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Satisfactory performance of intelligent vehicles systems in tracking a predefined trajectory requires an efficient control scheme to generate steering control signals from posture errors (i.e., errors in position and orientation). For such systems, it is necessary at each instant to control steering action so that any deviation from the path is corrected in a stable manner, in a reasonable time and without any oscillation about the desired path. This paper deals with stability of motion and motion control of intelligent vehicle systems. In this regard, the general control structure and specification of an optimum range of predefined control parameters for accurate path tracking of these systems are determined. A two degree of freedom (DOF) nonlinear dynamic model is developed to represent their plane motion.

This paper reports on development of a sub-optimal control strategy for path tracking control of automated guided vehicles (AGV’s) and wheeled mobile robots. A two degree of freedom (DOF) nonlinear dynamic model is developed to represent their plane motion. Path tracking of the AGV is attained by controlling the position and orientation errors about the trajectory, which is accomplished by controlling the steering input signal on the basis of error feedbacks to the controller. Experimental results demonstrating the performance of the controlled system are reported.

This paper deals with controller design for path tracking control of intelligent vehicle systems. A two degrees of freedom (DOF) model is developed to represent the motion of a vehicle which is used to formulate the path tracking problem of vehicles. By using optimal control theory, the structure of a controller is obtained for vehicles with front and rear steering systems. In designing the controller, a quadratic measure of performance consisting of the integral of the errors (in position and orientation of the vehicle) and the input (front and rear wheel steering angles) are minimized. This controller is implemented to an experimental vehicle and the experimental results of its path following are presented.

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.

Vehicles are becoming part of the Internet, either as a terminal in a mobile network, as a network node or as a moving sensor (providing environmental, car status or video information). Interest of vehicles' passengers in location-based information is steadily growing. Moreover drivers and passengers may like to receive information about traffic jams or accidents in their vicinity, or chat with other vehicle's passengers. Enabling communication among automobile nodes (cars) is not a straightforward task. Such nodes form an extremely dynamic ad hoc network, and this presents some technical challenges. One essential characteristic of such networks is that the available services are in principle unknown to a node. A Dynamic Discovery Service (DDS) protocol to discover nodes is needed.

In the near future, vehicles are expected to become a part of the Internet, either as a terminal in a mobile network, as a network node, or as a moving sensor (providing environmental information, cars status, streaming video, etc.) or a combination of the three. This is partly due to the steadily growing interest of vehicles' passengers in location-based information. Drivers and passengers that would want to receive information about traffic jams or accidents in their vicinity will likely be interested in accessing Internet services from within the vehicular network. Access can be gained by using roadside installed Internet Gateways (IGs), which are able to communicate with the vehicles. When the car network is connected to the Internet, it is important for the vehicle to detect available gateways providing access to the Internet. Therefore, a gateway discovery mechanism is required.

Automotive multiplexing allows sharing information among various intelligent modules inside an automotive electronic system. In order to achieve an optimum functionality, the information should be exchanged among various electronic modules in real time. New features are introduced in automobiles such as Intelligent Vehicle Highway System (IVHS), intelligent transportation support system, engine immobilizers, night vision assistance system, and automated collision avoidance and notification system. The inclusion of such features increases the data traffic over the multiplexing bus. Also, these features require very high speed and expensive bus. Data reduction techniques are used to send the data over a transmission media at high speed. Using the data reduction techniques, we will be able to include new features in automobiles without the need of a high speed bus. Since the automotive environment is different, a special data reduction algorithm is mandated.