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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.

In the modern and fast growing automotive sector, reliability & durability are two terms of utmost importance along with weight & cost optimization. Therefore it is important to explore new technology which has less weight, low manufacturing cost and better strength. The new technology developed always seek for a quick, cost effective and reliable methodology for its design validation so that any modification can be made by identifying the failures. This paper presents the rig level test methodology to validate and to correlate the CAE derived strain levels, life cycle & failure mode of newly developed light weight stabilizer link for EV Bus suspension

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.

The “Rigidization-on-Command”™ (ROC™) resin development has focused on the development of resin systems that use UV light cure for rigidization. Polymeric sensitizers have been incorporated into the resin formulations to promote cure using Pen-Ray lamps and UV light-emitting diodes (LED's). Formulations containing the polymeric sensitizers were examined by FTIR and DSC. Complete cure was observed after 15 min. exposure with the Pen-Ray lamps. Performance of the Pen-Ray lamps and UV LEDs was thoroughly characterized. Thermal models were developed to optimize the performance of the of the MLI insulation thermal oven used for orbital cure of the boom. Results show that -12°C is the lowest temperature required for cure of the ROC™ resin systems.

This paper describes the engine design details of the Pratt & Whitney JT15D-1 engine as related to noise generation. Design principles and factors contributing to the very low-noise levels on the Cessna Citation aircraft are illustrated. Noise testing experiences and data from static tests on the United Aircraft of Canada Ltd. (UACL) flight test aircraft and from both static and flight tests on the Citation aircraft are discussed. Lessons learned from these tests and some future probabilities are outlined.

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 ability to carry cargo efficiently in passenger aircraft has influenced airline economics to the point that optimisation of the freight capacity is mandatory. This document discusses the alternative loading possibilities in defined Lover Deck Compartments and their doors to cater for current and future trends in ULD dimensions. As a result items for study centred on: 1) Optimisation of the available volumes Freight capacity resulting in the selection of “Pallets”-doors for both the Forward and AFT Compartments. Flexibility to meet Freight and Baggage requirements. Possible load arrangements to optimize aircraft C of G 2) Bulk Cargo Compartment Additional LD3 Container position in AFT/Bulk compartment to cater for an uneven number of Baggage container, allowing the carriage of an additional pallet. What is regarded as an optimum is presented.

Presented in this paper is a brief review of momentum exchange theory for Jet Noise Suppression. “Experimental Results from Scale Model Tests” are included. These data exhibit peak to peak attenuation of 20 db along maximum exhaust noise azimuths at a nozzle pressure ratio of 3.1.

Engineers doing squeak and rattle testing of instrument panels (IP's) have successfully used large electrodynamic vibration systems to identify sources of squeaks and rattles (S&R's). Their successes led to demands to test more IP's, i.e., to increase throughput of IP's to reflect the many design, material, and/or manufacturing process changes that occur, and to do so at any stage of the development, production, or QA process. What is needed is a radically different and portable way to find S&R's in a fraction of the time and at lower capital cost without compromising S&R detection results.

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.

This paper describes the application of statistical techniques known as Design of Experiments (D.O.E.) to efficiently use the results of numerical analysis data in order to improve the configuration of automotive systems. The general framework of these techniques is presented in a format aiming at the design engineer as their end user. Besides, a case study is presented with the purpose of illustrating their practical use. The first step of the case study is to build predictive models for the behaviour of the automotive system being developed by means of the Response Surface Method (RSM), using the proper D.O.E. options. Once these predictive models are available, automatic numerical optimization algorithms are used to improve the responses of interest for given operating conditions. Finally, the automotive systems are robust designed taking into account that the operating conditions vary randomly.

Over the last ten years there has been a steady growth in the market share of light-duty diesel engines, especially in Europe. At the same time, a general trend in petrol engine development has been seen, in which normal aspirated engines are being replaced by downsized turbocharged engines. Therefore, NVH engineers have to deal with new challenges. Turbochargers produce an aerodynamic noise in the frequency range above 1000Hz, which might influence the exterior and interior noise level. As a result, the additional requirement for acoustical components to reduce this flow noise is going to pose an increasing challenge for air intake system suppliers. This paper describes a new design of well-known wide band silencer first mentioned by A. Selamet, N.S.Dickey and J.M.Novak [1,2]. The silencer works according to the interference principle. The sound is guided into two or more parallel pipes of different lengths.

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.

Plug-in Hybrid Electric Vehicles (PHEVs) use electric energy from the grid rather than fuel energy for most short trips, therefore drastically reducing fuel consumption. Different configurations can be used for PHEVs. In this study, the parallel pre-transmission, series, and power-split configurations were compared by using global optimization. The latter allows a fair comparison among different powertrains. Each vehicle was operated optimally to ensure that the results would not be biased by non-optimally tuned or designed controllers. All vehicles were sized to have a similar all-electric range (AER), performance, and towing capacity. Several driving cycles and distances were used. The advantages of each powertrain are discussed.

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).

Design of a Cabin Tilting System of heavy trucks, a multi degree of freedom mechanism, is a challenge. Factors like adequate tilting angle, cabin styling, packaging, non interference of tilting system with ride comfort, forces in the system, specifications of the hydraulic system, are all very important for designing the system. Numerous considerations make the design process highly iterative hence longer design time. This paper primarily focuses on Kinematics and Dynamic analysis of the system in ADAMS and validation of system with real time testing results. Intention of this work is to make a parametric ADAMS model and link it to a Knowledge Based Engineering application to facilitate designer to quickly carry out design iterations for reducing development time. The Knowledge Based Engineering software is made using object oriented language called ‘Object Definition Language’ which has been developed using C and C++ software languages.

In today’s Automotive world, there is NO need to advocate “Light weighting”. Government policies for carbon footprint reduction combined with high safety standards are driving OEMs to adopt advanced manufacturing technologies. Steel hot forming is selected as most preferred way to reduce weight as it is easy to adopt and commercially known. It had many advantages compare to conventional cold stamping of standard and high tensile steel. The process consists of heating blank to nearly 1000 °C and quenching it in tool to for martensitic structure. Higher strength up to 2000 MPa can be achieved by this process. There are many examples where part weight is reduced by 15 to 20 % by this method. But Steel hot forming has limitation as specific density of steel is still high. Thus, there is limitation to its weight reduction capability. For further reduction, OEMs have started exploring Aluminium hot forming.

‘Emotional controlling’ is a very efficient way to realize autonomous behaviour of digital human models by closed loop controls. In particular this is an emotional optimization procedure based upon the ‘Hedonic principle’ and thus following closely the human original. Emotional controlling will be outlined and illustrated by an example demonstrating the specific way force and posture induced discomfort is shaping our movements.