brake positions is analyzed for each of the tested conditions. The study further seeks to compare the full scale test data to predicted response from detailed heavy truck computer vehicle dynamics simulation models available in commercial software packages in order to validate the model's brake timing parameters. The brake timing data was collected during several days of full scale instrumented testing of a tractor-semitrailer performed at the Transportation Research Center, in East Liberty, Ohio.

Engine control units (ECUs) on heavy trucks have been capable of storing “last stop” or “hard stop” data for some years. These data provide useful information to accident reconstruction personnel. In past studies, these data have been analyzed and compared to higher-resolution on-vehicle data for several heavy trucks and several makes of passenger cars. Previous published studies have been quite helpful in understanding the limitations and/or anomalies associated with these data. This study was designed and executed to add to the technical understanding of heavy truck event data recorders (EDR), specifically data associated with a modern Cummins power plant ECU. Emergency “full-treadle” stops were performed at many combinations of load-speed-surface coefficient conditions. In addition, brake-in-curve tests were performed on wet Jennite for various conditions of disablement of the braking system.

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.

This paper is a follow up to a study published in 2005 1 on the same topic and presents a study that was conducted to compare vehicle speed change and acceleration data from full-scale testing to results generated by computer simulation using the SImulation MOdel Non-linear (SIMON) vehicle dynamic simulation model version 3.1 within the Human Vehicle Environment (HVE) software version 5.2. SIMON will be referred to in this paper as the computer or simulation model, while HVE will be referred to as the computer software. In the previous study, a simple method to model the curb was developed and version 2.0 of the simulation model was validated, for delta-v, up to approximately 6.7 m/s (15 mph) and for vertical accelerations, up to speeds of approximately 4.5 m/s (10 mph).

This study was conducted to compare vehicle speed change and acceleration data from full scale testing to results generated by the Simulation Model Non-linear (SIMON) vehicle dynamic simulation model (version 2.0) within the Human Vehicle Environment (HVE) software. The study also sought to expand the body of existing curb impact tests and compare the present results to data from published literature. The results of the full scale testing of a 1996 Dodge Ram 1500 pickup are presented. Instrumented tests were performed at speeds up to approximately 6.7 m/s (15.0 mph) and at approach angles of 90° and 45°. SIMON was used to simulate the full scale testing conducted by the authors. The simulation results, including primarily vehicle speed change (delta-v), and accelerations are compared to the results of full scale testing. The appropriate method for modeling curb profile within SIMON version 2.0 was studied and is presented in this paper.