This paper presents a method for real-time identification of sensor statistics especially aimed for low-cost automotive-grade sensors. Based on recent developments in adaptive particle filtering (PF) and under the assumption of Gaussian distributed noise, our method identifies the slowly time-varying sensor offsets and variances jointly with the vehicle state, and it extends to banked roads. While the method is primarily focused on learning the noise characteristics of the sensors, it also produces an estimate of the vehicle state. This can then be used in driver-assistance systems, either as a direct input to the control system or indirectly to aid other sensor-fusion methods. The paper contains verification against several simulation and experimental data sets. The results indicate that our method is capable of bias-free estimation of both the bias and the variance of each sensor, that the estimation results are consistent over different data sets, and that the computational load is feasible for implementation on computationally limited embedded hardware typical of automotive applications.

References

References
1.
Gustafsson
,
F.
,
2009
, “
Automotive Safety Systems
,”
IEEE Signal Process. Mag.
,
26
(
4
), pp.
32
47
.
2.
Reif
,
K.
, and
Dietsche
,
K.-H.
,
2011
,
Bosch Automotive Handbook
,
Robert Bosch
,
Plochingen, Germany
.
3.
Johansen
,
T. A.
,
Petersen
,
I.
,
Kalkkuhl
,
J.
, and
Ludemann
,
J.
,
2003
, “
Gain-Scheduled Wheel Slip Control in Automotive Brake Systems
,”
IEEE Trans. Control Syst. Technol.
,
11
(
6
), pp.
799
811
.
4.
Paden
,
B.
,
Cap
,
M.
,
Yong
,
S. Z.
,
Yershov
,
D.
, and
Frazzoli
,
E.
,
2016
, “
A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles
,”
IEEE Trans. Intell. Veh.
,
1
(
1
), pp.
33
55
.
5.
Berntorp
,
K.
,
2017
, “
Path Planning and Integrated Collision Avoidance for Autonomous Vehicles
,”
American Control Conference
(
ACC
), Seattle, WA, May 24–26.
6.
Thrun
,
S.
,
Montemerlo
,
M.
,
Dahlkamp
,
H.
,
Stavens
,
D.
,
Aron
,
A.
,
Diebel
,
J.
,
Fong
,
P.
,
Gale
,
J.
,
Halpenny
,
M.
,
Hoffmann
,
G.
,
Lau
,
K.
,
Oakley
,
C.
,
Palatucci
,
M.
,
Pratt
,
V.
,
and Stang
,
P.
,
Strohband
,
S.
,
Dupont
,
C.
,
Jendrossek
,
L.-E.
,
Koelen
,
C.
,
Markey
,
C.
,
Rummel
,
C.
,
van Niekerk
,
J.
,
Jensen
,
E.
,
and Alessandrini
,
P.
,
Bradski
,
G.
,
Davies
,
B.
,
Ettinger
,
S.
,
Kaehler
,
A.
,
and Nefian
,
A.
, and
Mahoney
,
P.
,
2006
, “
Stanley: The Robot That Won the DARPA Grand Challenge
,”
J. Field Rob.
,
23
(
9
), pp.
661
692
.
7.
Nilsson
,
J.
,
Falcone
,
P.
,
Ali
,
M.
, and
Sjöberg
,
J.
,
2015
, “
Receding Horizon Maneuver Generation for Automated Highway Driving
,”
Control Eng. Pract.
,
41
, pp.
124
133
.
8.
Solyom
,
S.
, and
Hultén
,
J.
,
2013
,
Physical Model-Based Yaw Rate and Steering Wheel Angle Offset Compensation
,
Springer
,
Berlin
, pp.
51
58
.
9.
Gustafsson
,
F.
,
Ahlqvist
,
S.
,
Forssell
,
U.
, and
Persson
,
N.
,
2001
, “
Sensor Fusion for Accurate Computation of Yaw Rate and Absolute Velocity
,”
SAE
Paper No. 2001-01-1064.http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.574.4853&rep=rep1&type=pdf
10.
Berntorp
,
K.
,
2016
, “
Joint Wheel-Slip and Vehicle-Motion Estimation Based on Inertial, GPS, and Wheel-Speed Sensors
,”
IEEE Trans. Control Syst. Technol.
,
24
(
3
), pp.
1020
1027
.
11.
Baffet
,
G.
,
Charara
,
A.
, and
Lechner
,
D.
,
2009
, “
Estimation of Vehicle Sideslip, Tire Force and Wheel Cornering Stiffness
,”
Control Eng. Pract.
,
17
(
11
), pp.
1255
1264
.
12.
Berntorp
,
K.
, and
Di Cairano
,
S.
,
2018
, “
Tire-Stiffness and Vehicle-State Estimation Based on Noise-Adaptive Particle Filtering
,”
IEEE Trans. Control Syst. Technol.
(in press).
13.
Berntorp
,
K.
, and
Di Cairano
,
S.
,
2018
, “
Offset and Noise Estimation of Automotive-Grade Sensors Using Adaptive Particle Filtering
,”
American Control Conference
(
ACC
), Milwaukee, WI, June 27–29.
14.
Doucet
,
A.
, and
Johansen
,
A. M.
,
2009
, “
A Tutorial on Particle Filtering and Smoothing: Fifteen Years Later
,”
Handbook of Nonlinear Filtering
,
D.
Crisan
, and
B.
Rozovsky
, eds.,
Oxford University Press
,
Oxford, UK
.
15.
Eidehall
,
A.
,
Schön
,
T. B.
, and
Gustafsson
,
F.
,
2005
, “
The Marginalized Particle Filter for Automotive Tracking Applications
,”
Intelligent Vehicles Symposium
, Las Vegas, NV, June 6–8.
16.
Lundquist
,
C.
,
Karlsson
,
R.
,
Özkan
,
E.
, and
Gustafsson
,
F.
,
2014
, “
Tire Radii Estimation Using a Marginalized Particle Filter
,”
IEEE Trans. Intell. Transp. Syst.
,
15
(
2
), pp.
663
672
.
17.
Anderson
,
B. D. O.
, and
Moore
,
J. B.
,
1979
,
Optimal Filtering
,
Prentice Hall
,
Englewood Cliffs, NJ
.
18.
Schön
,
T. B.
,
Gustafsson
,
F.
, and
Nordlund
,
P.-J.
,
2005
, “
Marginalized Particle Filters for Mixed Linear Nonlinear State-Space Models
,”
IEEE Trans. Signal Process.
,
53
(7), pp.
2279
2289
.
19.
Bishop
,
C. M.
,
2006
,
Pattern Recognition and Machine Learning
,
Springer-Verlag
,
New York
.
20.
Saha
,
S.
, and
Gustafsson
,
F.
,
2012
, “
Particle Filtering With Dependent Noise Processes
,”
IEEE Trans. Signal Process.
,
60
(
9
), pp.
4497
4508
.
21.
Gillespie
,
T.
,
1992
,
Fundamentals of Vehicle Dynamics
,
Society of Automotive Engineers
,
Warrendale, PA
.
22.
Rajamani
,
R.
,
2006
,
Vehicle Dynamics and Control
,
Springer-Verlag
,
New York
.
23.
Ryu
,
J.
, and
Gerdes
,
J. C.
,
2004
, “
Estimation of Vehicle Roll and Road Bank Angle
,”
American Control Conference
(
ACC
), Boston, MA, June 30–July 2.
24.
Gustafsson
,
F.
,
2010
,
Statistical Sensor Fusion
,
Utbildningshuset/Studentlitteratur
,
Lund, Sweden
.
25.
Murphy
,
K. P.
,
2007
, “
Conjugate Bayesian Analysis of the Gaussian Distribution
,” UBC, Vancouver, BC, Canada,
Report
.https://www.cs.ubc.ca/~murphyk/Papers/bayesGauss.pdf
26.
Özkan
,
E.
,
Šmídl
,
V.
,
Saha
,
S.
,
Lundquist
,
C.
, and
Gustafsson
,
F.
,
2013
, “
Marginalized Adaptive Particle Filtering for Nonlinear Models With Unknown Time-Varying Noise Parameters
,”
Automatica
,
49
(
6
), pp.
1566
1575
.
27.
Rao
,
C. R.
,
2001
,
Linear Statistical Inference and Its Applications
,
Wiley
,
Hoboken, NJ
.
28.
Berntorp
,
K.
, and
Di Cairano
,
S.
,
2017
, “
Particle Gibbs With Ancestor Sampling for Identification of Tire-Friction Parameters
,”
IFAC World Congress
,
Toulouse, France
,
July 9–14
.
29.
Lindsten
,
F.
,
Jordan
,
M. I.
, and
Schön
,
T. B.
,
2014
, “
Particle Gibbs With Ancestor Sampling
,”
J. Mach. Learn. Res.
,
15
(
1
), pp.
2145
2184
.http://www.jmlr.org/papers/volume15/lindsten14a/lindsten14a.pdf
You do not currently have access to this content.