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In general for Vehicle-to-Vehicle (V2V) communication, message authentication is performed on every received wireless message by conducting verification for a valid signature, and only messages that have been successfully verified are processed further. In V2V safety communication, there are a large number of vehicles and each vehicle transmits safety messages frequently; therefore the number of received messages per second would be large. Thus authentication of each and every received message, for example based on the IEEE 1609.2 standard, is computationally very expensive and can only be carried out with expensive dedicated cryptographic hardware. An interesting observation is that most of these routine safety messages do not result in driver warnings or control actions since we expect that the safety system would be designed to provide warnings or control actions only when the threat of collision is high.

The intersection of changing lifestyles and evolving transportation needs finds smart USA well positioned for launch in 2008 during one of the most competitive periods in U.S. automotive history. In a zero sum market with new global entrants competing for single points of share, where quality levels have been redefined and fractions of points separate the best from the challengers, lifestyle awareness, innovation and product positioning become the differentiators. Simply adding features has left some with hefty investments and confused consumers. Bigger is not always better. More is not always desirable. The real opportunity for new entrants to the US market may be defined within niche markets where changing lifestyles allow for the emergence of new segments. Today, smart USA has surfaced as a clear example of right product, right place, right time.

Software programs in non-application areas such as Board Support Packages, Hardware Abstraction Layers, signal processing and data acquisition are more or less very standard and common across many applications. These form a major part of the “platform” software, which changes very little. However, it is seen that many a time, efforts are spent resolving issues in the hardware dependent layers rather than concentrating on the application at hand, despite the fact that the software controlling the hardware has been developed many times. There are many reasons why this section of the software is rewritten many times over: different coding standards, different software architecture and layering concepts, the dreadful cut-and-paste methods, and so on. Introduction of a tool-based code configurator and generator eliminates access to the code and focuses on configuring a pre-written set of SW procedures. Advantages: Standardization, reuse and high levels of productivity.

As part of an overall effort to support the National Highway Traffic Safety Administration's (NHTSA) national program to increase seat belt usage, General Motors instituted an employe seat belt use incentive program at the General Motors Technical Center in Warren, Michigan. This program was responsible for raising seat belt use at the Tech Center from 36% to 70% during its 5 1/2 month duration. The program was patterned, in part, after research work done by professor E. Scott Geller of the Virginia Polytechnic Institute and State University under a grant from the General Motors Research Laboratories and a program conducted by Berg Electronics (a DuPont subsidiary). The intent of the program was to provide sufficient positive incentive to employes to buckle up for an extended period of time, thereby establishing a seat belt use habit that will continue after the incentives are no longer offered.

The SHIFT-MATE is a dashboard mounted computer based device that cues a truck driver to shift more efficiently. Through electronic circuitry, key vehicle parameters are monitored, computed, then via graphic display, instructs the driver when to shift for improved fuel economy. The theory of operation is described in the text.

Posture and gait controls underlie the fundamental physical and cognitive human factors necessary for astronauts’ safety and performance in Space. This central subsystem is adversely affected when exposed to an extreme or hostile environment. A specific stimulation, using dermal optical sensitivity, can be provided to the central nervous system to counteract peripheral stimulations due to microgravity as well as other negative stressors. We believe using dermal optical sensitivity-based stimulation can be key in the performance enhancement necessary to ensure human based space mission viability and success.

A sense of “personal integrity” blocks pilot use of new information about how he thinks. Research on human performance under stress done over the past fifty years indicates increased rigidity and regression to earlier learned behavior in high stress, and in low Stress a shift in attention to any domestic situation or on the job controversy which is of higher stress than that of the job at hand, all without the pilot's knowledge. Informal surveys of commercial pilot training and commercial pilot attitudes towards these studies indicate that the study findings directly confront learned cultural responses. Pilot and trainer reactions prevent the information from being adequately investigated or formally taught. The findings are not written into training manuals and pilots who are informally given the information do not have adequate access to the knowledge when it is needed.

A large number of testing procedures have been developed to ensure vehicle safety in common and extreme driving situations. However, these conventional testing procedures are insufficient for testing autonomous vehicles. They have to handle unexpected scenarios with the same or less risk a human driver would take. Currently, safety related systems are not adequately tested, e.g. in collision avoidance scenarios with pedestrians. Examples are the change of pedestrian behaviour caused by interaction, environmental influences and personal aspects, which cannot be tested in real environments. It is proposed to use augmented reality techniques. This method can be seen as a new (Augmented) Pedestrian in the Loop testing procedure.

Research information on solid lubricants has been compiled for consideration in the possible use of such materials in aircraft electrical equipment. Solid lubricants are capable of lubricating at the maximum temperatures (600° F) for aircraft electrical equipment. Many solids that adhere well to metals may be useful lubricants; those with layer-lattice structure usually give low friction. Solid lubricants are most commonly used as bonded films but the use of fluid carriers and surface reaction products have considerable merit.

A multi vector design tool to accurately predict instrument panel obscuration was developed to insure that critical legal displays in vehicles are not obscured. The concept provides for a computer generated light source shaped to replicate the human eyes. The light source is then projected onto a 3D math based arrangement and the resultant shadows are visible on the instrument panel surface and its displays. Design studios require criteria for the placement of the instrument cluster gages and displays, various controls, switches, and steering column stalks before an interior theme can be completed. Therefore, instrument panel obscuration and visibility must be determined early in the design process. The obscured areas are a function of the instrument panel surface, steering wheel rim, hub, spokes, and the location of the driver's eyes. This light source method allows engineers and designers the ability to quickly determine obscured areas.

Vehicle dynamics is a discipline of mechanical engineering that benefited of significant improvements thanks to the progress of computational engineering. Vehicle dynamics engineers are using CAE for the development of a vehicle with MBS and FEA. The concurrent use of these two technologies is a standard in the automotive industry. However the current simulation process is not fully efficient because local geometrical and material nonlinearities are not accurately modeled in classical MBS software. This paper introduces a methodology for vehicle dynamics simulation integrating MBS capabilities in one single nonlinear FEA environment enabling an accurate modeling of nonlinearity in vehicles.

Issues relating to the reduction of CO₂ emissions and energy consumption are currently more important than ever before. In the construction engineering and automotive sectors research and development efforts are focused closely on efficient buildings and automobiles. The designated target is a reduction in greenhouse gas emissions and overall energy demand. However, almost all approaches focus solely on either "buildings" or "mobility." By considering both aspects as a single holistic system, further energy saving potential arises due to synergetic effects. The goal of current research projects relating to Smart Homes and Vehicle to Building (V2B) is to smooth the electrical load profile on a household level rather than to reduce the individual-related total energy consumption and thereby the CO₂ emissions.

The results of several anti-knock studies are discussed in this paper. Road anti-knock performance for 1000 fuel blends covering the years 1940 to 1957 have been investigated. The laboratory Research octane numbers of these fuels covered the range from 80 to 105. The fuels were evaluated in 46 cars representing a cross-section of the automotive products for these years. The objective of these investigations was to determine the practical application of the laboratory to road octane rating relationships, and the effect of vehicles, and operating conditions on these relationships. The results show that there is a valid correlation between laboratory and road octane ratings. The relative importance of Research and Motor octane ratings on road performance is influenced by make of car, engine speed, throttle position, and distributor advance characteristics. It also indicated that aromatics improve, whereas olefins reduce high speed Modified Borderline ratings.

When looking into using PCMCIA PC Cards in the avionics market, three areas must be researched. The first is what are the applications and benefits of using the PC Cards while in flight, followed by the applications and benefits on the ground, and thirdly on how to make a PC Card that would stand up to the rugged avionics environment. PCMCIA PC Cards can be used in all aspects of flight. Three possible applications on the ground are; paperless documentation, modifications, flightline changes. Once airborne, PC Cards can be removed and a different functionality card can be inserted. One PC card socket can be used for many different functions during one flight. Some of the possible applications for PC Cards inflight are; flight plan changes, backup Line Replaceable Units (LRUs), and solid state data collection.

In recent years there has been increasing interest in quantifying the emissions from aircraft in order to generate inventories of emissions for climate models, technology and scenario studies, and inventories of emissions for airline fleets typically presented in environmental reports. The preferred method for calculating aircraft engine emissions of NOx, HC, and CO is the proprietary “P3T3” method. This method relies on proprietary airplane and engine performance models along with proprietary engine emissions characterizations. In response and in order to provide a transparent method for calculating aircraft engine emissions non proprietary fuel flow based methods 1,2,3 have been developed. This paper presents derivation, updates, and clarifications of the fuel flow method methodology known as “Fuel Flow Method 2”.

The goal of this project was to investigate how to make driver distraction state classification more efficient by applying selected machine learning techniques to existing datasets. The data set used in this project included both overt driver behavior measures (e.g., lane keeping and headway measures) and indices of internal cognitive processes (e.g., driver situation awareness responses) collected under four distraction conditions, including no-distraction, visual-manual distraction only, cognitive distraction only, and dual distraction conditions. The baseline classification method that we employed was a support vector machine (SVM) to first identify driver states of visual-manual distraction and then to identify any cognitive-related distraction among the visual-manual distraction cases and other non-visual manual distraction cases.

Driver state monitoring is a crucial technology for enhancing road safety and preventing human error-caused accidents in the era of autonomous vehicles. This paper presents CogniSafe, a comprehensive driver monitoring system that uses deep learning and computer vision methods to detect various types of driver distractions and fatigue. CogniSafe consists of four modules: Driver anomaly detection and classification: A novel two-phase network that proposes and recognizes driver anomalies, such as texting, drinking, and adjusting radios, using multimodal and multiview input. Gaze estimation: A video-based neural network that jointly learns head pose and gaze dynamics, achieving robust and efficient gaze estimation across different head poses. Eye state analysis: A multi-tasking CNN that encodes features from both eye and mouth regions, predicting the percentage of eye closure (PERCLOS) and the frequency of mouth opening (FOM).

Energy demand climbs as a consequence of the inherent relationship between the rate of consumption of energy and the growth of the economy. In light of the depletion of fossil fuels, it is necessary to implement energy efficiency techniques and policies that support sustainable development. Globally, researchers show more interest in discovering fossil fuel alternatives, as a result of fuel crisis. This research elaborates on the production and experimental investigation of briquettes made from ideal municipal solid waste (MSW), such as food waste and garden waste, as a feasible choice for alternate fossil fuels. From Municipal, agricultural, and food waste, we can get biomass waste. Municipal solid and agricultural waste is extensively dispersed, but their potential for converting biomass into energy generation still needs to be explored. This study was carried out based on the information gathered from various studies published in the scientific literature.

The objective of the development of the aerodynamic drag predictive tool CDaero was for use as a module for the Automobile Design Support System (AutoDSS). CDaero is an empirically based drag coefficient predictive tool based initially on the MIRA (Motor Industry Research Association) algorithm. The development philosophy was to be able to predict the aerodynamic drag coefficient of an automobile with knowledge of the features of the surface geometry control curves. These are the curves that control the 3-dimensional geometry as seen in the profile, plan and front and rear views. CDaero has been developed in a computing environment using the equation solver TKSolver™. Fifty-one input feature values are first determined from the automobile geometry and then entered into the program. CDaero models the drag coefficient with thirteen different components covering the basic body, as well as additional components such as the wheels, mud flaps, etc.