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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.

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.

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.

Mathematical modeling and control of artificial ecosystems, such as MELISSA, require first the study of physical and biological characteristics in optimal and limiting conditions. Following the previous determination of the stoichiometric equations (Spirulina compartment) and regarding the two phototrophic compartments of MELISSA (Rhodospirillaceae and Spirulina), we have first to focus our control study on the growth kinetics for the light source. In this paper, we recall the theoretical equations of microbial growth kinetics and emphasise the problem of the light transfer in a photobioreactor. We present their adaptations to our pilot plant taking into account technological and biological specifics (lamp spectrum, working illuminated volume, growth rate,…). We then develop the principles and structure of the control system and describe tests of both the hardware and software for several steady state configurations.

This paper describes the interrelated controls for automatic start sequencing, fuel scheduling, customer air delivery, and supervisory and protective systems as applied to the Curtiss-Wright CW657E “Jet-Air” Compressor. Model CW657E is capable of delivering 15,000 SCFM air at 85 psig (at 30°F and sea level pressure) and may be used in a diversity of manufacturing, processing, and industrial applications. A description of the control system and its operation in relation to compressor requirements, while furnishing air to feed distribution lines to air assisted water atomizing nozzles for snow making is reviewed as an example. Other models can deliver up to 30,000 SCFM with modified control systems, including pressure controls.

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.

This paper discusses the use of electromechanical devices as the kinematic portions of a microprocessor based gas turbine control system. Specific applications are: 1. An electric motor driven, positive displacement pump, which provides metered high pressure fuel to the distribution manifold. Fuel metering to be provided by varying the motor angular velocity. 2. An electric motor driven lube oil pump. 3. Electromechnical actuators for motion and control of compressor and power turbine variable geometry. 4. A starter/generator integral with the gas generator. Topics covered include: Comparison to conventional hydro-mechanical systems. Response characteristics of the fuel pump and actuator systems. Brushless D.C. motor characteristics. Power electronics requirements for brushless D.C. motors. Control electronics interface with brushless D.C. motor systems. Reliability and maintainability issues. Diagnostic/prognostic enhancements.

As a typical parameter of the road-vehicle interface, the road friction potential acts an important factor that governs the vehicle motion states under certain maneuvering input, which makes the prior knowledge of maximum road friction capacity crucial to the vehicle stability control systems. Since the direct measure of the road friction potential is expensive for vehicle active safety system, the evaluation of this variable by cost effective method is becoming a hot issue all these years. A ‘wheel slip based’ maximum road friction coefficient estimation method based on a modified Dugoff tire model for distributed drive electric vehicles is proposed in this paper. It aims to evaluate the road friction potential with vehicle and wheel dynamics analyzing by using standard sensors equipped on production vehicle, and fully take the advantage of distributed EV that the wheel drive torque and rolling speed can be obtained accurately.

Vehicle relationship management (vRM) is a means to use data generated from embedded in-vehicle telematics systems to re-define the customer relationship between a vehicle owner and the owner's carmaker and dealer. This ability to tap the vehicle for real-time data offers potential to provide both OEM and dealership with enhanced customer retention and brand loyalty, increased revenue, greater lifetime value of customers, and cost reduction. vRM also involves the return on OEM investment in telematics hardware than currently provided through telematics business models based solely on the sale of annual subscriptions for location-based services.

Abstract With the adoption of Vehicle-to-everything (V2X) technology, security and privacy of vehicles are paramount. To avoid tracking while preserving vehicle/driver’s privacy, modern vehicular public key infrastructure provision vehicles with multiple short-term pseudonym certificates. However, provisioning a large number of pseudonym certificates can lead to an enormous growth of Certificate Revocation Lists (CRLs) during its revocation process. One possible approach to avoid such CRL growth is by relying on activation code (AC)-based solutions. In such solutions, the vehicles are provisioned with batches of encrypted certificates, which are decrypted periodically via the ACs (broadcasted by the back-end system). When the system detects a revoked vehicle, it simply does not broadcast the respective vehicle’s AC. As a result, revoked vehicles do not receive their respective AC and are prevented from decrypting their certificates.

eROSITA (extended ROentgen Survey with an Imaging Telescope Array) is a powerful X-ray telescope under development by the Max-Planck-Institut für extraterrestrische Physik (MPE) in Garching, Germany. eROSITA is the core instrument on the Russian SRG1 mission which is planned for launch in 2011. It comprises seven nested Wolter-I grazing incidence telescopes, each equipped with its own CCD camera. The mirror modules have to be maintained at 20°C while the cameras are operated at -80°C. Both, mirrors and CCDs have to be kept within tight limits. The CCD cooling system consists of passive thermal control components only: two radiators, variable conductance heat pipes (VCHP) and two special thermal storage units. The orbit scenario imposes severe challenges on the thermal control system and also on the attitude control system.

With the increase in demand for energy sustainability projects over the last few years, the Brazilian commercial vehicle industry was guided to develop projects based on ESG policies. Aligned with this need, an initiative that ended up becoming a reality was the “e-Sys” electrification solution, by the company Suspensys. This solution includes a power source (battery), an e-powertrain (motors, inverters and drive axle) and an intelligent control system (VCU with embedded code and sensors). The main motivational drive was the hybridization of semi-trailers, in order to generate a reduction in fuel consumption in cargo transport in Brazil, in addition to the consequent reduction in the emission of particles into the environment and promoting the safety of the operation. It was also adopted, as a premise of the project, that the electrification system was totally independent of the truck’s electronic system (stand alone system), in order to facilitate the operation of the fleet owner.

Energy Development Associates, a division of Gulf+Western Industries, Inc., has undertaken the design and fabrication of a four-passenger electric car incorporating state-of-the art zinc-chloride battery technology. The purpose of the project is to demonstrate the viability of the zinc-chloride energy storage system as a practical alternative to cars powered by internal combustion engines. Significant among the project goals to be achieved is the attainment of a vehicle range three to four times that of current lead-acid battery-powered vehicles on a single battery charge. Progress to date on the project is discussed. It includes the design, specification, and fabrication of the battery, vehicle and its components, motor control system, and battery control microprocessor.

Recent developments in the commercialization of mobility services have brought unprecedented connectivity to the automotive sector. While the adoption of connected features provides significant benefits to vehicle owners, adversaries may leverage zero-day attacks to target the expanded attack surface and make unauthorized access to sensitive data. Protecting new generations of automotive controllers against malicious intrusions requires solutions that do not depend on conventional countermeasures, which often fall short when pitted against sophisticated exploitation attempts. In this paper, we describe some of the latent risks in current automotive systems along with a well-engineered multi-layer defense strategy. Further, we introduce a novel and comprehensive attack and performance test framework which considers state-of-the-art memory corruption attacks, countermeasures and evaluation methods.

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Yield potential was predicted and mapped for three corn fields in Central Illinois, using digital aerial color infrared images. Three methods, namely statistical (regression) modeling, genetic algorithm optimization and artificial neural networks, were used for developing yield models. Two image resolutions of 3 and 6 m/pixel were used for modeling. All the models were trained using July 31 image and tested using images from July 2 and August 31, all from 1998. Among the three models, artificial neural networks gave best performance, with a prediction error less than 30%. The statistical model resulted in prediction errors in the range of 23 to 54%. The lower resolution images resulted in better prediction accuracy compared to resolutions higher than or equal to the yield resolution. Images after pollination resulted in better accuracy compared to images before pollination.

From the beginning of 1995 on, RB will start the production of the Vehicle Dynamics Control System. A key part of this system is the Yaw Rate Sensor described in this paper. The basic requirements for this sensor for automotive applications are: mass producibility, low cost, resistance against environmental influences (such as temperature, vibrations, EMI), stability of all characteristics over life time, high reliability and designed-in safety. Bosch developed a sensor on the basis of the “Vibrating Cylinder”. The sensor will be introduced into mass production in beginning of 1995.