Ontology Modeling

The ontological formula A = A + (–A₀) from Base Ontology is not a mathematical identity but a conceptual expression of dynamic tension. A represents Being, –A₀ represents Non-being or negation, and the equation signifies that any stable form exists only through interaction with its own negation. This paper explores how such an ontological relation can be visualized through a dynamic model. By interpreting the formula as a process rather than a state, we construct a qualitative function that captures the oscillatory nature of becoming, resonating with fields like quantum fluctuation, identity formation, and systemic transformation.

This paper proposes an ontology modelling approach for assisting vehicle drivers through safety warning messages during time critical situation. Intelligent Driver Assistance System (I-DAS) is a major component of InVANET[12], which focuses on generating the alert messages based on the context aware parameters such as driving situations, vehicle dynamics, driver activity and environment. I-DAS manages the parameter representation, consistent update /maintenance in XML format while the interpretation of a critical situation is done using ontology modeling. Related safety technologies such as Adaptive Cruise Control, Collision Avoidance System, Lane Departure Warning System, Driver Drowsiness detection system, Parking Assistance System, which generate warnings and alerts to driver continuously, for assistance according to context which is integrated in Vehicle and Vehicle 2 Driver (V2D) communications by DVI(Driver Vehicle Interface) had been applied. The simulation test bed developed using Java framework[21] to generate safety alerts in various driving situations shows the usefulness of this approach. The response time graph for the simulation of context I-DAS is depicted and analysed. The effective performance of the driving scenarios in various modes like day and night for single, 2-way and 4-way road scenario for the best, worst and average cases of simulation had been studied. The system works in VANET scenario, which needs to be adaptive for environment changes and to vary according to the context. The presented approach shows the simulation that can be implemented to all vehicles in real time scenario with promising results.

A Multiagent Chess playing paradigm is defined. By defining spheres and strength degrees for pieces winning strategies on games can be defined. The new Intelligent Tree Computing theories we have defined since 1994 can be applied to present precise strategies and prove theorems on games. The multiagent chess game model is defined by an isomorphism on multiboards and agents. Intelligent game trees are presented and goal directed planning is defined by tree rewrite computation on intelligent game trees. Applying intelligent game trees we define capture agents and state an overview to multiagent chess thinking. Game tree intelligence degree is defined and applied to prove model-theoretic soundness and completeness. The game is viewed as a multiplayer game with only perfect information between agent pairs. The man-machine technologies thought dilemma is dispelled in brief by addressing the thinking in the absolute versus thinking for a precisely defined area with a multiagent image for the computing mind.

A heterogeneous computing model with ontology preserving functions are applied to present concept learning across domains with structural agent morphisms. A computing models based on a novel multi-agent competitive learning with multiplayer game tree plans are applied. Agents are assigned to transform the models to reach goal plans. Goals are satisfied based on competitive game tree learning. Agent tree computing models are example prototypes for modeling ontology algebras. Specific agents are assigned to transform the models to reach goal plans where goals are satisfied based on competitive game tree learning. Cooperating agents, that have opened new avenues in modeling and implementing agent teams, are ingredients to specific application modeling. Applications to Formal Concept Description are developed with new description logic algebraic models. Novel Description algebras with concept description ontology algebras and description ontology preservation morphisms are presented.

Current proposals on Semantic Web Services discovery and ranking are based on user preferences descriptions that often come with insufficient expressiveness, consequently making more difficult or even preventing the description of complex user desires. There is a lack of a general and comprehensive preference model, so discovery and ranking proposals have to provide ad hoc preference descriptions whose expressiveness depends on the facilities provided by the corresponding technique, resulting in user preferences that are tightly coupled with the underlying formalism being used by each concrete solution. In order to overcome these problems, in this paper an abstract and sufficiently expressive model for defining preferences is presented, so that they may be described in an intuitively and user-friendly manner. The proposed model is based on a well-known query preference model from database systems, which provides highly expressive constructors to describe and compose user preferences semantically. Furthermore, the presented proposal is independent from the concrete discovery and ranking engines selected, and may be used to extend current Semantic Web Service frameworks, such as wsmo, sawsdl, or owls. In this paper, the presented model is also validated against a complex discovery and ranking scenario, and a concrete implementation of the model in wsmo is outlined.

For many years now, the Web of data has been dominated with the use of only one Coordinates Reference System (CRS), namely WGS84, to represent the location of geographical features on Earth. In this paper, we propose two vocabularies that take into account geometries defined in different CRS. We provide as well mappings with existing vocabularies to ensure compatibilities with existing implementations. Finally, we describe a REST service that supports the conversion of coordinates between several CRS.

This paper proposes an ontology modelling approach for assisting vehicle drivers through safety warning messages during time critical situation. Intelligent Driver Assistance System (I-DAS) is a major component of InVANET[12], which focuses on generating the alert messages based on the context aware parameters such as driving situations, vehicle dynamics, driver activity and environment. I-DAS manages the parameter representation, consistent update /maintenance in XML format while the interpretation of a critical situation is done using ontology modeling. Related safety technologies such as Adaptive Cruise Control, Collision Avoidance System, Lane Departure Warning System, Driver Drowsiness detection system, Parking Assistance System, which generate warnings and alerts to driver continuously, for assistance according to context which is integrated in Vehicle and Vehicle 2 Driver (V2D) communications by DVI(Driver Vehicle Interface) had been applied. The simulation test bed developed using Java framework[21] to generate safety alerts in various driving situations shows the usefulness of this approach. The response time graph for the simulation of context I-DAS is depicted and analysed. The effective performance of the driving scenarios in various modes like day and night for single, 2-way and 4-way road scenario for the best, worst and average cases of simulation had been studied. The system works in VANET scenario, which needs to be adaptive for environment changes and to vary according to the context. The presented approach shows the simulation that can be implemented to all vehicles in real time scenario with promising results.

The joint OGC and W3C standard SOSA/SSN ontology describes sensors, observations, sampling, and actuation. The W3C Thing Description ontology under development in the W3C WoT working group describes things and their interaction patterns. In this paper we are interested in combining these two ontologies for modeling Smart-Sensors. Along with basic sensors, a Smart-Sensor contains a micro-controller that can run different algorithms adapted to the context and a communicating system that exposes the Smart-Sensor on some network. For example, a smart accelerometer can be used to measure cycling cadence, step numbers or a variety of other things. The SOSA/SSN ontology is only able to model partially the adaptation capabilities of Smart-Sensors to different contexts. Thus, we design an SOSA/SSN extension, called the Semantic Smart Sensor Network (S3N) ontology. S3N answers several competency questions such as how to adapt the Smart-Sensor to the current context of use, that is to say sele...

Design techniques with software agents and Abstract Intelligent Implementations are presented. Agent morphisms are defined and applied to preservation principles. The object level definitions for individual modules can be automatically programmed by source abstract syntax tree to target abstract syntax tree morphisms. AII techniques are applied to define an Ontology Preservation Principle for Heterogeneous KB Design and implementation.

Current proposals on Semantic Web Services discovery and ranking are based on user preferences descriptions that often come with insufficient expressiveness, consequently making more difficult or even preventing the description of complex user desires. There is a lack of a general and comprehensive preference model, so discovery and ranking proposals have to provide ad hoc preference descriptions whose expressiveness depends on the facilities provided by the corresponding technique, resulting in user preferences that are tightly coupled with the underlying formalism being used by each concrete solution. In order to overcome these problems, in this paper an abstract and sufficiently expressive model for defining preferences is presented, so that they may be described in an intuitively and user-friendly manner. The proposed model is based on a well-known query preference model from database systems, which provides highly expressive constructors to describe and compose user preferences semantically. Furthermore, the presented proposal is independent from the concrete discovery and ranking engines selected, and may be used to extend current Semantic Web Service frameworks, such as wsmo, sawsdl, or owls. In this paper, the presented model is also validated against a complex discovery and ranking scenario, and a concrete implementation of the model in wsmo is outlined.

Intelligent tree computing techniques are defined with applications to decision tree computing defining decisive agent computing. New linguistics abstraction theories are presented. Treating objects as abstract data types and a two level programming approach to OOP allows us to define Pullup abstractions to treat incompatible objects. A basis for a tree computing theory for abstract objects with intelligent languages and intelligent algebraic tree rewriting is presented. The formulation leads to theoretical results that provide the basis for parallel algebraic tree rewrite computing with intelligent trees. Tree completion theorems are presented, and techniques for generating initial intelligent models are developed. We also have soundness and completeness theorems for the algebraic tree computing theory for abstract objects and its preliminary model theory. New frontiers for object level computing with tree rewriting is presented.

The intensive research on artificial intelligence and internet of things is speeding up the rise of smart cities and autonomous vehicles. In order to ensure the safety of the drivers and pedestrians, the transportation network needs to be connected to its surroundings and consider every valuable piece of information it can gather. Knowledge bases have proven themselves to be efficient in the storage and processing of structured data, making them interesting solutions for the management of transportation networks. This study focuses on the building of a driving simulator allowing the gathering of practical data that can be processed by an ontology and a set of rules, and can quickly and continuously infer a result to suggest the driver on an optimal choice to make. The accuracy results are encouraging, yet giving us extra room for improvement.

Topic: Driver Assistance Technology is emerging as new driving technology popularly known as ADAS. It is supported with Adaptive Cruise Control, Automatic Emergency Brake, blind spot monitoring, lane change assistance, and forward collision warnings etc. It is an important platform to integrate these multiple applications by using data from multifunction sensors, cameras, radars, lidars etc. and send command to plural actuators, engine, brake, steering etc. ADAS technology can detect some objects, do basic classification, alert the driver of hazardous road conditions, and in some cases, slow or stop the vehicle. The architecture of the electronic control units (ECUs) is responsible for executing advanced driver assistance systems (ADAS) in vehicle which is changing as per its response during the process of driving. Automotive system architecture integrates multiple applications into ADAS ECUs that serve multiple sensors for their functions. Hardware architecture of ADAS and autonomo...

We present an ontology to represent generic teaching strategies in an intelligent tutoring system framework. The learning contents, learner's state, and system actions are modeled in just enough detail to support the definition of teaching strategies. Teaching strategies are organized into a hierarchy of teaching goals, and are represented using SWRL rules.

The paper is a basis for multiagent visual computing with the Morph Gentzen logic. A basis to VR computing, computational illusion, and virtual ontology is presented. The IM_BID model is introduced for planning, spatial computing, and visual ontology. Visual intelligent objects are applied with virtual intelligent trees to carry on visual planning. New KR techniques are presented with generic diagrams and appllied to define computable models. The IM Morph Gentzen Logic for computing for multimedia are new projects with important computing applications. The basic principles are a mathematical logic where a Gentzen or natural deduction systems is defined by taking arbitrary structures and multimedia objects coded by diagram functions.The techniques can be applied to arbitrary structures definable by infinitary languages. Multimedia objects are viewed as syntactic objects defined by functions, to which the deductive system is applied.

New optimality principles are put forth based on competitive model business planning. A Generalized MinMax local optimum dynamic programming algorithm is presented and applied to business model computing where predictive techniques can determine local optima. Based on a systems model an enterprise is not viewed as the sum of its component elements, but the product of their interactions. The paper starts with introducing a systems approach to business modeling. A competitive business modeling technique, based on the author's planning techniques is applied. Systemic decisions are based on common organizational goals, and as such business planning and resource assignments should strive to satisfy higher organizational goals. It is critical to understand how different decisions affect and influence one another. Here, a business planning example is presented where systems thinking technique, using Causal Loops, are applied to complex management decisions. Predictive modeling specifics are briefed. A preliminary optimal game modeling technique is presented in brief with applications to innovation and R&D management. Conducting gap and risk analysis can assist with this process. Example application areas to ecommerce with management simulation models are examined.

The purpose of this article is to analyze semantic relations based on graph-independent structural analysis in VocBench. The mix-method of deductive and inductive approach is adapted in operating the research methodology, especially for data collection. The research data are structural domains of semantic relations in ontologies. The data resource is the authoritative agricultural ontology, VocBench, that has been originated by Food and Agricultural organization (FAO), United Nation. VocBench includes around 40000 concepts. The sample size is around 1500 concepts. Sampling technique used is the stratified random sampling. The data analysis results are employed in the SPSS and Excel software using descriptive and proportional analysis. The research results reveal that the taxonomic relations cover a wide area in VocBench. Moreover, the overloading was not seen in the usage of non-taxonomic relations. The high frequency in the usage of the semantic relations' output might be implied the possibility of the width (i.e., exhaustivity) in semantic network in VocBench.

Manufacturing cost of locomotive wheel largely depends on mass of locomotive wheel and to
reduce mass of wheel, design optimization is necessary. In this research the design of locomotive
wheel is optimized considering hub radius and hub width as input parameters to DOE (Design
of Experiments). Initially finite element analysis is performed under static structural loading
conditions to determine equivalent stress and safety factor which is followed by design
optimization using Response Surface Methodology. The software used for design and analysis
is ANSYS.

This study is about the project early operation content of the green road development, takes full account of the operation items of various stages of the life cycle, by the use of special case define the Project Definition Rating Index (PDRI). PDRI assessment framework, defining the need and scope of green road project development operations in the metropolitan area, and inquire set various assessment indicators of the work to complete building the overall indicator assessment system. From research in a policy aspect, as well as data collection out of instances of project case, research program obtains evaluation index operation item, and by semi-structured interviews supplements insufficient evaluation index items and particularity needs. Research results will be beneficial to the application in the metropolitan regional overall development project. Building green road index evaluation system helps to avoid the environmental impact brought about by land development, reduce damage to people's life safety as a consequence from needs for road maintenance, alleviate future maintenance and management expenses, and is in line with the expected benefit of green road project sustainable development.

The new trends of high-speed rail locomotive manufacturing set higher requirement for MRO knowledge representation and XBOM. Therefore, XBOM ontology modeling supporting MRO semantic knowledge representation has become an important research topic of the high speed railway locomotive manufacturing industry. This paper firstly expounds the model frame of high-speed locomotive XBOM ontology, then take the global ontology, the construction ontology and the maintenance plan ontology as examples; respectively carding and analyzing four approaches each ontology contains that class (concept), object, data attribute, and constraint rule and central with the supporting MRO semantic knowledge representation, the XBOM ontology conceptual model can be created; At last, High speed rail train MRO semantic knowledge representation was realized by using protégé4.1 ontology modeling of XBOM for high-speed locomotive.

The paper presents a novel agent plan computing basis where the interaction amongst heterogeneous computing resources is via objects, multiagent AI, and agent intelligent languages. Modeling, objectives, and planning issues are examined with competitive agent computing models. A basis to model discovery and prediction planning is stated in breif. The new agent computing theories the first author defined since 1994 are applied to present precise decision strategies on multiplayer games with only perfect information between agent pairs. The game trees are applied to complete model diagrams on agent learning trees. The computing model is based on a novel competitive learning with agent multiplayer game tree planning. Specific agents are assigned to transform the models to reach goal plans where goals are satisfied based on competitive game tree learning. The planning applications include Operations Research as goal satisfiability and management decision support with means-end analysis.

The paper is based on agent plan computing where the interaction amongst heterogeneous computing resources is via objects, multiagent AI and agent intelligent languages. Modeling, objectives, and planning issues are examined at an agent planning. A basis to model discovery and prediction planning is stated. The new agent computing theories the author defined since 1994 can be applied to present precise decision strategies on multiplayer games with only perfect information between agent pairs. The game trees are applied to train models. The computing model is based on a novel competitive learning with agent multiplayer game tree planning. Specific agents are assigned to transform the models to reach goal plans where goals are satisfied based on competitive game tree learning. The planning applications include OR-Operations Research as goal satisfiability and management decision support withmeansendanalysis.

This paper proposes an ontology modelling approach for assisting vehicle drivers through safety warning messages during time critical situation. Intelligent Driver Assistance System (I-DAS) is a major component of InVANET[12], which focuses on generating the alert messages based on the context aware parameters such as driving situations, vehicle dynamics, driver activity and environment. I-DAS manages the parameter representation, consistent update /maintenance in XML format while the interpretation of a critical situation is done using ontology modeling. Related safety technologies such as
Adaptive Cruise Control, Collision Avoidance System, Lane Departure Warning System, Driver Drowsiness detection system, Parking Assistance System, which generate warnings and alerts to driver continuously, for assistance according to context which is integrated in Vehicle and Vehicle 2 Driver
(V2D) communications by DVI(Driver Vehicle Interface) had been applied. The simulation test bed developed using Java framework[21] to generate safety alerts in various driving
situations shows the usefulness of this approach. The response time graph for the simulation of context IDAS
is depicted and analysed. The effective performance of the driving scenarios in various modes like day and night for single, 2-way and 4-way road scenario for the best, worst and average cases of simulation had been studied. The system works in VANET scenario, which needs to be adaptive for
environment changes and to vary according to the context. The presented approach shows the simulation that can be implemented to all vehicles in real time scenario with promising results.

The Heterogamous agent computing models with ontology preserving functions are applied to transform cognitive learning across domains with structural signatured agent morphisms (author 1992-2005). A computing models based on a novel multiagent competitive learning with agent multiplayer game tree planning are applied where agents are assigned to transform the models to reach goal plans. Goals are satisfied based on competitive game tree learning modeling. Applications to algebras concept description is glimpsed in brief.

Intelligent tree computing techniques are defined with applications to decision tree computing defining decisive agent computing. New linguistics abstraction theories are presented. Treating objects as abstract data types and a two level programming approach to OOP allows us to define Pullup abstractions to treat incompatible objects. A basis for a tree computing theory for abstract objects with intelligent languages and intelligent algebraic tree rewriting is presented. The formulation leads to theoretical results that provide the basis for parallel algebraic tree rewrite computing with intelligent trees. Tree completion theorems are presented, and techniques for generating initial intelligent models are developed. We also have soundness and completeness theorems for the algebraic tree computing theory for abstract objects and its preliminary model theory. New frontiers for object level computing with tree rewriting is presented.

"Design techniques with software agents and Abstract
Intelligent Implementations are presented. Agent
morphisms are defined and applied to preservation
principles. The object level definitions for individual
modules can be automatically programmed by source
abstract syntax tree to target abstract syntax tree
morphisms. AII techniques are applied to define an
Ontology Preservation Principle for Heterogeneous KB
Design and implementation.

A formal heterogeneous software design begins with a formal specification (see for example) for the programs and stores them at a knowledge-base . A formal specification is based on a formal language and makes use of some defining axioms and possibly mathematical structures, in characterizing modules or programs and defining software agents . A formal specification in our approach consists of a signature specifying the type names, and the operations on types, including the rank and the arity of the operations. It also includes a set of axioms which recursively define the operations. Such specifications capture the intended meaning of the possible computation sequences applying a given set of objects and operations, thus specifying a program . Rather than tuning the specifications for efficiency, we argue that efficiency can be achieved by transformation. Note that transformations are one method of program tuning, but tuning the specifications are not achieved through program transformation techniques. The specifications are tuned by discovering new rules or defining axioms which can subsume other such axioms, or introducing rules which can be more efficiently realized given a target implementation language. Completing an incomplete set of defining rules through implementation constraints or gradual domain knowledge learning is another important aspect of specification tuning. Meta--programming is a technique for syntax tree mapping from one language to another. We had put forth the paradigm of mapping the specifications to a high--level language for which an optimizing compiler already exists . The programs that literally implement the mappings are defined by meta--programs , but with a prudent choice of the syntax tree maps during meta-programming, such that correct and efficient implementation maps are attained. A meta--program is a program that manipulates programs, in the sense that the object on which the meta--program functions act on are program constructs of a source language.Meta--programs work at the level of abstract syntax trees and allow us to transform the syntax trees in the specification language, to the syntax trees for a target high level language code, while allowing us to manually code--in the implementation map[1] during the translation. Implementations are homomorphic maps of the syntax trees in one language to another, such that the semantics (the intended meaning) of the specifications are preserved. The trees defined by the present approach have function names corresponding to computing agents. The computing agent functions have a specified module defining their functionality. These definitions are applied at syntax tree implementation time. The homomorphism is defined by setting the correspondence between syntax trees in the specification language and the target language, which consists of executable code syntax trees, through the user defined meta--programs. The mapping preserves the operation on trees, in the image algebra of trees for the target language.

The underlying concept of ERP is based on the holistic nature of the organization. This requires a systemic perspective where the enterprise is not viewed as the sum of its component elements (i.e., departments, divisions, branches, etc), but the product of their interactions. The paper starts with introducing a systems approach to business modeling. A competitive business modeling techniques, based on the first author's work on Planning, Competitive Business Models, and ERP are introduced. Systemic decisions are based on common organizational goals, and as such, ERP should strive to satisfy higher organizational goals. A systems approach to business decisions is a prerequisite to ERP implementation. It is critical to the preceding to understand how different decisions affect and influence one another. Here, a business planning example is presented where Systems Thinking technique, using Causal Loops, are applied to complex management decisions. Conducting gap and risk analysis can assist with this process. Depending on capability and flexibility factors ERP can be applied to determine and modify implementation plans, as specific functionalities appear to become more critical. The paper will illustrate application areas to corporate ERP models and their implications for the strategic management of the enterprise. Transactional business models and e-business infrastructures are also illustrated and their business system interfaces as well as infrastructure applications are discussed.

The paper is a basis for multiagent visual computing with the Morph Gentzen logic. The IM_BID model is introduced for planning, spatial computing, and visual ontology. Visual intelligent objects are applied with virtual intelligent trees to carry on visual planning. New KR techniques are presented with G-diagrams and applications to define computable models and relevant world reasoning. G-diagrams are diagrams defined from a minimal set of function symbols that can inductively define a model. G-diagrams are applied to relevance reasoning by model localized representations and a minimal efficient computable way to represent relevant knowledge for localized AI worlds. Dagrammatic reasoning is defined in terms of inferences directed by the G-diagrams for models. The techniques show how computable AI world knowledge is representable. G-diagrams are applied towards KR from planning with nondeterminism and planning with free proof trees to planning with predictive diagrams. The IM Morph Gentzen Logic for computing for multimedia are new projects with important computing applications since our papers for diagrammatic computing. The basic principles are a mathematical logic where a Gentzen or natural deduction systems is defined by taking arbitrary structures and multimedia objects coded by diagram functions.The techniques can be applied to arbitrary structures definable by infinitary languages. Multimedia objects are viewed as syntactic objects defined by functions, to which the deductive system is applied. A basis to VR computing, computational illusion and virtual ontology is presented.

The paper is a basis for multiagent visual computing with the Morph Gentzen logic. The IM_BID model is introduced for planning, spatial computing, and visual ontology. Visual intelligent objects are applied with virtual intelligent trees to carry on visual planning. New KR techniques are presented with G-diagrams and applications to define computable models and relevant world reasoning. G-diagrams are diagrams defined from a minimal set of function symbols that can inductively define a model. G-diagrams are applied to relevance reasoning by model localized representations and a minimal efficient computable way to represent relevant knowledge for localized AI worlds. Dagrammatic reasoning is defined in terms of inferences directed by the G-diagrams for models. The techniques show how computable AI world knowledge is representable. G-diagrams are applied towards KR from planning with nondeterminism and planning with free proof trees to planning with predictive diagrams. The IM Morph Gentzen Logic for computing for multimedia are new projects with important computing applications since our papers for diagrammatic computing. The basic principles are a mathematical logic where a Gentzen or natural deduction systems is defined by taking arbitrary structures and multimedia objects coded by diagram functions.The techniques can be applied to arbitrary structures definable by infinitary languages. Multimedia objects are viewed as syntactic objects defined by functions, to which the deductive system is applied. A basis to VR computing, computational illusion and virtual ontology is presented.

Multi-agent planning is presented as a basis to attention management. Viewing our agent modular approach as the augmented approach to intelligent multiagent systems planning, the basic foundations to our preceding project become explorable for emerging areas like optimization of augmented knowledge spaces, ubiquitous computing and interface design with attentional agent spanning using SVMs. Index Terms-cognitive multi-agent planning, optimization, knowledge representation, SVM

The paper is based on agent plan computing where the interaction amongst heterogeneous computing resources is via objects, multiagent AI and agent intelligent languages. Modeling, objectives, and planning issues are examined at an agent planning. A basis to model discovery and prediction planning is stated. The new AI agent computing business bases defined during the last several years can be applied to present precise decision strategies on multiplayer games with only perfect information between agent pairs. A new basis for business modelling with the new agent computing paradigms is essential to economic agent models. Multiplayer agnet game trees are introuced as the basis to ecenomic games The game trees are applied to attain models. The computing model is based on a novel competitive learning with agent multiplayer game tree planning. Specific agents are assigned to transform the models to reach goal plans where goals are satisfied based on competitive game tree learning. The planning applications include OR-Operations Research as goal satsfibility and micro-managing decision support with means-end analysis.

Electronics play a key role in improving vehicles safety. Use of electronics has made possible the introduction and integration of a wide range of new safety and environmental devices in cars. Nowadays, both customer demands and government legislation continue to improve traffic safety. Safety awareness for vehicles has been increasing strongly since the 1980s. It started with simple seat-belt systems continued with airbags, and has now led to the first really intelligent safety systems. With today's advances in sensor and processor technology, the possibilities are growing rapidly. Governments are also viewing these as ways to decrease traffic casualties, and legislation is starting to demand that car manufacturers make use of the technology. The paper highlights the recent technology used in the vehicles for purpose of safety. Electronics & Communication field has expanded remarkably in the last few years with the development in safety of vehicles. Carmakers are constantly seeking new ways of helping drivers to avoid accidents.

This paper proposes an ontology modelling approach for assisting vehicle drivers through safety warning messages during time critical situation. Intelligent Driver Assistance System (I-DAS) is a major component of InVANET[12], which focuses on generating the alert messages based on the context aware parameters such as driving situations, vehicle dynamics, driver activity and environment. I-DAS manages the parameter representation, consistent update /maintenance in XML format while the interpretation of a critical situation is done using ontology modeling. Related safety technologies such as Adaptive Cruise Control, Collision Avoidance System, Lane Departure Warning System, Driver Drowsiness detection system, Parking Assistance System, which generate warnings and alerts to driver continuously, for assistance according to context which is integrated in Vehicle and Vehicle 2 Driver (V2D) communications by DVI(Driver Vehicle Interface) had been applied. The simulation test bed developed using Java framework [21] to generate safety alerts in various driving situations shows the usefulness of this approach. The response time graph for the simulation of context I-DAS is depicted and analysed. The effective performance of the driving scenarios in various modes like day and night for single, 2-way and 4-way road scenario for the best, worst and average cases of simulation had been studied. The system works in VANET scenario, which needs to be adaptive for environment changes and to vary according to the context. The presented approach shows the simulation that can be implemented to all vehicles in real time scenario with promising results.