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. Afterwards, the reliability of the described sensors is determined according to the driving situation. The heuristic knowledge about the reliability is implemented in the fuzzy system's knowledge base. The right choice of signal inputs is also important to conclude sensor reliability. Depending on the determined reliability, the significance of each individual sensor for yaw rate calculation is adapted. Measurements with a test vehicle proof the validity of the presented system. Tests with artificial errors analyze the fuzzy system's sensitivity to sensor failures.