1. A system comprising:
a processor; and
5 an estimation engine coupled to the processor, wherein the
estimation engine is to:
obtain an input vehicle characteristic indicating motional
changes occurring in a vehicle while travelling on a road;
process the input vehicle characteristic based on an
10 estimation model to determine a weightage parameter corresponding
to the input vehicle characteristic, wherein the estimation model is
trained based on a training vehicle characteristic and an actual
inclination angle of the road corresponding to the training vehicle
characteristic; and
15 calculate an inclination angle of the road based on the
determined weightage parameter.
2. The system as claimed in claim 1, wherein the vehicle characteristics
is one of a motor torque, a throttle position, a vehicle speed, or combination
thereof.
20 3. The system as claimed in claim 1, wherein the vehicle characteristics
are obtained from a plurality of sensors installed onto the vehicle.
4. The system as claimed in claim 1, wherein the estimation engine is
to calculate the inclination angle based on the determined weightage
parameter using the following relation:
25 Inclination Angle = (W1*(d(Motor_Torque)/dt) +
W2*(d(Throttle)/dt) + W3*(d(Vehicle speed)/dt) + W4*Motor Torque +
W5*Throttle + W6*Vehicle Speed )+C;
wherein ‘C’ is a constant for compensating error and offset,
W1 and W4 are the weightage parameters determined corresponding
30 to an input torque value, W2 and W5 are the weightage parameters
determined corresponding to a input throttle value, and W3 and W6
15
are the weightage parameters corresponding to a input vehicle
speed.
5. The system as claimed in claim 1, wherein the weightage parameters
indicate amount of contribution of each of the vehicle characteristics and
5 their corresponding derivatives in calculating the inclination angle.
6. The system as claimed in claim 1, wherein the estimation model is
trained to output a confidence score along with the estimated inclination
angle, indicating the reliability of the estimation.
7. A method comprising:
10 obtaining training information comprising a training vehicle
characteristic and an actual inclination angle corresponding to the training
vehicle characteristic; and
training an estimation model based on the training information and a
weight data, wherein the estimation model when trained is to predict a
15 weightage parameter corresponding to an input vehicle characteristic, and
wherein the weight data corresponds to the weightage parameter
associated with the input vehicle characteristic.
8. The method as claimed in claim 7, wherein the training vehicle
characteristic is one of a motor torque, a throttle position, a vehicle speed,
20 or combination thereof.
9. The method as claimed in claim 7, wherein the training information is
obtained from a plurality of vehicles, wherein motor torque is obtained from
a torque sensor, throttle position is obtained from a throttle position sensor,
and the vehicle speed is obtained from a wheel speed sensor.
25 10. The method as claimed in claim 7, wherein an inclination angle
corresponding to an input vehicle characteristic is determined using the
following relation based on the determined weightage parameter:
Inclination Angle =(W1*(d(Motor_Torque)/dt) +
W2*(d(Throttle)/dt) + W3*(d(Vehicle speed)/dt) + W4*Motor Torque +
30 W5*Throttle + W6*Vehicle Speed )+C;
16
wherein ‘C’ is a constant for compensating error and offset,
W1 and W4 are the weightage parameters determined corresponding
to an input torque value, W2 and W5 are the weightage parameters
determined corresponding to a input throttle value, and W3 and W6
5 are the weightage parameters corresponding to a input vehicle
speed.