Reservation based optimal parking lot recommendation model in Internet of Vehicle environment

Abstract

In order to solve the problem that the drivers can't find the optimal parking lot timely, a reservation based optimal parking lot recommendation model in Internet of Vehicle (IoV) environment is designed. Based on the users oriented parking information recommendation system, the model considers subjective demands of drivers comprehensively, makes a deeply analysis of the evaluation indicators. This recommendation model uses a phased selection method to calculate the optimal objective parking lot. The first stage is screening which based on the users' subjective parking demands; the second stage is processing the candidate parking lots through multiple attribute decision making. Simulation experiments show that this model can effectively solve the problems encountered in the process of finding optimal parking lot, save the driver's parking time and parking costs and also improve the overall utilization of parking facilities to ease the traffic congestion caused by vehicles parked patrol.