Fig 1.
Schematic diagram of a vehicle model.
Fig 2.
Block diagram of the proposed hierarchical estimator.
Fig 3.
Structure of the hybrid estimator for TRFC.
Table 1.
Ranges of Input Parameters.
Fig 4.
GRNN architecture used for the TRFC estimation.
Fig 5.
The process of GRNN establishment.
Fig 6.
The selection of the smoothing factor.
Table 2.
Vehicle parameters.
Table 3.
Road surface in CarSim.
Fig 7.
Target velocity in CarSim.
Fig 8.
Control input and vehicle state estimation.
(The red dotted line is estimated value; continuous black line is reference value; continuous blue line is sensor noise.)
Fig 9.
Slip ratio and slip angle estimation results.
(The red dotted line is estimated value; continuous black line is reference value).
Fig 10.
Tire force estimation results.
(The red dotted line is estimated value; continuous black line is reference value).
Fig 11.
Tire-road friction coefficient estimation.
(The red dotted line is estimated value; continuous black line is reference value).
Table 4.
Road surface in CarSim.
Fig 12.
Control input and vehicle state estimation.
(The red dotted line is estimated value; continuous black line is reference value; continuous blue line is sensor noise.)
Fig 13.
Slip ratio estimation results.
(The red dotted line is estimated value; continuous black line is reference value).
Fig 14.
Slip angle estimation results.
(The red dotted line is estimated value; continuous black line is reference value).
Fig 15.
Tire force estimation results.
(The red dotted line is estimated value; continuous black line is reference value).
Fig 16.
Relationship between slip ratio and normalized longitudinal tire force under different friction coefficients.
Fig 17.
Tire-road friction coefficient estimation.
(The red dotted line is estimated value; continuous black line is reference value).