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Traditional climate controller process depends upon the establishment of a mathematical model. Expert systems were created to mimic the behavior of a skilled human operator for those processes too complex to be mathematically modeled in real time[1]. Fuzzy logic inference engine use an expert system paradigm for automatic process control[2], and have been successful in controlling climate for a vehicle controller. Recently, there has been many practical applications of fuzzy control. Applications of fuzzy control to vehicles become more attractive. In this paper we implemented fuzzy logic based climate controller using software develpment tool (MATLAB).

Distributed Computing systems consist of several processors that interact and cooperate with each other by message passing. These distributed systems provide many attractive features such as fault tolerance, resource sharing, high reliability and high throughput. These features make distributed systems good candidates for many real time applications such as aircraft, space crafts and automotive control. Car Industry is striving to provide reliable and cost effective Computing systems for their automobiles. As the number of processors increases in a vehicle, the demand increases to provide a reliable Computing system for the automotive. Therefore, it is important to develop specialized distributed Computing systems for this type of applications taking into consideration reliability as well as cost of the system. In this paper, a distributed Computing system architecture has been proposed for automotive applications.

Over 42,000 deaths have occurred on highways in the United States during calendar year 2002 [1]. One way to achieve a safe highway environment is using a communication system that allows all vehicles on the highway or road to share their data so they can warn each other about dangerous situations and plan for safe driving activities. One problem to be addressed in such a system is dividing the vehicles on the highway into groups-of-interest, where vehicles that may need cooperation among each other to perform safe driving maneuvers comprise a group-of-interest. This paper proposes a location matrix-based algorithm to define the peer space (group-of-interest); that is, vehicles on the highway are encapsulated in matrices, and all maneuvers are planned in a cellular fashion using the Dynamic Service Discovery (DSD) -based Jini protocol as an ad-hoc network communication protocol.