self.restart=True
return self.df
QLearnInfo = WriteFrame(['ID','Car Location','Lane Number','Destination Road',
'Destination Lane','Correct Lane','Speed','Collision',
'Adjacent Lane Free','Front of Line',
'Speed of Ahead Car','Distance to Ahead Car',
'Time to Nearest Vehicle'])
iteration = 1
err = 0
## run iteration
while iteration <= numiter and err == 0:
starttime = time.time()
Sim = Sumo(configuration)
## now set up parameters and vehicles
# [creation time, starting lane, destination lane, starting speed]
cars = pd.DataFrame([[0., '1i_0','3o_0',20.]])
cars = cars.append([[0., '2i_0','1o_0',20.]])
cars.columns = ['time','lane','dest','speed']
ncars = cars.shape[0]
cars['status'] = [-1]*ncars #-1 not created, 0 created, 1 exited, 2 crashed
cars['lanepos'] = [-1]*ncars # not given to Agent but needed for calculation
cars['x'] = [-1]*ncars
cars['y'] = [-1]*ncars
cars['angle'] = [-1]*ncars
cars['ilane'] = ['']*ncars
ttime = 0
# smart restart if file is saved
if 'lastStart.int' in os.listdir(os.path.realpath('.')):
lastStart = open('lastStart.int')
iteration = int(lastStart.read())
lastStart.close()
params = pd.read_csv(paramFile,header=0)
else:
iteration = 1
params = None
## run iteration
while iteration <= options.numiter:
err = 0
starttime = time.time()
Sim = Sumo(configuration, options.gui)
## now set up parameters and vehicles
err += Sim.createVehicle('ego','1i_0',0.)
egoSpeed = 25.
err += Sim.createVehicle('left','3i_1',0.)
leftSpeed = 20.
params_iter = pd.DataFrame([[egoSpeed, leftSpeed, 0., 0., -1., 'na']],
columns=ParameterColumns)
output = None
ttime = 0
maxTime = 100 # seconds
## run simulation
# smart restart if file is saved
if 'lastStart.int' in os.listdir(os.path.realpath('.')):
lastStart = open('lastStart.int')
iteration = int(lastStart.read())
lastStart.close()
params = pd.read_csv(paramFile,header=0)
else:
iteration = 1
params = None
call(['mkdir','-p',outputFolder+'/'+options.outputName]) # add folder
## run iteration
while iteration <= options.numiter:
err = 0
starttime = time.time()
Sim = Sumo(configuration, options.gui)
## now set up parameters and vehicles
err += Sim.createVehicle('ego','main_0',VEHsize[0])
#egoControl = Controllers.RearEndEgo(vehicleSpeed(), vehicleAccel())
egoControl = Controllers.RearEndRandom(vehicleSpeed(),maxdecel=.5)
err += Sim.createVehicle('lead','main_0',50+VEHsize[0])
#leadControl = Controllers.RearEndBrake(vehicleSpeed(), vehicleAccel())
leadControl = Controllers.RearEndRandom(vehicleSpeed(),maxdecel=5.)
# params_iter = pd.DataFrame([[egoControl.speed, leadControl.speed,
# egoControl.accel, leadControl.accel,
# leadControl.brakeMagnitude, leadControl.brakeTime,
# -1.]], columns=ParameterColumns)
params_iter = pd.DataFrame([[egoControl.speed, leadControl.speed, -1.]],
columns=ParameterColumns)
# smart restart if file is saved
if 'lastStart.int' in os.listdir(os.path.realpath('.')):
lastStart = open('lastStart.int')
iteration = int(lastStart.read())
lastStart.close()
params = pd.read_csv(paramFile, header=0)
else:
iteration = 1
params = None
## run iteration
while iteration <= options.numiter:
err = 0
starttime = time.time()
Sim = Sumo(configuration, options.gui)
## now set up parameters and vehicles
err += Sim.createVehicle('ego', '1i_0', 0.)
egoSpeed = 25.
err += Sim.createVehicle('left', '3i_1', 0.)
leftSpeed = 20.
params_iter = pd.DataFrame([[egoSpeed, leftSpeed, 0., 0., -1., 'na']],
columns=ParameterColumns)
output = None
ttime = 0
maxTime = 100 # seconds
## run simulation
QLearnInfo = WriteFrame([
'ID', 'Car Location', 'Lane Number', 'Destination Road',
'Destination Lane', 'Correct Lane', 'Speed', 'Collision',
'Adjacent Lane Free', 'Front of Line', 'Speed of Ahead Car',
'Distance to Ahead Car', 'Time to Nearest Vehicle'
])
iteration = 1
err = 0
## run iteration
while iteration <= numiter and err == 0:
starttime = time.time()
Sim = Sumo(configuration)
## now set up parameters and vehicles
# [creation time, starting lane, destination lane, starting speed]
cars = pd.DataFrame([[0., '1i_0', '3o_0', 20.]])
cars = cars.append([[0., '2i_0', '1o_0', 20.]])
cars.columns = ['time', 'lane', 'dest', 'speed']
ncars = cars.shape[0]
cars['status'] = [
-1
] * ncars #-1 not created, 0 created, 1 exited, 2 crashed
cars['lanepos'] = [
-1
] * ncars # not given to Agent but needed for calculation
cars['x'] = [-1] * ncars
# -*- coding: utf-8 -*-
"""
Created on Tue Nov 17 20:13:37 2015
@author: motro
"""
from sumoMethods import Sumo
configuration = 'emptyhighway'
sim = Sumo(configuration, gui=True)
sim.createVehicle('a','main_0',40)
[lane,lanex,xy] = sim.getVehicleState('a')
print 'a, 0: '+str(xy[0])
sim.createVehicle('b','main_0')
[lane,lanex,xy] = sim.getVehicleState('b')
print 'b, 0: '+str(xy[0])
sim.moveVehicleAlong('b',38)
[lane,lanex,xy] = sim.getVehicleState('a')
print 'a, 1: '+str(xy[0])
[lane,lanex,xy] = sim.getVehicleState('b')
print 'b, 1: '+str(xy[0])
sim.end()
self.restart=True
def add(self, newrows):
if self.restart:
self.df = pd.DataFrame(newrows)
self.restart=False
else:
self.df = self.df.append(newrows)
def out(self):
if self.colnames is not None:
self.df.columns = self.colnames
#self.df.to_csv(fileName, sep=',', header=True, index=False)
self.restart=True
return self.df
err = 0
Sim = Sumo(configuration,gui=True)
# first gather the possible positions/angles of each intersection lane
allcars = {}
for start, end, road in intersectionLookUp:
print "at "+road
err += Sim.createVehicle(road, start, 90.)
err += Sim.moveVehicleAlong(road, 0.1, end)
thisdf = WriteFrame(['x','y','angle','length','width','lp'])
dist = 1.
status = -1
totaldist = 0
while status < 1 and totaldist < 50:
lane,lanepos,pos,angle = Sim.getVehicleState(road)
status = (lane[1]=='o')-(lane[1]=='i')