Automatic Parking Controller with a Twin Artificial Neural Network Architecture

Algorithm 1

Predictive collision-avoidance algorithm based on twin ANN parking agent.

	Input: // Input to the Clone agent for every decision step of the Main agent
	= {,,}; // Input Pose of the Virtual vehicle = Current pose of the main vehicle
	; // Input Action of the clone agent = Output of the main agent’s action
	Parking Environment & obstacles ; // Parking slot length and neighboring obstacles
	Output: Adjusted Action to the main vehicle ;
	Parameters ; // # of looking forward steps (), adjustment parameters for desired actions ()
(1)	Procedure forecasting step forward poses and actions for the virtual vehicle
	// Predicting Pose at j forward steps
	// Simulating j step forward actions
(2)	for j = 1 to do
(3)	Calculate j step forward state of the virtual vehicle ;
(4)	Calculate j step forward actions of the virtual vehicle ;
	// Checking collision occurrence and adjustment of actions if collision detected
(5)	if Collision Case ①:
(6)	adjust steering angle ;
(7)	break for-loop
(8)	else if Collision Case ②:
(9)	adjust steering angle ;
(10)	break for-loop
(11)	else if Collision Case ③:
(12)	adjust desired velocity ;
(13)	break for-loop
(14)	else // If no collision is predicted, then do not adjust inputs
(15)	{, };
(16)	end if
(17)	end for
(18)	return;
(19)	end of Procedure