openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for over 200 supported car makes and models.
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#!/usr/bin/env python
import pygame # pylint: disable=import-error
from plant import Plant
from selfdrive.car.honda.values import CruiseButtons
import numpy as np
import selfdrive.messaging as messaging
import math
CAR_WIDTH = 2.0
CAR_LENGTH = 4.5
METER = 8
def rot_center(image, angle):
"""rotate an image while keeping its center and size"""
orig_rect = image.get_rect()
rot_image = pygame.transform.rotate(image, angle)
rot_rect = orig_rect.copy()
rot_rect.center = rot_image.get_rect().center
rot_image = rot_image.subsurface(rot_rect).copy()
return rot_image
def car_w_color(c):
car = pygame.Surface((METER*CAR_LENGTH, METER*CAR_LENGTH)) # pylint: disable=too-many-function-args
car.set_alpha(0)
car.fill((10,10,10))
car.set_alpha(128)
pygame.draw.rect(car, c, (METER*1.25, 0, METER*CAR_WIDTH, METER*CAR_LENGTH), 1)
return car
if __name__ == "__main__":
pygame.init()
display = pygame.display.set_mode((1000, 1000))
pygame.display.set_caption('Plant UI')
car = car_w_color((255,0,255))
leadcar = car_w_color((255,0,0))
carx, cary, heading = 10.0, 50.0, 0.0
plant = Plant(100, distance_lead = 40.0)
control_offset = 2.0
control_pts = zip(np.arange(0, 100.0, 10.0), [50.0 + control_offset]*10)
def pt_to_car(pt):
x,y = pt
x -= carx
y -= cary
rx = x * math.cos(-heading) + y * -math.sin(-heading)
ry = x * math.sin(-heading) + y * math.cos(-heading)
return rx, ry
def pt_from_car(pt):
x,y = pt
rx = x * math.cos(heading) + y * -math.sin(heading)
ry = x * math.sin(heading) + y * math.cos(heading)
rx += carx
ry += cary
return rx, ry
while 1:
if plant.rk.frame%100 >= 20 and plant.rk.frame%100 <= 25:
cruise_buttons = CruiseButtons.RES_ACCEL
else:
cruise_buttons = 0
md = messaging.new_message()
md.init('model')
md.model.frameId = 0
for x in [md.model.path, md.model.leftLane, md.model.rightLane]:
x.points = [0.0]*50
x.prob = 0.0
x.std = 1.0
car_pts = map(pt_to_car, control_pts)
print car_pts
car_poly = np.polyfit([x[0] for x in car_pts], [x[1] for x in car_pts], 3)
md.model.path.points = np.polyval(car_poly, np.arange(0, 50)).tolist()
md.model.path.prob = 1.0
Plant.model.send(md.to_bytes())
plant.step(cruise_buttons = cruise_buttons, v_lead = 2.0, publish_model = False)
display.fill((10,10,10))
carx += plant.speed * plant.ts * math.cos(heading)
cary += plant.speed * plant.ts * math.sin(heading)
# positive steering angle = steering right
print plant.angle_steer
heading += plant.angle_steer * plant.ts
print heading
# draw my car
display.blit(pygame.transform.rotate(car, 90-math.degrees(heading)), (carx*METER, cary*METER))
# draw control pts
for x,y in control_pts:
pygame.draw.circle(display, (255,255,0), (int(x * METER),int(y * METER)), 2)
# draw path
path_pts = zip(np.arange(0, 50), md.model.path.points)
for x,y in path_pts:
x,y = pt_from_car((x,y))
pygame.draw.circle(display, (0,255,0), (int(x * METER),int(y * METER)), 1)
"""
# draw lead car
dl = (plant.distance_lead - plant.distance) + 4.5
lx = carx + dl * math.cos(heading)
ly = cary + dl * math.sin(heading)
display.blit(pygame.transform.rotate(leadcar, 90-math.degrees(heading)), (lx*METER, ly*METER))
"""
pygame.display.flip()