The Object Management Group's (OMG) Model Driven Architecture (MDA) strategy envisages a world where models play a more direct role in software production, being amenable to manipulation and transformation by machine. Model Driven Engineering (MDE) is wider in scope than MDA. MDE combines process and analysis with architecture. This article sets out a framework for model driven engineering, which can be used as a point of reference for activity in this area. It proposes an organisation of the modelling 'space' and how to locate models in that space. It discusses different kinds of mappings between models. It explains why process and architecture are tightly connected. It discusses the importance and nature of tools. It identifies the need for defining families of languages and transformations, and for developing techniques for generating/configuring tools from such definitions. It concludes with a call to align metamodelling with formal language engineering techniques.

Model Driven Engineering

Developing on-board automotive driver assistance systems aiming to alert drivers about driving environments, and possible collision with other vehicles has attracted a lot of attention lately. In these systems, robust and reliable vehicle detection is a critical step. This paper presents a review of recent vision-based on-road vehicle detection systems. Our focus is on systems where the camera is mounted on the vehicle rather than being fixed such as in traffic/driveway monitoring systems. First, we discuss the problem of on-road vehicle detection using optical sensors followed by a brief review of intelligent vehicle research worldwide. Then, we discuss active and passive sensors to set the stage for vision-based vehicle detection. Methods aiming to quickly hypothesize the location of vehicles in an image as well as to verify the hypothesized locations are reviewed next. Integrating detection with tracking is also reviewed to illustrate the benefits of exploiting temporal continuity for vehicle detection. Finally, we present a critical overview of the methods discussed, we assess their potential for future deployment, and we present directions for future research.

/pdf/on-road-vehicle-detection-a-review-4iw469j6iz.pdf

On-road vehicle detection: a review

This paper formulates a general analytic approach to the theory of microwave generation in magnetic nano-structures driven by spin-polarized current and reviews analytic results obtained in this theory. The proposed approach is based on the universal model of an auto-oscillator with negative damping and nonlinear frequency shift. It is demonstrated that this universal model, when applied to the case of a spin-torque oscillator (STO) based on a current-driven magnetic nano-pillar or nano-contact, gives adequate description of most of the experimentally observed properties of STO. In particular, the model describes the power and frequency of the generated microwave signal as functions of the bias current and magnetic field, predicts the magnitude and properties of the generation linewidth, and explains the STO behavior under the influence of periodic and stochastic external signals: frequency modulation, phase-locking to external signals, mutual phase-locking in an array of STO, broadening of the generation linewidth near the generation threshold, etc. The proposed nonlinear auto-oscillator theory is rather general and can be used not only for the development of practical nano-sized STO, but, also, for the description of nonlinear auto-oscillating systems of any physical nature.

Nonlinear Auto-Oscillator Theory of Microwave Generation by Spin-Polarized Current

Introductory Fourier transform spectroscopy

Within the field of spectral imaging, the vast majority of instruments used are scanning devices. Recently, several snapshot spectral imaging systems have become commercially available, providing new functionality for users and opening up the field to a wide array of new applications. A comprehensive survey of the available snapshot technologies is provided, and an attempt has been made to show how the new capabilities of snapshot approaches can be fully utilized.

https://www.spiedigitallibrary.org/journals/optical-engineering/volume-52/issue-9/090901/Review-of-snapshot-spectral-imaging-technologies/10.1117/1.OE.52.9.090901.pdf

Review of snapshot spectral imaging technologies

Wavelet transforms are currently being used for a number of applications such as cue feature and noise extraction from images and acoustic signals. This work describes and applies an algorithm that uses wavelets for finding the clutter in infrared (IR) and visual images. Once the clutter is found, the probability of detection (Pd) is calculated. Tidhar’s and Rotman’s probability of edge metric (POE) is extended to encompass the wavelet methodology for multiscale clutter metrics in IR images.

Wavelet transforms of cluttered images and their application to computing the probability of detection

We present our research efforts toward the deployment of 3-D sensing technology to an under-vehicle inspection robot. The 3-D sensing modality provides flexibility with ambient lighting and illumination in addition to the ease of visualization, mobility, and in- creased confidence toward inspection. We leverage laser-based range-imaging techniques to reconstruct the scene of interest and address various design challenges in the scene modeling pipeline. On these 3-D mesh models, we propose a curvature-based surface feature toward the interpretation of the reconstructed 3-D geometry. The curvature variation measure (CVM) that we define as the en- tropic measure of curvature quantifies surface complexity indicative of the information present in the surface. We are able to segment the digitized mesh models into smooth patches and represent the automotive scene as a graph network of patches. The CVM at the nodes of the graph describes the surface patch. We demonstrate the descriptiveness of the CVM on manufacturer CAD and laser-

https://imaging.utk.edu/publications/papers/2006/231_JEI06_ss.pdf

Robotic three-dimensional imaging system for under-vehicle inspection

The TARDEC Intelligent Mobility program addresses several essential technologies necessary to support the army after next (AAN) concept. Ground forces in the AAN time frame will deploy robotic unmanned ground vehicles (UGVs) in high-risk missions to avoid exposing soldiers to both friendly and unfriendly fire. Prospective robotic systems will include RSTA/scout vehicles, combat engineering/mine clearing vehicles, indirect fire artillery and missile launch platforms. The AAN concept requires high on-road and off-road mobility, survivability, transportability/deployability and low logistics burden. TARDEC is developing a robotic vehicle systems integration laboratory (SIL) to evaluate technologies and their integration into future UGV systems. Example technologies include the following: in-hub electric drive, omni-directional wheel and steering configurations, off-road tires, adaptive tire inflation, articulated vehicles, active suspension, mine blast protection, detection avoidance and evasive maneuver. This paper will describe current developments in these areas relative to the TARDEC intelligent mobility program.

Intelligent mobility for robotic vehicles in the army after next

For the past several years the U.S. Army Tank-Automotive Command (TACOM) has sponsored the development of computer models to simulate the thermal signature of concept vehicles. The entire simulation process involves the prediction of target and background temperatures, creation of the 3-D graphics database, and the addition of atmospheric and sensor effects to produce a simulated infrared or thermal image. This paper also describes the model integration necessary to create thermal signature animations for concept vehicles. Each model is described in some detail along with the appropriate interface to the other thermal models.

A Comprehensive Methodology For Thermal Signature Simulation Of Targets And Backgrounds

There has been an increasing interest of unmanned vehicles keeping the importance of defense and security. A few
models for a convoy of unmanned vehicle exist in literature. The objective of this paper is to exploit agent based
modeling technique for a convoy of unmanned vehicles where each vehicle is an agent. Using this approach, the convoy
of vehicles reaches a specified goal from a starting point. Each agent is associated with number of sensors. The agents
make intelligent decisions based on sensor inputs and at the same time maintaining their group capability and behavior.
The simulation is done for a battlefield environment from a single starting point to a single goal. This approach can be
extended for multiple starting points to reach multiple goals. The simulation gives the time taken by the convoy to reach
a goal from its initial position. In the battlefield environment, commanders make various tactical decisions depending
upon the location of an enemy outpost, minefields, number of soldiers in platoons, and barriers. The simulation can help
the commander to make effective decisions depending on battlefield, convoy and obstacles to reach a particular goal.
The paper describes the proposed approach and gives the simulation results. The paper also gives problems for future
research in this area.

Grant R. Gerhart

Papers

Wavelet transforms of cluttered images and their application to computing the probability of detection

Robotic three-dimensional imaging system for under-vehicle inspection

Intelligent mobility for robotic vehicles in the army after next

A Comprehensive Methodology For Thermal Signature Simulation Of Targets And Backgrounds

Simulation of convoy of unmanned vehicles using agent based modeling