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Hundreds of millions of micromachined, piezoresistive Manifold Absolute Pressure (MAP) sensors have been produced to reduce pollution and improve fuel efficiency in engine control systems. Other vehicle applications for micromachined pressure sensors include monitoring turbo pressure, barometric pressure, fuel tank leakage, fuel rail pressure and tire pressure. Exhaust gas recirculation and even door compression for side impact detection are employing micromachined silicon pressure sensors. Piezoresistive pressure sensors have dominated the automotive market to date. Practical micromachined capacitive pressure sensors have recently been developed and could replace the piezoresistive sensor in many applications. This paper will examine the advantages of both pressure sensing technologies, and discuss applications that an inexpensive capacitive pressure sensor will open up.

Despite the general similarity of U.S. and European heavy trucks, there are differences in design properties that affect braking and turning performance. A European tractor-semitrailer was studied for the purpose of comparing its properties to those of U.S. vehicles and assessing the comparative performance. Mass, suspension, and braking system properties of the European tractor and semitrailer were measured in the laboratory and on the proving ground. Turning and braking performance qualities were evaluated by computer simulation and by experimental tests. In turning performance the European combination had a 9 percent advantage in rollover threshold, compared to a generic U.S. vehicle with properties that were in the midrange of U.S. design practice. Higher suspension roll stiffness and higher chassis weight on the European tractor and semitrailer accounted for the higher threshold.

Collision warning systems (CWS) are a relatively new technology to reduce or mitigate motor vehicle rear-end and side impact collisions. This study compared available police-reported crash experiences of 6,143 CWS-equipped heavy trucks with the experiences of 383,058 heavy trucks without CWS. Data were from the Motor Carrier Management Information System (2000-2002). Results suggest that CWS-equipped trucks had a significantly lower proportion of crashes involving other moving vehicles and a significantly lower proportion of multiple vehicle crashes compared to trucks without CWS, (40% vs. 49%, p<0.0001; 62% vs. 67%, p<0.004 respectively). These changes are the first crash-data based evidence that supports the design effect of CWS. However, more studies are needed to determine the specific impacts of CWS on heavy truck crashes.

For several staged collisions, results obtained with closed form reconstruction calculations and with a computerized step-by-step procedure are compared with measured responses. A refined, closed-form reconstruction procedure is defined, derivations of the analytical relationships are outlined and detailed results of sample applications are presented. Closed form calculation procedures for estimating impact conditions became a topic of interest in relation to the development of an automatic starting routine for iterative applications of the Simulation Model of Automobile Collisions (SMAC) computer program. The accuracy of initial estimates of speeds determines the total number of iterative adjustments of SMAC that are required to achieve an acceptable overall match of the evidence. Since a high degree of success was achieved in the refinement of such calculation procedures, the end product, by itself, is considered to be a valuable aid to accident investigations.

In order to evaluate the THOR-50M as a front impact Anthropomorphic Test Device (ATD) for vehicle safety design, the ATD was compared to the H3-50M in matching vehicle crash tests for 20 unique vehicle models from 2 vehicle manufacturers. For the belted driver condition, a total of fifty-four crash tests were investigated in the 56.3 km/h (35 mph) front rigid barrier impact condition. Four more tests were compared for the unbelted driver and right front passenger at 40.2 km/h (25 mph) in the flat frontal and 30-degree right oblique rigid barrier impact conditions. The two ATDs were also evaluated for their ability to predict injury risk by comparing their fleet average injury risk to Crash Investigation Sampling System (CISS) accident data for similar conditions. The differences in seating position and their effect on ATD responses were also investigated.

This paper describes a general purpose computer graphics interface for performing detailed two- and three-dimensional studies involving the dynamic response of humans and vehicles during the pre-crash, crash and post-crash phases of a motor vehicle accident. Specifications are provided for human, vehicle and environment models which can be constructed and analyzed using the interface. The requirements of analysis methods which may be incorporated into the interface are examined, and several examples are provided. Finally, the paper illustrates how the interface is used for creating high-level animations to view the resulting human and/or vehicle motion on various output devices such as computer displays, printers, plotters and video tape recorders.

A class of heavy truck vehicles, characterized primarily by high centers of gravity, was studied using analysis and computer simulation to identify and understand the relationship between directional and roll stability of such vehicles during steady turning maneuvers. Findings of the computer-based study suggest: (1) directional instability (yaw divergence) is possible for such vehicles during steady turning while operating at elevated speeds on horizontal road surfaces, (2) yaw divergence will lead to rollover in the absence of corrective steering action and/or reduced speed, and (3) the primary mechanism responsible for precipitating yaw divergent behavior in such vehicles is the nonlinear sensitivity of truck tire cornering stiffness to vertical load acting in combination with typical heavy truck fore/aft roll stiffness distributions. In addition, the influences of roadway superelevation and driver steering control as contributors to vehicle stabilization are examined and discussed.

The reproduction of the vehicle motion is a crucial element of accident reconstruction. Apart from the position of the center of gravity in an inertial coordinate system, the vehicle heading plays an important role. The heading is the sum of the yaw angle and the vehicle body side slip angle. In standard vehicles, the yaw angle can be determined using the yaw rate sensor and the wheel speeds. However, the yaw rate sensor is often subject to temperature drift. The wheel speed signals are forged at low speeds or due to slip. These errors result in significant deviations of reconstructed and real vehicle heading. Therefore, an intelligent combination of these signals is required. This paper describes a fuzzy system which is capable to increase the accuracy of yaw angle calculation by means of fuzzy logic. Before the data is applied to the fuzzy system, it is preprocessed to ensure the accuracy of the fuzzy system inputs.

The research on connected vehicles has attracted much interest of governments and research institutions in these days. As researchers who have been deeply intrigued, we are particularly interested in investigating the lane changing issues of connected buses when exiting bus stops. In order to examine the utilities of both the buses and social vehicles in a connected environment, we employ the game theory to analyze the interactions between them. A two-player, non-cooperative, non-zero-sum game model was built in this paper. We analyzed 5 different scenarios for bus exiting at bus bay stops and curbside bus stops. The payoffs considered in the game model were mainly from the perspective of safety and time. Besides the commonly studied safety issues caused by collisions, we supplement the existing literature by adding on non-collision injuries caused by improper driving behaviors (e.g. excessive acceleration).

Today, active dynamic control systems for commercial vehicles, offering improved safety, are frequently discussed. Yaw stabilising systems are based on theories from passenger car implementation, yet roll stabilisation - probably introduced in the near future - requires increased knowledge of rollover mechanics. Static analysis, providing steady state rollover threshold (SSRT), is the most common approach. Nevertheless in a rolling vehicle, kinetic energy is always present, deteriorating roll stability, invalidating the analysis. A simple method determining the dynamic rollover threshold (DRT) is therefore introduces in this paper. DRT is the worst case measure of roll instability: the conditions are necessary but not sufficient for rollover.

In recent years research and development on ‘compatibility’ in the area of collision safety has been proceeding. It is a big issue how to prevent an increase in the severity of injuries of occupants in a weaker vehicle. With regard to FUP (Front Underrun Protector), we consider it possible to further lessen the severity of injuries of car occupants by simultaneously studying the requirement for collision safety on the passenger car as well as the requirement for strength stipulated by the ECE regulation. Therefore we develop the study method for collision safety structure using an optimizing method.

An experimental methodology is proposed to measure the rollover propensity of road tankers when subjected to lateral perturbations derived from steering manoeuvers. The testing principle involves subjecting a scaled down sprung tank to the elimination of a lateral acceleration, to analyze its rollover propensity as a function of various vehicle's operational and design parameters. Initial acceleration is generated through putting the scaled tank on a tilt table supported by a hydraulic piston. The controlled release of the fluid in the hydraulic system generates a perturbation situation for the tank, similar to the one that a vehicle experiences when leaving a curved section of the road and going to a straight segment. Durations for the maneuver and initial tilt angles characterize both the corresponding intensities of the steering maneuver.

A long standing problem with heavy vehicle stability has been rollover. With the higher center of gravity, heavier loads, and narrower tracks (as compared to passenger vehicles), they have a lower rollover stability threshold. In this paper, a rollover stability control algorithm based on a two-degrees-of-freedom (DOF) and a three-DOF vehicle model for a two-axle truck was developed. First, the 3DOF model was used to predict the future Lateral load Transfer Rate (LTR). Using this LTR value, the dynamic rollover propensity was estimated. Then, a robust output feedback gain control rollover stability control algorithm based on the combination of active yaw control and active front steering control was developed. A H₂/H∞/poles placement multi-objective control strategy was developed based on the 2DOF reference model.

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.

The study of heavy vehicles rollover prediction, especially in algorithm-based heavy vehicles active safety control for improving road handling, is a challenging task for the heavy vehicle industry. Due to the high fatality rate caused by vehicle rollover, how to precisely and effectively predict the rollover of heavy vehicles became a hot topic in both academia and industry. Because of the strong non-linear characteristics of Human-Vehicle-Road interaction and the uncertainty of modeling, the traditional deterministic method cannot predict the rollover hazard of heavy vehicles accurately. To deal with the above issues, this paper applies a probability method of uncertainty to the design of a dynamic rollover prediction algorithm for heavy vehicles and proposes a novel algorithm for predicting the rollover hazard based on the combined empirical model of reliability index and failure probability.

This paper describes a crash detection system developed for use in automotive passive restraint applications. The system is unique in that the small, rugged module performs all of the functions necessary to determine when airbag deployment is required. Because it is designed to be mounted near the impact zone, the system is well suited to three difficult crash discrimination situations: front impacts in body-on-frame vehicles such as light trucks, side impacts in any automobile, and crash severity discrimination for future adaptive restraint systems.

Automobile accident reconstruction and vehicle collision analysis techniques generally separate vehicle collisions into three different phases: pre-impact, impact and post-impact. This paper will concern itself exclusively with the modeling of the impact phase, typically defined as the time the vehicles are in contact. Historically, two different modeling techniques have been applied to the impact of vehicles. Both of these techniques employ the impulse-momentum formulation of Newton's Second Law. The first relies exclusively on this principle coupled with friction and restitution to completely model the impact. The second method combines impulse-momentum with a relationship between crush geometry and energy loss to model the impact. Both methods ultimately produce the change in velocity. ΔV, and other pertinent information about a collision.

This paper describes a forward looking on-board vehicle detection and driver alert system that provides a distance indication and alert tone to the driver. The system, called VORAD (Vehicular On-board Radar), is the first of its kind to be fielded. The system can be programmed to function in different operating modes, allowing customization to the user's requirements. Some possible operating modes include simply providing an alert to the driver, providing following distance indication measured in seconds based on the vehicles' speeds, or providing following distance measured in feet. The VORAD System also has optional features to enhance its usefulness, including a blind spot alert system and a built-in event recorder. The blind spot system provides additional information to the driver regarding the presence of vehicles in his blind spot for use in making lane changes.

Motor vehicle accidents are often difficult to resolve since the data is conflicting and of questionable validity. Conventional analysis requires a great deal of expertise on the part of the accident investigator. Problems that are conceptual and cannot be reduced to numbers can often be solved using expert system technology. KAR is a prototype rule based Knowledge-based Accident Reconstruction system used at the initial stage of an investigation. The program is capable of calculating vehicle speeds using any combination of the following techniques: skid, roll, overturn, yaw, vault, momentum and energy. The system's most notable feature is its interpretive abilities. The program is able to determine how to solve the mechanics of the accident, and verifies the evidence before it uses a particular method in the calculations. Additionally, an interactive explanation facility allows the user to examine the program's reasoning.

Computational finite element (FE) modeling of real world motor vehicle crashes (MVCs) is valuable for analyzing crash-induced injury patterns and mechanisms. Due to unavailability of detailed modern FE vehicle models, a simplified vehicle model (SVM) based on laser scans of fourteen modern vehicle interiors was used. A crash reconstruction algorithm was developed to semi-automatically tune the properties of the SVM to a particular vehicle make and model, and subsequently reconstruct a real world MVC using the tuned SVM. The required algorithm inputs are anthropomorphic test device position data, deceleration crash pulses from a specific New Car Assessment Program (NCAP) crash test, and vehicle interior property ranges. A series of automated geometric transformations and five LSDyna positioning simulations were performed to match the FE Hybrid III’s (HIII) position within the SVM to reported data. Once positioned, a baseline simulation using the crash test pulse was created.