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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.

A line of five new row-crop tractors is being introduced by John Deere with innovative features including a 15-speed full power shift transmission, a high capacity, highly-maneuverable full-time mechanical front-wheel drive and micro-processor controlled instrumentation. In addition, the tractors have increased power, improved fuel economy, greater hydraulic power, improved hitch sensing, improved operator controls, lower sound levels, and revised styling. This paper documents the design and development of these new John Deere row-crop tractors.

Fuel economy can be part of a business case for a fleet making the decision to buy new HD hybrid drivetrain technologies. Chassis dynamometer tests using SAE Recommended Practice J2711 on a bus equipped with an Allison EP SYSTEM ™ hybrid system and operated on standard bus driving cycles have produced impressive gains of over 60%. Preliminary urban bus field tests, on the other hand, have shown lower fuel economy gains. The difference can be attributed, in part, to the use of accessories - most importantly air conditioning - which are parasitic loads on the vehicle. In this paper the characteristics of driving cycles are studied to determine those factors which have the strongest influence on fuel economy for hybrids. The data show that the number of stopping events in a route or cycle is a strong influence as is the average vehicle speed. Energy analysis will show the relationship of fuel economy benefit and battery energy within a driving cycle.

TFC/IW, total fuel consumption divided by inertia weight is reported with other engineering variables for recent EPA data for industry passenger cars and truck. TFC/IW is used in comparisons between gasoline and diesel engines, 49 States and California, passenger cars and trucks. The California fuel economy penalty due to more stringent emissions standards is discussed. The relationship between TFC/IW and ton miles per gallon is shown. Special attention is focused on 4 cylinder gasoline powered vehicles in 49 States passenger car fleet. The use of TFC/IW to answer the question, ‘What Changed?’ when comparing the fuel economies of two fleets is described.

High performance lubricant additive systems have been developed to formulate SAE 5W-30 passenger car engine oils which meet current and anticipated requirements of the North American original equipment manufacturers. The trend in North America is to recommend SAE 5W-30 oils that not only meet the API SF requirements for gasoline engines (“first-generation” oils), but also meet the stringent API CC requirement for light duty diesel engines (“second-generation” oils). Furthermore, the engine builders have issued “world specifications” for motor oils which incorporate additional “second-generation” SAE 5W-30 characteristics, such as enhanced API SF limits, improved fuel efficiency, an increased margin of bearing protection, and lower finished-oil phosphorus levels. The additive systems described herein exceed API SF and CC requirements as well as “second-generation” performance hurdles.

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.

Estimation of soot deposited on a wall flow type DPF, is a vital information to ensure safe and efficient DPF management. Accuracy in determining mass of soot present inside the DPF ensures a correct regeneration management strategy in-terms of fuel efficiency and DPF safety considering soot overloading and too frequent regenerations. It also ensures an efficient detection of anomalies in the PM filtration mandated by the BSVI/EURO VI legislation as a part of On-board diagnostics. Classical approach of determining soot present inside DPF involves monitoring increase in pressure drop. Real time usage of such a model is limited by the inaccuracy of measuring pressure drop at low exhaust flows. Hence, contemporary engine controllers use pressure drop based models as a failsafe and estimate DPF soot loading by modelling soot release rate due to engine combustion and the rate at which it is oxidized.

This study mainly focuses on the blending of Alumina and Titanium oxide nanoparticles (NP’s) in Spirulina biodiesel blends (SB20) to estimate the influence of engine (combustion, performance and emission) parameters of a diesel engine. The characterization of Al2O3 and TiO2 NP’s like SEM were reported. By using various fuel samples such as Diesel, SB20, SB20+40 ppm AO, SB20+80 ppm AO, SB20+40 ppm TO and SB20+80 ppm TO, the engine tests on the diesel engine were conducted at various load conditions. The BTE for SB20+80 ppm AO were enhanced by 12.35% and 8.4 % compared to the SB20 fuel and SB20+40 ppm AO fuel samples. The combustion parameters were improved for the NP’s as additives (Al2O3 and TiO2) fuels than the SB20 fuel sample because NP’s contain oxygen content. The parameters of engine exhaust emissions such as HC, CO and smoke are drastically diminished for the SB20+40 ppm AO, SB20+80 ppm AO, SB20+40 ppm TO and SB20+80 ppm TO fuels compared to the SB20 fuel.

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.

The current research was aimed at determining the most effective way to use alternative renewable feedstock to power a diesel engine. Mimusops elengi, a new and novel biofuel was recognized for this current study, which is widely available in the south of India. The investigation was conducted on B20 volume basis (20% Mimusops elengi methyl ester blended with 80% diesel). Furthermore, it was recognized that when the performance characteristics were traded off, the emission magnitude has slightly higher. To address the diesel engine pollution, an oxygenated nano additive like titanium oxide was dissipated only with the fuel blend at distinct mass fractions of 25 parts per million (ppm) with differing injection pressures of 180 bar, 200 bar, 220 bar, and 240 bar. The tests were created using a statistical programme known as design of experiments, which is purely based on Taguchi and response surface methodology.

Advanced diesel engines developed for the commercial market need to be adapted to the military requirements by OPERAS (Optimizing the injection pressure P, the Exhaust gas recirculation E, injection events Retard and/or Advance and the swirl ratio S). The different after treatment devices, already used or expected to be applied to diesel engines, require feed gases of appropriate properties for their efficient operation. To produce these gases some OPERAS are needed to control the diesel combustion process. Since military vehicles do not need the after treatment devices, the OPERAS of the commercial engines should be modified to meet the military requirements for high power density, better fuel economy, reduction of parasitic losses caused by the cooled EGR system, and reduction of invisible black and white smoke in the field.

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.

Due to ever soaring fuel costs and even more stringent emission regulations which require more elaborate technical efforts and unfortunately lead to a negative trend on fuel economy as well, todays and future trucking business is extremely challenged. These facts create an urgent requirement for the engine manufacturer to offer an engine with an optimized cost-benefit-ratio for the trucking business. Mercedes-Benz, as the leader in the European commercial vehicle market - of which e. g. high fuel costs, long maintenance intervals and high engine power-to-weight ratios have always been key characteristics - has developed a new class 8 engine for the US market. The MBE 4000 is a 6 cylinder inline engine in the compact size and low weight category, but due to its displacement of 12,8 liters it offers high performance characteristics like heavier big block engines.

The influence of engine variables on the concentration of oxides of nitrogen present in the exhaust of a multicylinder engine was studied. The concentrations of nitric oxide (NO) were measured with either a mass spectrometer or a non-dispersive infrared analyzer. The NO concentration was low for rich operation (deficient in oxygen) and increased with air-fuel ratio to a peak value at ratios slightly leaner than stoichiometric proportions. A further increase in air-fuel ratio resulted in reduced NO concentrations. Advanced spark timing, decreased manifold vacuum, increased coolant temperature and combustion chamber deposit buildup were also found to increase exhaust NO concentration. These results support either directly or indirectly the hypothesis that exhaust NO concentration is primarily a result of the peak combustion gas temperature and the available oxygen.

A lithium ion battery system has been developed for use in Honda's FCX Clarity fuel cell vehicle. This represents the first time that Honda has employed lithium ion batteries. The battery system equals the high level of power of the ultracapacitor system used in the previous FCX vehicle but achieves a higher level of energy, contributing to various improvements in performance, such as the Clarity's superior acceleration feel and improved fuel efficiency. The system displays sufficient durability and reliability at the same time as satisfying requirements from the perspective of safety. In addition, positioning the battery system under the floor of the vehicle has increased cabin space, boosting the Clarity's commercial appeal.

Over the last decade, Climate change due to fossil fuel burning has taken centre stage in all discussions. Automotive sector has come under some flak for being one of the contributors to this Climate Change. Active steps have been taken by Vehicle Manufacturers and their Suppliers to address this issue. This sector has been facing below challenges to reduce pollutant in the air by A. Reducing Emissions, B. Increasing Energy Efficiency C. Use of Renewable Energy. One of the many alternatives by the Automotive Industry was to have a phased introduction to Electric Vehicles (EV), Hybrids, Fuel cells and other variants. As various emission norms and safety requirements takes Centre stage, it invariably, increases the weight of the vehicle. Now a days, Vehicles are having challenges to make it lightweight to achieve Range for an EV and improve fuel efficiency without sacrificing safety.

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).

Due to the rising costs of fuel and increasingly stringent regulations, auto makers are in need of technology to enable more fuel-efficient powertrain technologies to be introduced to the marketplace. Such powertrains must not sacrifice performance, safety or driver comfort. Today's engine and powertrain manufacturers must, therefore, do more with less by achieving acceptable vehicle performance while reducing fuel consumption. One effective method to achieve this is the extreme downsizing of current direct injection spark ignited (DISI) engines through the use of high levels of boosting and cooled exhaust gas recirculation (EGR). Key challenges to highly downsized gasoline engines are retarded combustion to prevent engine knocking and the necessity to operate at air/fuel ratios that are significantly richer than the stoichiometric ratio.