Citation

Jonasson M, Rogenfelt, Lanfelt C, Fredriksson J, Hassel M. IEEE Trans. Vehicular Tech. 2020; 69(5): 4788-4802.

Copyright

(Copyright © 2020, IEEE (Institute of Electrical and Electronics Engineers))

DOI

10.1109/TVT.2020.2971667

PMID

unavailable

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.

Language: en

Keywords

aggressive manoeuvres; allan variance; angular wheel speed sensors; atonomous vehicles; autonomous vehicle; blind safe stop; complex filter; conceptual limitations; Dead reckoning; degrees of freedom; EKF; EKF filter concepts; estimation theory; experimental vehicle; Extended Kalman Filter; filter designs; filtering process; independent measurement devices; inertia measurement unit; inertial 6 DOF measurement unit; inertial navigation; Inertial navigation; initial vehicle speed; Kalman filters; measurement models; mobile robots; nonlinear filters; pinion angle sensor; position data; position estimation errors; position uncertainty; position-uncertainty estimation; power black-out; remotely operated vehicles; road vehicles; safe-stop scenarios; Sensor phenomena and characterization; sensors; simpler filter; smooth manoeuvres; Uncertainty; use-case manoeuvres; vehicle dynamics; Vehicle dynamics; vehicle dynamics models; vehicle dynamics process models; vehicle position; velocity 70.0 km/h; wheels; Wheels