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Prior research has tested the validity of Cycles Engine render in Blender for the creation of physically correct lighting models; however, a research gap still exists in examining the use of Arnold render engine in 3DS Max for accident reconstruction and other forensic settings [1]. Specifically, the process presented in this paper utilizes the Arnold render engine within 3DS-Max to analyze the lighting models. Arnold is a physically-based render (PBR) engine and can be used to recreate an accident scene geometry and lighting conditions. The goal is to create light sources within Arnold that represent the real-world light sources. The light sources in Arnold are quantified by several variables, including intensity, color, and size. The intensity and size variables determine the self-emitted radiance of the light source and require further explanation to determine the relationship between these variables in Arnold and real-world lighting quantities.

Video from dash or surveillance cameras is sometimes used in vehicle accident reconstruction to analyze the speeds of vehicles. However, video captured during nighttime, during poor visibility conditions, or of events out of frame may not always visually capture details needed to determine the speed of the vehicle in question. Prior research has determined speed from vehicle acoustic signals, but little research has analyzed the audio portion of dash camera video for use in accident reconstruction and other forensic settings. The purpose of this study was to outline and test the validity of a method for using the audio portion of dash camera video to determine vehicle speed. Extracting the audio portion from the video recording and further processing it with commercially available software can allow the calculation of vehicle speed and acceleration when traveling over roadway surfaces and detection of turn signal activations while driving.

Mapping the luminance values of a visual scene 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. Previous work has shown that pixel intensity captured by consumer-grade digital still cameras can be calibrated to estimate luminance [1-7]. Taking a digital still image and converting this image into a luminance map even further reduces the time required for luminance measurement. Suway and Suway previously presented a methodology for estimating luminance from digital images and video of a scene [1]. In this paper, the authors update this methodology for calculating luminance from a digital camera.

Laser scanners are typically used in vehicle accident reconstruction and forensic applications to measure roadway and vehicle details. However, laser scanners used near congested roadways can digitize unwanted passing vehicles, which produces a scan with noisy and poor image quality point clouds. On the other hand, small Unmanned Aircraft System (sUAS) images of reflective objects may result in a less accurate mesh, and capturing vertical surfaces such as telephone poles, traffic lights, and building faces is more difficult. Prior research has tested the accuracy of sUAS-captured images processed with commercially available software, such as AgiSoft or Pix4D, as well as in comparison to the accuracy of laser scan data. Research still has yet to be conducted on combining the laser scans and sUAS images for use in accident reconstruction and other forensic settings.

It is important for large trailers to be outlined with retroreflective tape to make them more conspicuous in roadway environments with diminished ambient lighting. Retroreflective material is also utilized on signs as well as clothing to improve their conspicuity. As used conspicuity tape does not perform at the same level as clean and new tape. Hence, there is a need for visibility testing of retroreflective materials with degraded or reduced effectiveness. In an effort to control the coefficient of retroreflection (RA). A methodology that uniformly obscured parts of the retroreflective materials was developed. Validation testing of this procedure was conducted using glass bead sheeting, as well as microscopic prismatic sheeting. The results from the study showed that, by uniformly obscuring parts of the tape, RA is approximately a linear function of the area exposed to the viewer. Thus, the overall perceived brightness and coefficient of retroreflection readings were reduced.

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.

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.

Collision statistics show that more than half of all pedestrian fatalities caused by vehicles occur at night. The recognition of objects at night is a crucial component in driver responses and in preventing nighttime pedestrian accidents. To investigate the root cause of this fact pattern, Richard Blackwell conducted a series of experiments in the 1950s through 1970s to evaluate whether restricted viewing time can be used as a surrogate for the imperfect information available to drivers at night. The authors build on these findings and incorporate the responses of drivers to objects in the road at night found in the SHRP-2 naturalistic database. A closed road outdoor study and an indoor study were conducted using an automatic shutter system to limit observation time to approximately ¼ of a second. Results from these limited exposure time studies showed a positive correlation to naturalistic responses, providing a validation of the time-limited exposure technique.

Dynamic Brake Support (DBS) is a safety system that has been applied to various passenger cars and has been shown to be effective at assisting drivers in avoiding or mitigating rear-end collisions. The objective of a DBS system is to ensure that the brake system is applied quickly and at sufficient pressure when a driver responds to a collision imminent situation. DBS is capable of improving braking response due to a passenger car driver's tendency to utilize multi-stage braking. Interest is developing in using DBS on commercial vehicles. In order to evaluate the possible improvement in safety that could be realized through the use of DBS, driver braking behavior must first be analyzed to confirm that improvement is possible and necessary. To determine if this is the case, a study of the response of truck drivers' braking behavior in collision imminent situations is conducted. This paper presents the method of evaluation and results.

This research was to model a 6×4 tractor-trailer rig using TruckSim and simulate severe braking maneuvers with hardware in the loop and software in the loop simulations. For the hardware in the loop simulation (HIL), the tractor model was integrated with a 4s4m anti-lock braking system (ABS) and straight line braking tests were conducted. In developing the model, over 100 vehicle parameters were acquired from a real production tractor and entered into TruckSim. For the HIL simulation, the hardware consisted of a 4s4m ABS braking system with six brake chambers, four modulators, a treadle and an electronic control unit (ECU). A dSPACE simulator was used as the “interface” between the TruckSim computer model and the hardware.

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.

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.

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.

According to NHTSA's 2011 Traffic Safety Facts [1], passenger vehicle occupant fatalities continued the strong decline that has been occurring recently. In 2011, there were 21,253 passenger vehicles fatalities compared to 22,273 in 2010, and that was a 4.6% decrease. However; large-truck occupant fatalities increased from 530 in 2010 to 635 in 2011, which is a 20% increase. This was a second consecutive year in which large truck fatalities have increased (9% increase from 2009 to 2010). There was also a 15% increase in large truck occupant injuries from 2010. Moreover, the fatal crashes involving large trucks increased by 1.9%, in contrast to other-vehicle-occupant fatalities that declined by 3.6% from 2010. The 2010 accident statistics NHTSA's report reveals that large trucks have a fatal accident involvement rate of 1.22 vehicles per 100 million vehicle miles traveled compared to 1.53 for light trucks and 1.18 for passenger cars.

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.