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The reproduction of the vehicle motion is a crucial element of accident reconstruction. Apart from the position of the center of gravity in an inertial coordinate system, the vehicle heading plays an important role. The heading is the sum of the yaw angle and the vehicle body side slip angle. In standard vehicles, the yaw angle can be determined using the yaw rate sensor and the wheel speeds. However, the yaw rate sensor is often subject to temperature drift. The wheel speed signals are forged at low speeds or due to slip. These errors result in significant deviations of reconstructed and real vehicle heading. Therefore, an intelligent combination of these signals is required. This paper describes a fuzzy system which is capable to increase the accuracy of yaw angle calculation by means of fuzzy logic. Before the data is applied to the fuzzy system, it is preprocessed to ensure the accuracy of the fuzzy system inputs.

Coordination and concentration of different electronic functions within a car with the objective of functional cooperation and, if possible, incorporation into a single package to reduce costs and improve reliability is discussed. The alternatives of a Special Purpose Computer or a General Purpose Realtime Computer are described with regard to available sensor technology.

In this paper the vehicle body side slip angle (VBSSA) is determined by means of non-linear state space observers. First, an adaptive non-linear double track model is presented. Validation with real measurement data shows that the model accuracy is sufficient for observer design. On basis of this model two observers are derived. One observer is based on a linearization of the vehicle model around the currently estimated state vector. The other observer adapts the dynamics of the non-linear estimation error to the one of a linear reference model. As this observer is restricted to systems of a specific structure, the adaptive non-linear double track model has to be restructured accordingly. The presented observers are validated with real measurement data. They provide an accurate estimation of the VBSSA up to the stability limit of the vehicle.

As future drive-by-wire systems have no mechanical fallback level, the increased safety requirements need to be met by software-based solutions. The task of the software is to provide services in the field of fault detection and compensation as well as control of redundant hardware structures. Particularly the implementation of fault detection and error correction avoids fatal output of drive-by-wire control units caused by erroneous input signals. This article describes the implementation of a module compensating faults in the input signals of a vehicle function, which controls the longitudinal dynamics of a truck. The error correction is achieved by means of data fusion. Sensing units consisting of the sensor as well as the preprocessing unit often are provided by external suppliers. In some cases information regarding the characteristics of their output data written on the CAN bus is not available.

The increasing linkage of route guidance servers within the recent years leads to numerous efforts to split traffic assignment algorithms in an efficient way on these distributed computers. Especially in the field of intermodal services, i.e. calculating the fastest paths of certain origin-destination pairs with respect to different individual and public traffic services, solutions are required to implement the routing models in a fast, reliable way. Unfortunately, analysis of different realizations is commonly done by comparing the amount of necessary instructions O(·) in different net topologies. However, as computing power is in the meanwhile at a fairly high level, delay in a distributed environment can mainly be expected due to communication time. Dynamic calculations demand to transmit actual traffic conditions during several time periods, thus this paper examines the different routing strategies by evaluating the occuring message transmission time in common graph classes.

The vehicle body sideslip angle (VBSSA) is a key variable in vehicle dynamics indicating critical driving situations. It is, e.g., essential in vehicle dynamics control concepts. Since it cannot be measured with standard sensors, it has to be determined via a model based approach. Thereto an Extended Kalman Filter will be presented that is capable of describing the VBSSA with high accuracy. The filter design is based on a nonlinear double track model combining the longitudinal and lateral dynamics. Starting point is a double track model with three state variables, that are the velocity in the center of gravity, the VBSSA and the yaw rate. Then, the longitudinal dynamics are incorporated, yielding the velocity and the longitudinal forces at the individual wheels. The resulting nonlinear state space model only requires information that is provided by the standard sensors available in series production vehicles. On basis of this nonlinear model an Extended Kalman Filter is derived.

Future vehicle electrical systems will differ substantially from current ones due to rising requirements. For example driver-assistance and drive-by-wire systems will lead to novel and demanding electrical load profiles which in turn will pose new requirements on the electrical system. Furthermore safety concepts, reliability, availability and diagnosis are getting increasingly important in such systems and thus also in the vehicle's electrical system. In order to meet the upcoming requirements new concepts for future vehicle electrical systems have to be developed such that the new powernet is able to adapt flexibly to different situations or failures by routing the energy through different channels. For efficiency the corresponding development process should be based on modeling and simulation techniques. Depending on the design or analysis task, the powernet is represented through different modeling descriptions.

In this approach a nonlinear controller for the lateral vehicle dynamics is designed. The basis for the design is a nonlinear model of the lateral vehicle dynamics in state space representation consisting of three states: The vehicle velocity, the yaw rate as well as the vehicle body sideslip angle (VBSSA). As control variables the yaw rate and the VBSSA are chosen. To assure the vehicle follows the driver's directional intent, the yaw rate is adapted to a desired reference value determined by means of a linear single track model. The second control variable -the VBSSA- is utilized to reduce the lateral forces. Incorporating the VBSSA, the controller's behavior can be significantly improved. Thus, a nonlinear controller is designed which is capable to stabilize the vehicle in critical driving situations. This nonlinear controller is based on an adaptation of a quality function for the nonlinear model to the one for a linear reference system.

As automotive systems are becoming increasingly distributed, communication between their components is becoming even more eminent. In safety-relevant distributed systems, the reliability of communication between nodes is crucial for the safety of a system. To guarantee such reliability, it is prerequisite that all nodes in the system have a consistent view of which nodes are functioning correctly and which are not (group membership). In this paper existing algorithms for ensuring group membership are presented and possible solutions for communication systems without such functionality, for example FlexRay, as well as a solution for a network based approach are outlined.