def reset(self):
###
#self.generate_routefile_two_intersections()
self.generate_routefile()
traci.load([
"-c", "one_lane/one_lane4.sumocfg", "--collision.check-junctions",
"1", "--start", '--no-step-log', 'true'
])
###
#traci.load(["-c", "one_intersection_w_priority/one_intersection_w_priority.sumocfg", "--collision.check-junctions", "1", "--start"])
run = Assembler(self.carID)
terminate = False
while terminate == False:
num_vec = traci.vehicle.getIDList()
for i in range(len(num_vec)):
if num_vec[i] != 'ego':
traci.vehicle.setLaneChangeMode(num_vec[i], 512)
self.output = run.getTensor()
if self.output is not None:
terminate = True
traci.simulationStep()
return self.getObservation()
def execute(self, action):
#traci.vehicle.setSpeedMode('ego', 0)
#print(action)
run = Assembler(self.carID)
# self.output = tensor.executeTensor()
self.output = run.getTensor()
# print(self.output)
if self.output is None:
term = True
return self.getObservation(), term, 0
# rew = Reward('ego', self.output)
rew = Reward('ego')
coll, term = rew.collision()
if term is True:
cost = coll
return self.getObservation(), term, cost
traci.vehicle.setSpeedMode('ego', 0)
num_vec = traci.vehicle.getIDList()
for i in range(len(num_vec)):
if num_vec[i] != 'ego':
traci.vehicle.setLaneChangeMode(num_vec[i], 512)
# print(action)
carID = 'ego'
act = Action(carID)
if action == 0:
pass
#act.decelerate()
#print('dec')
elif action == 1:
pass
#act.accelerate()
#print('acc')
else:
pass
#act.remain()
#print('rem')
traci.simulationStep()
#net = sumolib.net.readNet('huge_crossing/huge_crossing.net.xml')
#tensor = Tensor('ego', net, self.conflictory_list[0], self.connection_list[0])
#self.output = tensor.executeTensor()
#rew = Reward('ego', self.output)
win = rew.target()
cost = rew.optimum_speed_deviation() + win
# + brake
traci.simulationStep()
return self.getObservation(), term, cost
def execute(self, action):
run = Assembler(self.carID)
self.output = run.getTensor()
#print(run.getTensor())
if self.output is None:
term = True
return self.getObservation(), term, 0
rew = Reward('ego', run.getTraffic(), self.output)
coll, term = rew.collision()
if term is True:
cost = coll
return self.getObservation(), term, cost
traci.vehicle.setSpeedMode('ego', 0)
num_vec = traci.vehicle.getIDList()
for i in range(len(num_vec)):
if num_vec[i] != 'ego':
traci.vehicle.setLaneChangeMode(num_vec[i], 512)
###
#if i % 2 == 0:
#traci.vehicle.setSpeedMode(num_vec[i], 23)
carID = 'ego'
act = Action(carID)
if action == 0:
act.decelerate()
# print('dec')
elif action == 1:
act.accelerate()
# print('acc')
else:
act.remain()
# print('rem')
gap, term = rew.emergency_gap()
wary = rew.wary_before_intersection()
#win = rew.target()
brake = rew.emergency_brake()
cost = rew.optimum_speed_deviation() + brake + gap + wary
traci.simulationStep()
#print(self.output)
return self.getObservation(), term, cost
