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Automated_Parallel_Parking

Numerical Optimal Control Project (SS 2023)

Project Name

Time-Optimal Automated Parallel Parking of Vehicle

Project Description

We present a maneuver planning system for autonomous parallel parking of wheeled vehicles. The planning problem is established as a minimum-time optimal control problem (OCP) using the vehicle dynamics, boundary constraints, and the physical restrictions of the vehicle. The formulated OCP is solved using the Interior Point (IP) method based on a direct multiple-shooting scheme.

Requirements

MATLAB

CasADi

MATLAB Files Description

main.m: Main file containing OCP and all constraint formulation. Run the file to see the simulated results of Optimized trajectory for different initial conditions.

ode.m: Implementation of kinematic model of a car.

rk4_step.m Implementation of single step RK4 integrator.

get_params.m: Contains the parameter related to car size.

get_car_coordinates.m: Calculates the coordinates of four corner points of a car.

OE_boundry.m Implementation of collision free conditions.

slot_function.m: Implementation of parking slot function.

Visuals

Simulation result of optimal trajectory obtained for OCP formulation for automated parallel parking of car

conditon_1

Simulation result for initial condition 1 where the green circle depicts the car’s starting state, the red dotted line shows the optimized trajectory of the car for the parking, and the blue colour rectangle represents the car.

Authors and acknowledgment

Authors: Shikha Tiwari, Ankita Pawar
Acknowledgment: For this project, we used template of direct multiple shooting provided by CasADi.

References

[1] B. Li, K. Wang, and Z. Shao, “Time-optimal maneuver planning in automatic parallel parking using a simultaneous dynamic optimization approach,” IEEE Transactions on Intelligent Transportation Systems,17(11), pp.3263-3274, 2016.
[2] C. Lee, C. Lin, and B. Shiu, “Autonomous vehicle parking using hybrid artificial intelligent approach,” J. Intell. Robot. Syst., vol. 56, no. 3, pp.319–343, Jan. 2009.
[3] M. Diehl, “Numerical Optimal Control,” Lecture Notes, Albert Ludwigs-Universitaet Freiburg, 2020.
[4] J. A. Andersson, J. Gillis, G. Horn, J. B. Rawlings, and M. Diehl,“Casadi: A software framework for nonlinear optimization and optimal control,” Mathematical Programming Computation, vol. 11, no. 1, pp.1–36, 2019.
[5] A. W¨achter and L.T. Biegler. “On the implementation of a primaldual interior point filter line search algorithm for large-scale nonlinear programming. Mathematical Programming,” 106(1):25–57, 2006.