def run():
# 初始化设置选项
ai_settings = Settings()
func.clean_img(ai_settings)
# 初始化小车
car = Car(ai_settings)
# 初始化深度学习模型
dlmodel = DLmodel(ai_settings)
# 初始化算法控制系统
algo = AlgoControl(ai_settings, car)
# 创建一个状态类, 用以储存标志物状态
markstats = MarkStatus()
# 开始任务的主循环
while True:
func.get_image(ai_settings, car, dlmodel)
algo.angle_prep = func.predict_angle(ai_settings, dlmodel)
car.angle = ai_settings.angle_formula(algo.angle_prep)
func.get_label_para(ai_settings, dlmodel, markstats)
func.algorithmal_control(ai_settings, car, markstats, algo)
def init_kinematic_cars(self):
for position, car_index in zip(self.positions_list, range(1, self.cars_nr + 1)):
car_tag = "car_" + str(car_index)
car_image_path = self.current_dir + '/resources/cars/' + car_tag + '.png'
car_image = pygame.image.load(car_image_path).convert_alpha()
car_image = pygame.transform.scale(car_image, (42, 20))
car = Car(position[0], position[1], car_tag=car_tag, car_image=car_image)
car.max_velocity = 10
if len(position) == 3:
car.angle = position[2]
self.kinematic_cars[car_tag] = car
def init_highway_traffic(self):
# define lanes : (40, 4); (37, 3); (34, 2); (31, 1); (43, 5); (46, 6); (49, 7); (52, 8)
available_x = np.arange(31, 53, 3)
available_y = np.arange(self.traffic_safe_space, self.screen_height, 4 * self.traffic_safe_space
+ self.car_image.get_width())
available_positions = []
for x in available_x:
for y in available_y:
position = (x, y)
available_positions.append(position)
random.shuffle(available_positions)
for car_index in range(self.traffic_cars_nr):
# generate random position
car_position = available_positions[random.randint(0, len(available_positions) - 1)]
# remove that position from the available position list
available_positions.remove(car_position)
# init traffic car and add it to traffic list
traffic_car = Car(car_position[0], car_position[1])
traffic_car.angle = -90
traffic_car.include_next_lane_mechanic = True
traffic_car.max_velocity = random.randint(10, self.car.max_velocity)
self.highway_traffic.append(traffic_car)
