An Automated Parking Guidance System for Megacities

Abstract

Enormous increase for vehicles in the megacities, with limited parking creates a serious issue. In order to handle the issue, many cities have adopted the guided parking as a part of Intelligent Transportation System (ITS). The current ITS is continuously evolving to incorporate the required issues. ITS communicates among vehicles and parking facilities and shares the information of interest. Thereafter ITS employs dynamic information obtained from vehicles for guiding the parking. In the current work, authors have suggested two functions for parking guidance in this study. Using these functions, central server uses this dynamic information obtained from sensory networks and uses the same to suggest parking to the driver. The driver, upon receiving the suggestion, in turn may reserve the suggested parking or may choose to decline the suggestion based on his personal experience. The proposed approach considers various parameters to evaluate effectiveness of the guided parking. During simulation, these parameters have been demonstrated and it is observed that the proposed system outperforms the existing system in literature.