def __init__(self, model="simple"):
if (model != "simple" and model != "complex"):
raise Exception(
f"Illegal argument model can only be 'simple' or 'complex' not {model}"
)
self.model = model
#Variables to keep track of the car's current state
self.position = 0
self.velocity = 0
self.accel = 0
self.steering_angle = 0
self.gear = None
#Constants corresponding to the car pedals
self.ACCELERATOR = 0
self.BRAKE = 1
#Constants corrsponding to car gears
self.FORWARD = 0
self.REVERSE = 1
'''
PART OF WEEK 2 HW
FILL IN ESTIMATED COEFFICIENTS BELOW (Delete exception too)
All except for the brake_weight should be positive.
'''
#Coefficients corresponding to the motion dynamics
self.rolling_bias = None
self.friction_constant = None
self.accelerator_weight = None
self.brake_weight = None
raise Exception(
"You forgot to input SystemID learned weights in the Controller Model"
)
'''
If approximating the complex internal model we use a FCN
to model the acceleration as a function of the pedal depressions
and velocity. Since the weights for the this model will be in the
SystemID directory we include it in the file path.
The model has 3 inputs (accelerator depression, brake depression, velocity)
'''
if (self.model == "complex"):
self.complex_accel_fcn = nn.fcn(
model_name=self.complex_weights_fp(), num_inputs=3)
#Variables to keep track of time (seconds)
self.T = 0
#Corresponds to simulations internal discrete time step (15fps)
self.dt = 1 / 15
def __init__(self, car_model, estimator_type):
'''
Allowable combinations of car_model and estimator_type are
("simple", "fcn")
("simple", "analytical")
("complex", "fcn")
No analytical solution for complex internal model.
'''
if (estimator_type not in {"analytical", "fcn"}):
raise Exception(
f"Illegal estimator_type, f{estimator_type}, must be 'analytical' or 'fcn'"
)
if (car_model not in {"simple", "complex"}):
raise Exception(
f"Illegal estimator_type, f{estimator_type}, must be 'simple' or 'complex'"
)
if (estimator_type == 'analytical' and car_model == 'complex'):
raise Exception("No analytical estimator for complex car model")
self.estimator_type = estimator_type
'''
If using a fcn load parameters from Brakind Distance directory
two inputs (intitial velocity, stopping distance), output must be between 0 and 1
'''
if (estimator_type == "fcn"):
self.fcn = nn.fcn(model_name=os.path.join(self.bd_fp(),
f"{car_model}_bd"),
num_inputs=2,
out_range=(0, 1))
'''
If using analytical approach get coefficients from controller
model (pedal weights, friction constant, and rolling bias)
'''
if (estimator_type == "analytical"):
ci = controller_model.Car_Interface()
self.brake_weight = ci.brake_weight
self.rolling_bias = ci.rolling_bias
self.friction_constant = ci.friction_constant
self.rolling_bias = 0.009929075478129247
self.friction_constant = 0.10974291535061839
self.accelerator_weight = 0.10000558634381539
self.brake_weight = -0.2499897051771736
>>>>>>> e85aa159abb29b9eba779ce605b479a4dfa30407
'''
If approximating the complex internal model we use a FCN
to model the acceleration as a function of the pedal depressions
and velocity. Since the weights for the this model will be in the
SystemID directory we include it in the file path.
The model has 3 inputs (accelerator depression, brake depression, velocity)
'''
if (self.model == "complex"):
self.complex_accel_fcn = nn.fcn(model_name = self.complex_weights_fp(), num_inputs = 3)
#Variables to keep track of time (seconds)
self.T = 0
#Corresponds to simulations internal discrete time step (15fps)
self.dt = 1 / 15
#Depress the specified pedal by the specified amount for one dt time step
def apply_control(self, pedal, amount):
if (self.gear is None):
raise Exception("Please set gear before applying control")
if (pedal not in [None, self.ACCELERATOR, self.BRAKE]):
raise Exception(f"Invalid pedal provided, {pedal}")