Abstract
This work considers the problem of position and position-uncertainty estimation for atonomous vehicles during power black-out, where it cannot be assumed that any position data is accessible. To tackle this problem, the position estimation will instead be performed using power separated and independent measurement devices, including one inertial 6 Degrees of Freedom (DOF) measurement unit, four angular wheel speed sensors and one pinion angle sensor. The measurement unit's sensors are initially characterized in order to understand conceptual limitations of the inertial navigation and also to be used in a filtering process. Measurement models are then fused together with vehicle dynamics process models using the architecture of an Extended Kalman Filter (EKF). Two different EKF filter concepts are developed to estimate the vehicle position during a safe stop; one simpler filter for smooth manoeuvres and a complex filter for aggressive manoeuvres. Both filter designs are tested and evaluated with data gathered from an experimental vehicle for selected manoeuvres of developed safe-stop scenarios. The experimental results from a set of use-case manoeuvres show a trend where the size of the position estimation errors significantly grows above an initial vehicle speed of 70 km/h. This paper contributes to develop vehicle dynamics models for the purpose of a blind safe stop.
Highlights
T HE development of autonomous vehicles without interaction by a human driver is prioritized in the society, see for example [1]–[3]
Since the duration of a safe stop doesn’t exceed approximately 30 seconds, the random walk will likely not have an effect on the bias in this application
The results clearly shows, for this specific example, that yaw rate from inertial measurement unit (IMU) is more accurate than from the odometry
Summary
T HE development of autonomous vehicles without interaction by a human driver is prioritized in the society, see for example [1]–[3]. Since there is no guarantee that the position measurement is available, the control to a complete stop is suggested to be based on the estimated position from sensors protected from electro-magnetic disturbance and equipped with redundant power supply and communication abilities These sensors typically include a inertial measurement unit (IMU) measuring acceleration and angular speed of the vehicle body. The main objective of this work is to accurately estimate the position and its uncertainty of the vehicle using inertial navigation during a safe stop. The work attempts to answer the question of what position accuracy that is possible to achieve Note that it is the analysis of the safe stop use-case that is in focus and not the development of well-known Kalman filters.
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