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Viewing 1 to 30 of 1722
2017-09-23
Technical Paper
2017-01-1967
Wei Liu, Huan Tian, Jun Hu, Shuai Cheng, Huai Yuan
Abstract Image segmentation is critical in autonomous driving field. It can reveal essential clues such as objects’ shape or boundary information. The information, moreover, can be leveraged as input information of other tasks: vehicle detection, for example, or vehicle trajectory prediction. SegNet, one deep learning based segmentation model proposed by Cambridge, has been a public baseline for scene perception tasks. It, however, suffers an accuracy deficiency in objects marginal area. Segmentation of this area is very challenging with current models. To alleviate the problem, in this paper, we propose one edge enhanced deep learning based model. Specifically, we first introduced one simple, yet effective Artificial Interfering Mechanism (AIM) which feeds segmentation model manual extracted key features. We argue this mechanism possesses the ability to enhance essential features extraction and hence, ameliorate the model performance.
2017-09-23
Technical Paper
2017-01-1997
Cui Hua
Abstract Vision based driving environment perception is current research hotspot in automatic driving field, which has made great progress due to the continuous breakthroughs in the research of deep neural network. As is well known, deep neural network has won tremendous successes in a wide variety of image recognition tasks, such as pedestrian detection and vehicle identification, which have accomplished the commercialization successfully in intelligent monitor system. Nevertheless, driving environment perception has a higher request for the generalization performance of deep neural network, which needs further studies on its design and training methods. In this paper, we presented a new boosted deep neural network in order to improve its generalization performance and meanwhile keep computational budget constant. Above all, the most representative methods to improve the generalization performance of deep neural network were introduced.
2017-09-23
Technical Paper
2017-01-2005
Zhihong Wu, Jian_ning Zhao, Yuan Zhu, Qingchen Li
Abstract Vehicle cybersecurity consists of internal security and external security. Dedicated security hardware will play an important role in car’s internal and external security communication. TPM (Trusted Platform Module) can serve as the security cornerstone when vehicle connects with external entity or constructs a trusted computing environment. Based on functions such as the storage of certificate, key derivation and integrity testing, we research the principle of how to construct a trusted environment in a vehicle which has telematics unit. HSM (Hardware Security Module) can help to realize the onboard cryptographic communication securely and quickly so as to protect data. For certain AURIX MCU consisting of HSM, the experiment result shows that cheaper 32-bit HSM’s AES calculating speed is 25 times of 32-bit main controller, so HSM is an effective choice to realize cybersecurity.
2017-09-23
Technical Paper
2017-01-2007
Fang Li, Lifang Wang, Yan Wu
Abstract With the rapid development of vehicle intelligent and networking technology, the IT security of automotive systems becomes an important area of research. In addition to the basic vehicle control, intelligent advanced driver assistance systems, infotainment systems will all exchange data with in-vehicle network. Unfortunately, current communication network protocols, including Controller Area Network (CAN), FlexRay, MOST, and LIN have no security services, such as authentication or encryption, etc. Therefore, the vehicle are unprotected against malicious attacks. Since CAN bus is actually the most widely used field bus for in-vehicle communications in current automobiles, the security aspects of CAN bus is focused on. Based on the analysis of the current research status of CAN bus network security, this paper summarizes the CAN bus potential security vulnerabilities and the attack means.
2017-09-19
Journal Article
2017-01-2018
Won Il Jung, Larry Lowe, Luis Rabelo, Gene Lee, Ojeong Kwon
Abstract Operator training using a weapon in a real-world environment is risky, expensive, time-consuming, and restricted to the given environment. In addition, governments are under intense scrutiny to provide security, yet they must also strive for efficiency and reduce spending. In other words, they must do more with less. Virtual simulation, is usually employed to solve these limitations. As the operator is trained to maximize weapon effectiveness, the effectiveness-focused training can be completed in an economical manner. Unfortunately, the training is completed in limited scenarios without objective levels of training factors for an individual operator to optimize the weapon effectiveness. Thus, the training will not be effective. For overcoming this problem, we suggest a methodology on guiding effectiveness-focused training of the weapon operator through usability assessments, big data, and Virtual and Constructive (VC) simulations.
2017-09-19
Technical Paper
2017-01-2121
Greg Parlier
The US Department of Defense (DoD) operates the most complex global supply chain in the world. However, effectively integrating production planning, maintenance operations, inventory systems, and distribution policies has been a persisting strategic challenge for the logistics enterprise supporting the DoD. Neither DoD nor the Congressional Budget Office has been able to establish a well-defined linkage between Operations and Maintenance resource funding levels and the resulting readiness of military units. For nearly three decades the Government Accountability Office has attributed these inadequacies to poor demand forecasting, ineffective inventory management, and inadequate strategic planning. To address these persisting problems the US Army established the project to Transform Army Supply Chains (TASC) in order to investigate the nature, causes, and consequences of demand uncertainty and supply variability.
2017-09-04
Technical Paper
2017-24-0054
Francesco de Nola, Giovanni Giardiello, Alfredo Gimelli, Andrea Molteni, Massimiliano Muccillo, Roberto Picariello
Abstract In the last few years, the automotive industry had to face three main challenges: compliance with more severe pollutant emission limits, better engine performance in terms of torque and drivability and simultaneous demand for a significant reduction in fuel consumption. These conflicting goals have driven the evolution of automotive engines. In particular, the achievement of these mandatory aims, together with the increasingly stringent requirements for carbon dioxide reduction, led to the development of highly complex engine architectures needed to perform advanced operating strategies. Therefore, Variable Valve Actuation (VVA), Exhaust Gas Recirculation (EGR), Gasoline Direct Injection (GDI), turbocharging, powertrain hybridization and other solutions have gradually and widely been introduced into modern internal combustion engines, enhancing the possibilities of achieving the required goals.
2017-09-04
Technical Paper
2017-24-0068
Roberto Finesso, Ezio Spessa, Yixin Yang, Giuseppe Conte, Gennaro Merlino
Abstract A real-time approach has been developed and assessed to control BMEP (brake mean effective pressure) and MFB50 (crank angle at which 50% of fuel mass has burnt) in a Euro 6 1.6L GM diesel engine. The approach is based on the use of feed-forward ANNs (artificial neural networks), which have been trained using virtual tests simulated by a previously developed low-throughput physical engine model. The latter is capable of predicting the heat release and the in-cylinder pressure, as well as the related metrics (MFB50, IMEP - indicated mean effective pressure) on the basis of an improved version of the accumulated fuel mass approach. BMEP is obtained from IMEP taking into account friction losses. The low-throughput physical model does not require high calibration effort and is also suitable for control-oriented applications.
2017-09-04
Journal Article
2017-24-0051
Ferdinando Taglialatela, Mario Lavorgna, Silvana Di Iorio, Ezio Mancaruso, Bianca Maria Vaglieco
Abstract In order to meet the increasingly strict emission regulations, several solutions for NOx and PM emissions reduction have been studied. Exhaust gas recirculation (EGR) technology has become one of the more used methods to accomplish the NOx emissions reduction. However, actual control strategies do not consider, in the definition of optimal EGR, its effect on particle size and density. These latter have a great importance both for the optimal functioning of after-treatment systems, but also for the adverse effects that small particles have on human health. Epidemiological studies, in fact, highlighted that the toxicity of particulate particles increases as the particle size decreases. The aim of this paper is to present a Neural Network model able to provide real time information about the characteristics of exhaust particles emitted by a Diesel engine.
2017-08-24
Magazine
On-Orbit Satellite Refueling Flow Measurement The Path from Concept to Operational Status Radiation Tolerant "Smart Backplanes" for Spacecraft Avionics Using Heat Pipes to Cool Embedded Computers Electronically Dimmable Aircraft Windows How do you block the light of the sun? Eliminating Electrical Arcing in Satellite Systems NASA Miniaturizes Century-Old Radio Sounder Technology Developing an Airborne Optical Systems Testbed (AOSTB) New Class of Excimer-Pumped Atomic Lasers (XPALS) Research demonstrates the viability of an atomic laser having a quantum efficiency greater than one. Hydrodynamic Drag Force Measurement of a Functionalized Surface Exhibiting Superhydrophobic Properties Comparing the skin friction drag effects of a superhydrophobic flat plate to an untreated flat plate of the same material and geometry.
2017-08-04
Magazine
Opposed-piston engines: the powerplant of the future India's dream of an all-EV fleet by 2030: Myth, miracle, or reality? An approach for prediction of motorcycle engine noise under combustion load Innovations for lightweighting Tough U.S. fuel-economy bogies for 2021 and beyond are driving new approaches for materials, as seen in these examples. More intelligence equals more efficiency, enhanced functionality Advanced electronic systems require renewed focus on architectures, processors, sensors and networks. Connected commercial vehicles bring cybersecurity to the fore Connectivity, automation and electrification will drive vehicle development in the near future, say industry experts attending the revamped SAE COMVEC 17 event.
2017-08-03
Magazine
Hacked! Is automotive ready for the inevitable? Cybersecurity experts talk defense strategies. Active Aero takes flight Reconfigurable "smart" aerodynamic aids are stretching performance-car envelopes in every direction. The motorcycle's balanced future With its Ride Assist technology, Honda R&D moves two-wheelers toward autonomous capability. Honoring lightweight innovation Chrysler, Toyota, Faurecia and AP&T recognized with the 2017 Altair Enlighten Award for their efforts to reduce vehicle weight.
2017-08-03
Magazine
Collaborating on diesel emission control Stringent fuel-efficiency and criteria-pollutant standards call for new combustion strategies. The SwRI-led Advanced Combustion Catalyst and Aftertreatment Technologies consortium reinvents existing technologies and experiments with new catalysts to meet standards. More intelligence equals more efficiency, enhanced functionality Advanced systems require renewed focus on architectures, processors, sensors and networks. Appraising the potential for platooning in the U.S. Researchers from the National Renewable Energy Laboratory perform statistical analysis based on a large collection of real-world U.S. truck usage data to estimate the fraction of total miles that are technically suitable for platooning. Connected commercial vehicles bring cybersecurity to the fore Connectivity, automation and electrification will largely drive vehicle developments in the coming years, according to experts presenting at the revamped SAE COMVEC 17.
2017-07-27
Magazine
The Rapid Rise of Beryllium-Aluminum Alloys in Aerospace Aeroacoustic Simulation Delivers Breakthroughs in Aircraft Noise Reduction Using System Simulation to Manage Increasing Thermal Loads on Aircraft Fuel Systems Ensuring the Compliance of Avionics Software with DO-178C Microwave Photonic Notch Filter Helps Ensure Critical Mission Success Measuring Propellant Stress Relaxation Modulus Using Dynamic Mechanical Analyzer New testing technique requires less material, gives more accurate results. Combustion Characteristics of Hydrocarbon Droplets Induced by Photoignition of Aluminum Nanoparticles Test methodology allows analysis of combustion dynamics for subscale rocket injectors under super critical conditions. Vapor Pressure Data and Analysis for Selected Organophosphorous Compounds: DIBMP, DCMP, IMMP, IMPA, EMPA, and MPFA Determining the thermophysical properties of chemical warfare agent simulants can help evaluate the performance of defensive equipment.
2017-06-05
Technical Paper
2017-01-1904
Tan Li, Ricardo Burdisso, Corina Sandu
Abstract Tire-pavement interaction noise (TPIN) is a dominant source for passenger cars and trucks above 40 km/h and 70 km/h, respectively. TPIN is mainly generated from the interaction between the tire and the pavement. In this paper, twenty-two passenger car radial (PCR) tires of the same size (16 in. radius) but with different tread patterns were tested on a non-porous asphalt pavement. For each tire, the noise data were collected using an on-board sound intensity (OBSI) system at five speeds in the range from 45 to 65 mph (from 72 to 105 km/h). The OBSI system used an optical sensor to record a once-per-revolution signal to monitor the vehicle speed. This signal was also used to perform order tracking analysis to break down the total tire noise into two components: tread pattern-related noise and non-tread pattern-related noise.
2017-05-25
Magazine
Small Form Factor Embedded Systems New Technologies Drive Diverse Solutions Making Laser Weapons a Reality Modelling and Simulation Tools for Systems Integration on Aircraft Rotorcraft Anti-Icing Systems Redundant Transmitting System in Aircraft (RTSA) Cassini Stays in Touch with NASA's Radio Science Subsystem Laser Integration on Silicon Photonic Circuits Through Transfer Printing New fabrication approach allows the massively parallel transfer of III-V coupons to a silicon photonic target wafer. High Energy Computed Tomographic Inspection of Munitions Inspection system provides additional level of quality assurance for R&D, reverse engineering, and malfunction investigations. Terahertz (THz) Radar: A Solution for Degraded Visibility Environments (DVE) Operating at higher frequencies than other types of radar produces tighter beams and finer resolution. Imaging Detonations of Explosives Using high-speed camera pyrometers to measure and map fireball/shock expansion velocities.
CURRENT
2017-05-09
Standard
EIASTD4899C
This document applies to the development of Plans for integrating and managing electronic components in equipment for the military and commercial aerospace markets; as well as other ADHP markets that wish to use this document. Examples of electronic components, as described in this document, include resistors, capacitors, diodes, integrated circuits, hybrids, application specific integrated circuits, wound components, and relays. It is critical for the Plan owner to review and understand the design, materials, configuration control, and qualification methods of all “as-received” electronic components, and their capabilities with respect to the application; identify risks, and where necessary, take additional action to mitigate the risks. The technical requirements are in Clause 3 of this standard, and the administrative requirements are in Clause 4.
2017-05-04
Magazine
Innovations for lightweighting Tough fuel-economy bogies for 2021 and beyond are driving new approaches to materials use, as seen in these case studies. Axellent progress AAM's new Quantum drive-axle technology is a leap forward in lightweight, efficient driveline systems aimed at 2020 and beyond. Low-temperature combustion ready for prime time? At SAE's High-Efficiency IC Engines Symposium, Delphi said its new, third-generation GDCI is promising, but even LTC proponents admit that challenges remain. More automation for ECU testing The latest fault-insertion tests enable engineers to run more test cases in less time.
2017-04-27
Magazine
Interoperability Standards Pave the Way for Modular Robotic Manipulators Solar Powering UAVs Deploying COTS Subsystems in UUVs Developing a Multi-Modal UGV Robot Control Interface Fast-Tracking Autonomous Vehicles with Simulation Gesture-Based Controls for Robots: Overview and Implications for Use by Soldiers Identifying the Flow Physics and Modeling Transient Forces on Two-Dimensional Wings Experimental Confirmation of an Aquatic Swimming Motion Theoretically of Very Low Drag and High Efficiency The Scaling of Loss Pathways and Heat Transfer in Small Scale Internal Combustion Engines A Guide for Developing Human-Robot Interaction Experiments in the Robotic Interactive Visualization and Experimentation Technology (RIVET) Simulation
2017-04-14
WIP Standard
STD0016A
This document defines the requirements for developing a DMSMS Management Plan, hereinafter also called the Plan, to assure customers that the Plan owner is using a proactive DMSMS process for minimizing the cost and impact that part and material obsolescence will have on equipment delivered by the Plan owner. The technical requirements detailed in clause 5 ensure that the Plan owner can meet the requirement of having a process to address obsolescence as required by Industry Standards such as EIA-4899 "Standard for Preparing an Electronic Components Management Plan" and DoD Programs as required by MIL-STD-3018 "Parts Management". Owners of DMSMS Management Plans include System Integrators, Original Equipment Manufacturers (OEM), and logistics support providers.
2017-04-06
Magazine
Connectivity continues its advance More OEMs and Tier 1 suppliers are focusing on embedded telematic systems, hoping to displace aftermarket hardware. Tailoring fuel injection to control NOx The next big step to help heavy-duty diesel engines meet stricter emissions regulations involves adapting the fuel-injection system to the combustion needs. Active on safety Crash-avoidance technologies are vital "building blocks" to automate commercial vehicles, implement truck platooning and ultimately achieve zero accidents. Engineering with simulation and data Companies are discovering new simulation techniques, especially optimization; the next step is to combine simulation with sensor data and predictive analytics to create even more robust off-highway equipment.
2017-03-28
Technical Paper
2017-01-1726
Sameer Shah, Aayoush Sharma, Raghav Angra, Nitin Singh, Khalique Ahmed
Abstract In an unavoidable event of a suspect being chased by police, there is high probability for the criminal to evade the police while driving his vehicle. At many instances, criminal escapes without leaving a trail behind and becomes untraceable. A new concept of Vigilance Assistance System Network (VASN) has been developed, which is spread across the city and helps in catching the escaping criminals. At every junction, the traffic-signals are installed with a microcontroller chip and these connected traffic signals form a network with distinct city areas demarcated on the map. The vehicle is installed with GPS and a RFID module on their ECU when it approaches any intersection or junction; they receive wireless signals from traffic-signals and transmit another registering signal to the traffic-light wirelessly through RFID.
2017-03-28
Technical Paper
2017-01-0092
Vladimir Hahanov, Wajeb Gharibi, Eugenia Litvinova, Svitlana Chumachenko, Arthur Ziarmand, Irina Englesi, Igor Gritsuk, Vladimir Volkov, Anastasiia Khakhanova
Abstract The new cyber-technological culture of the transport control based on virtual road signs and streetlight signals on the screen of car is the future of Humanity. A cyber-physical system (CPS) Smart Cloud Traffic Control, which realizes the mentioned culture, is proposed; it is characterized by the presence of the digitized regulatory rules, vehicles, infrastructure components, and also accurate monitoring, active cloud streetlight-free cyber control of road users, traffic lights, automatic output of operational regulatory actions (virtual traffic signs and traffic signals) to monitor of each vehicle. The main components of the cyber-physical system are the following: infrastructure, road users and rules, which have digital representation in cyberspace to realize a route, based on digital monitoring and cloud mobile control.
2017-03-28
Technical Paper
2017-01-1428
Berkan Guleyupoglu, Ryan Barnard, F. Scott Gayzik
Abstract Computational modeling of the human body is increasingly used to evaluate countermeasure performance during simulated vehicle crashes. Various injury criteria can be calculated from such models and these can either be correlative (HIC, BrIC, etc.) or based on local deformation and loading (strain-based rib fracture, organ damage, etc.). In this study, we present a method based on local deformation to extract failed rib region data. The GHMBC M50-O model was used in a Frontal-NCAP severity sled simulation. Failed Rib Regions (FRRs) in the M50-O model are handled through element deletion once the element surpasses 1.8% effective strain. The algorithm central to the methodology presented extracts FRR data and requires 4-element connectivity to register a failure. Furthermore, the FRRs are localized to anatomical sections (Lateral, Anterior, and Posterior), rib level (1,2,3 etc.) and element strain data is recorded.
2017-03-28
Collection
Business Modeling/Operation Research/Big Data Analytics are key enablers for the next wave of innovation and growth across most industries and will address complex issues and systems that involve multiple objectives, alternatives, trade-offs, and large amounts of data and situations involving uncertainty or risk. These papers address new technical advances in these areas and provide valuable insights through the applications of real-world case studies.
2017-03-28
Collection
This papers focu on cybersecurity for cyber-physical vehicle systems. Topics include: design, development and implementation of security-critical cyber-physical vehicle systems, cybersecurity design, development, and implementation strategies, analysis methodologies, process and life-cycle management, comparisons of system safety and cybersecurity, etc. Application areas include: security-critical automotive systems as well as other security-critical ground vehicle and aviation systems.
2017-03-28
Technical Paper
2017-01-0020
Mark Zachos
Abstract Since 2001, all sensitive information of U.S. Federal Agencies has been protected by strong encryption mandated by the Federal Information Processing Standards (FIPS) 140-2 Security Requirements. The requirements specify a formal certification process. The process ensures that validated encryption modules have implemented the standard, and have passed a rigorous testing and review processes. Today, this same strong security protection has become possible for vehicle networks using modern, cost-effective encryption in hardware. This paper introduces the motivation and context for the encryption diagnostics security in terms of all vehicles in general, not just trucks which use SAE J1939 communications. Several practical scenarios for using such encryption hardware and the advantages of using hardware compared to software private-key encryption and public-key encryption are described.
2017-03-28
Technical Paper
2017-01-0099
Jose E. Solomon, Francois Charette
Abstract The proposed technique is a tailored deep neural network (DNN) training approach which uses an iterative process to support the learning of DNNs by targeting their specific misclassification and missed detections. The process begins with a DNN that is trained on freely available annotated image data, which we will refer to as the Base model, where a subset of the categories for the classifier are related to the automotive theater. A small set of video capture files taken from drives with test vehicles are selected, (based on the diversity of scenes, frequency of vehicles, incidental lighting, etc.), and the Base model is used to detect/classify images within the video files. A software application developed specifically for this work then allows for the capture of frames from the video set where the DNN has made misclassifications. The corresponding annotation files for these images are subsequently corrected to eliminate mislabels.
2017-03-28
Journal Article
2017-01-0236
Zhigang Wei, Kamran Nikbin
In the Big Data era, the capability in statistical and probabilistic data characterization, data pattern identification, data modeling and analysis is critical to understand the data, to find the trends in the data, and to make better use of the data. In this paper the fundamental probability concepts and several commonly used probabilistic distribution functions, such as the Weibull for spectrum events and the Pareto for extreme/rare events, are described first. An event quadrant is subsequently established based on the commonality/rarity and impact/effect of the probabilistic events. Level of measurement, which is the key for quantitative measurement of the data, is also discussed based on the framework of probability. The damage density function, which is a measure of the relative damage contribution of each constituent is proposed. The new measure demonstrates its capability in distinguishing between the extreme/rare events and the spectrum events.
2017-03-28
Technical Paper
2017-01-0240
Yanli Zhao, Hao Zhou, Yimin Liu
Abstract Ride Hailing service and Dynamic Shuttle are two key smart mobility practices, which provide on-demand door-to-door ride-sharing service to customers through smart phone apps. On the other hand, some big companies spend millions of dollars annually in third party vendors to offer shuttle services to pick up and drop off employees at fixed locations and provide them daily commutes for employees to and from work. Efficient fixed routing algorithms and analytics are the key ingredients for operating efficiency behind these services. They can significantly reduce operating costs by shortening bus routes and reducing bus numbers, while maintaining the same quality of service. This study developed an off-line optimization routing method for employee shuttle services including regular work shifts and demand based shifts (e.g. overtime shifts) in some regions.
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