def auto_drive_call(m_order_queue, respond_dict):
"""
Runs drive instance in the simulation.
Defining and enabling sensors.
:param respond_dict: dictionary to send value VA process
:param m_order_queue:
:type m_order_queue: multiprocessing.Queue To provide communication between voice assistant process.
:rtype None
"""
# Driver initialize
auto_drive = Driver()
auto_drive.setAntifogLights(True)
auto_drive.setDippedBeams(True)
TIME_STEP = int(auto_drive.getBasicTimeStep())
# distance sensors
dist_sensor_names = [
"front", "front right 0", "front right 1", "front right 2",
"front right 3", "front left 0", "front left 1", "front left 2",
"front left 3", "rear", "rear left", "rear right", "right", "left"
]
dist_sensors = {}
for name in dist_sensor_names:
dist_sensors[name] = auto_drive.getDistanceSensor("distance sensor " +
name)
dist_sensors[name].enable(TIME_STEP)
# GPS
gps = auto_drive.getGPS("gps")
gps.enable(TIME_STEP)
# Compass
compass = auto_drive.getCompass("compass")
compass.enable(TIME_STEP)
# get and enable front camera
front_camera1 = auto_drive.getCamera("front camera 1")
front_camera1.enable(TIME_STEP)
front_camera2 = auto_drive.getCamera("front camera 2")
front_camera2.enable(TIME_STEP)
front_camera3 = auto_drive.getCamera("front camera 3")
front_camera3.enable(TIME_STEP)
front_cams = {
"right": front_camera2,
"left": front_camera1,
"center": front_camera3
}
# get and enable back camera
back_camera = auto_drive.getCamera("camera2")
back_camera.enable(TIME_STEP * 10)
# back_camera.recognitionEnable(TIME_STEP * 10)
# Get the display devices.
# The display can be used to visually show the tracked position.
# For showing lane detection
display_front = auto_drive.getDisplay('display')
display_front.setColor(0xFF00FF)
# To establish communication between Emergency Vehicle
receiver = auto_drive.getReceiver("receiver")
receiver.enable(TIME_STEP)
# To establish communication between other vehicles
emitter = auto_drive.getEmitter("emitter")
# lidar devices
lidars = []
Log = list()
error_Log = list()
for i in range(auto_drive.getNumberOfDevices()):
device = auto_drive.getDeviceByIndex(i)
if device.getNodeType() == Node.LIDAR:
lidars.append(device)
device.enable(TIME_STEP * 10)
device.enablePointCloud()
if not lidars:
error_Log.append(" [ DRIVER CALL] This vehicle has no 'Lidar' node.")
# Set first values
auto_drive.setCruisingSpeed(40)
auto_drive.setSteeringAngle(0)
VA_order, emergency_message, prev_gps, gps_val = None, None, None, None
# Main Loop
while auto_drive.step() != -1:
start_time = time.time()
# for lidar in lidars:
# lidar.getPointCloud()
if m_order_queue.qsize() > 0:
VA_order = m_order_queue.get()
else:
VA_order = None
""" If an Emergency Vehicle in the emergency state closer than 4 metre it sends emergency message
to cars in front of it and other cars has sends messages as a chain to clear the way """
if receiver.getQueueLength() > 0:
message = receiver.getData()
# for sending emergency message to AutoCars front of our AutoCar
# emitter.send(message)
emergency_message = struct.unpack("?", message)
emergency_message = emergency_message[0]
receiver.nextPacket()
else:
emergency_message = False
gps_val = round(sqrt(gps.getValues()[0]**2 + gps.getValues()[2]**2), 2)
if gps_val is None:
error_Log.append("[DRIVER CALL] couldn't get gps value..")
else:
prev_gps = gps_val
if prev_gps is not None and gps_val is not None:
gps_val = prev_gps
if gps_val is not None:
# To calculate direction of the car
cmp_val = compass.getValues()
angle = ((atan2(cmp_val[0], cmp_val[2])) * (180 / pi)) + 180
# goes on Z axis
if 335 <= angle <= 360 or 0 <= angle <= 45 or 135 <= angle <= 225:
axis = 1
# goes on X axis
elif 225 <= angle < 335 or 45 <= angle < 135:
axis = 0
obj_data, LIDAR_data = Obj_Recognition.main(
dist_sensor_names, lidars, dist_sensors, front_cams,
back_camera)
DataFusion.main(auto_drive, gps_val, obj_data, LIDAR_data,
emergency_message, display_front, front_cams,
dist_sensors, VA_order, respond_dict, gps,
axis)
else:
error_Log.append("[DRIVER CALL] couldn't get gps value..")
Log.append(str(time.time() - start_time))
with open("Logs\Driver_Log.csv", 'a') as file:
wr = writer(file, quoting=QUOTE_ALL)
wr.writerow(Log)
if len(error_Log):
with open("Logs\error_Log.csv", 'a', newline="") as file:
wr = writer(file, quoting=QUOTE_ALL)
wr.writerow(error_Log)
#!/usr/bin/env python
"""vehicle_driver controller."""
import rospy
import math
from nav_msgs.msg import Odometry
from vehicle import Driver
#from cars_stage1.msg import ControlPoints, VehicleInfo, VehicleInfoArray,Location,CarDimensions,CarVelocity
from geometry_msgs.msg import Point, Pose, Quaternion, Twist, Vector3
rospy.init_node('vehicle_driver', anonymous=True)
pub = rospy.Publisher('/ego_vehicle', Odometry, queue_size=20)
rate = rospy.Rate(10)
odom = Odometry()
driver = Driver()
driver.setSteeringAngle(0)
driver.setCruisingSpeed(20)
gps = driver.getGPS("gps")
gps.enable(1)
while driver.step() != -1:
driver.setSteeringAngle(0)
print(gps.getValues()[0], gps.getValues()[2])
x = gps.getValues()[0]
y = gps.getValues()[2]
odom.pose.pose = Pose(Point(x, y, 0), Quaternion(0, 0, 0, 0))
print(gps.getSpeed())
vel = gps.getSpeed()
odom.twist.twist = Twist(Vector3(vel, 0, 0), Vector3(0, 0, 0))
pub.publish(odom)
'left']
sensors = {}
maxSpeed = 100
driver = Driver()
driver.setSteeringAngle(0.0) # go straight
# get and enable the distance sensors
for name in sensorsNames:
sensors[name] = driver.getDistanceSensor('distance sensor ' + name)
sensors[name].enable(10)
# get and enable the GPS
gps = driver.getGPS('gps')
gps.enable(10)
# get the camera
camera = driver.getCamera('camera')
# uncomment those lines to enable the camera
#camera.enable(50)
#camera.recognitionEnable(50)
dest =0
prevpos = -2
counter=0
while driver.step() != -1:
# adjust the speed according to the value returned by the front distance sensor
frontDistance = sensors['front'].getValue()
frontRange = sensors['front'].getMaxValue()
speed = maxSpeed * frontDistance / frontRange