Use of communicated GPS position and velocity information in adaptive cruise control and cooperative adaptive cruise control with the purpose of cooperative driving and the use of GPS position for automated path following in highly automated driving are two current research applications requiring fast and accurate GPS updates. Based on previous experience, a GPS/INS integration system is presented in this paper to allow faster updates as compared to the use of GPS only and to provide accurate position/velocity information in the presence of temporary losses of GPS fix. An INS algorithm and GPS/INS integration are presented in this paper in a realistic simulation setting. The aim is to analyze the effects of different sampling rates of sensors, errors, covariances and to use GPS/INS fusion to broadcast position data at a higher rate than GPS. The DCM method is used to estimate rotations in a inertial measurement unit. Drifts and biases are seen to be the main error sources. As a prerequisite before road testing with our experimental vehicle, GPS/INS is fused using the extended Kalman filter in a highly realistic simulation setting.