The primary purpose of each autonomous Exit Parking system is to facilitate the process of Exiting the vehicle, emphasizing the comfort and safety of driving in the absence of almost any human effort. In this paper, the problem of Exit Parking for autonomous vehicles is addressed. A nonlinear kinematic model is presented based on the geometric relationship of the vehicle velocities, and a linear time-varying discrete-time model of the vehicle is obtained for utilizing the optimal control strategy. The proposed path planning algorithm is based on the minimization of a geometric cost function. This algorithm works for ample space Exit Parking in Single-Maneuver and tight spaces in Multi-Maneuver Exit Parking. Finally, an optimal discrete-time linear quadratic control approach is hired to minimize a quadratic cost function. To evaluate the performance of the proposed algorithm, the control system is simulated by MATLAB/Simulink software. The results show that the optimal control strategy is well able to design and follow the desired path in each of the Exit Parking maneuvers.

This paper develops an automatic Parking algorithm based on a fuzzy logic controller with the vehicle pose for the input and the steering angle for the output. In this way some feasible reference trajectory path have been introduced according to geometric and kinematic constraints and nonholonomic constraints to simulate motion path of car. Also a novel method is used for Parking space detection according to image processing. A fuzzy controller according to experiments of skilled driver and path planning is designed, and then fuzzy rules are tuned and finally fuzzy membership functions are optimized using genetic algorithm. Simulation results illustrate the effectiveness of the developed schemes.

Drivers in urban neighborhoods who patrol streets, seeking inexpensive on-street Parking create a significant fraction of measured traffic congestion. The pool of drivers patrolling at any time can be modeled as a queue, where ‘queue service’ is the act of Parking in a recently vacated Parking space and queue discipline is SIRO – Service In Random Order. We develop a queueing model of such driver behavior, allowing impatient drivers to abandon the queue and to settle for more expensive off-street Parking. We then relate the model to the economic theory of congestion pricing, arguing that price differentials between on-street and off-street Parking should be reduced in order to reduce traffic congestion. Reducing the number of "patrolling drivers" often can reduce urban road congestion significantly, in some cases as effectively as technologically expensive road pricing schemes that cordon off the center city.