class Plant():
messaging_initialized = False
def __init__(self,
lead_relevancy=False,
speed=0.0,
distance_lead=2.0,
only_lead2=False,
only_radar=False):
self.rate = 1. / DT_MDL
if not Plant.messaging_initialized:
Plant.radar = messaging.pub_sock('radarState')
Plant.controls_state = messaging.pub_sock('controlsState')
Plant.car_state = messaging.pub_sock('carState')
Plant.plan = messaging.sub_sock('longitudinalPlan')
Plant.messaging_initialized = True
self.v_lead_prev = 0.0
self.distance = 0.
self.speed = speed
self.acceleration = 0.0
# lead car
self.distance_lead = distance_lead
self.lead_relevancy = lead_relevancy
self.only_lead2 = only_lead2
self.only_radar = only_radar
self.rk = Ratekeeper(self.rate, print_delay_threshold=100.0)
self.ts = 1. / self.rate
time.sleep(1)
self.sm = messaging.SubMaster(['longitudinalPlan'])
from selfdrive.car.hyundai.values import CAR
from selfdrive.car.hyundai.interface import CarInterface
self.planner = Planner(CarInterface.get_params(CAR.GRANDEUR_IG),
init_v=self.speed)
def current_time(self):
return float(self.rk.frame) / self.rate
def step(self, v_lead=0.0, prob=1.0, v_cruise=50.):
# ******** publish a fake model going straight and fake calibration ********
# note that this is worst case for MPC, since model will delay long mpc by one time step
radar = messaging.new_message('radarState')
control = messaging.new_message('controlsState')
car_state = messaging.new_message('carState')
a_lead = (v_lead - self.v_lead_prev) / self.ts
self.v_lead_prev = v_lead
if self.lead_relevancy:
d_rel = np.maximum(0., self.distance_lead - self.distance)
v_rel = v_lead - self.speed
if self.only_radar:
status = True
elif prob > .5:
status = True
else:
status = False
else:
d_rel = 200.
v_rel = 0.
prob = 0.0
status = False
lead = log.RadarState.LeadData.new_message()
lead.dRel = float(d_rel)
lead.yRel = float(0.0)
lead.vRel = float(v_rel)
lead.aRel = float(a_lead - self.acceleration)
lead.vLead = float(v_lead)
lead.vLeadK = float(v_lead)
lead.aLeadK = float(a_lead)
lead.aLeadTau = float(1.5)
lead.status = status
lead.modelProb = float(prob)
lead.radar = True
if not self.only_lead2:
radar.radarState.leadOne = lead
radar.radarState.leadTwo = lead
control.controlsState.longControlState = LongCtrlState.pid
control.controlsState.vCruise = float(v_cruise * 3.6)
car_state.carState.vEgo = float(self.speed)
car_state.carState.standstill = self.speed < 0.01
# ******** get controlsState messages for plotting ***
sm = {
'radarState': radar.radarState,
'carState': car_state.carState,
'controlsState': control.controlsState
}
self.planner.update(sm)
self.speed = self.planner.v_desired_filter.x
self.acceleration = self.planner.a_desired
fcw = self.planner.fcw
self.distance_lead = self.distance_lead + v_lead * self.ts
# ******** run the car ********
#print(self.distance, speed)
if self.speed <= 0:
self.speed = 0
self.acceleration = 0
self.distance = self.distance + self.speed * self.ts
# *** radar model ***
if self.lead_relevancy:
d_rel = np.maximum(0., self.distance_lead - self.distance)
v_rel = v_lead - self.speed
else:
d_rel = 200.
v_rel = 0.
# print at 5hz
if (self.rk.frame % (self.rate // 5)) == 0:
print(
"%2.2f sec %6.2f m %6.2f m/s %6.2f m/s2 lead_rel: %6.2f m %6.2f m/s"
% (self.current_time(), self.distance, self.speed,
self.acceleration, d_rel, v_rel))
# ******** update prevs ********
self.rk.monitor_time()
return {
"distance": self.distance,
"speed": self.speed,
"acceleration": self.acceleration,
"distance_lead": self.distance_lead,
"fcw": fcw,
}