SCP-Tree: Finding Multiple Nearest Parking Spots With Minimal Group Travel Cost

Jine Tang,Weijing Liu,Yupeng Wang,Xiling Luo,Zhangbing Zhou

doi:10.1109/access.2021.3131229

Abstract

Finding the nearest parking location in road networks is one of the most commonly faced challenges in everyday life of green transportation. A main challenge faced by the state-of-the-art existing parking allocation methods is to optimally offer the nearest parking location for a group of m users at the cost of minimal overall traveling time to ensure the traffic and environmental sustainability. In this article, we model it as a Multiple Nearest Parking Location Allocation (MNPLA) problem, and devise a spatial index tree, called SCP-tree, to accelerate the nearest parking location allocation within the users’ time constraints. During the search process in SCP-tree, we build a pruning strategy relevant to the Geographical Preference Estimation, travel time and parking capacity to determine which branch to visit so that the search accuracy can be improved. Considering the users’ behaviors are often impacted by the geographical location and some personalized attribute information, we set the user priority based on them to help the parking officer determine the allocation sequence. We evaluate our allocation scheme using large real-world dataset with on-street parking sensor data, and extensive experimental results reveal (i) a minimum improvement of 15.9%, 1.4%, 96.9%, 160% in parking allocation time, average traveling time, I/O cost and service utility compared to the progressive methods, and (ii) a minimum improvement of 8.9%, 11.1%, 78.2%, 714% in parking allocation time, average traveling time, I/O cost and service utility compared to the baseline methods.

Highlights

In order to reduce energy uses and cut emissions that contribute to the climate and environment change, parking allocation is an important aspect required to be considered in green vehicular transportation, as search for parking by drivers is a significant contributor to the congestion in cities and generates a lot of greenhouse gas emissions [1], [2]
We propose User Priority setting based on the personalized attribute and distance, combined with the estimation of geographical location proximity developed for each user, to maximize the benefit of all users
In this article, we propose a novel parking location allocation scheme for mobile users to support the sustainability in green transportation systems

Summary

Introduction

In order to reduce energy uses and cut emissions that contribute to the climate and environment change, parking allocation is an important aspect required to be considered in green vehicular transportation, as search for parking by drivers is a significant contributor to the congestion in cities and generates a lot of greenhouse gas emissions [1], [2]. Drivers spend a great deal of time on searching for parking and on leaving sooner or later due to the anticipated parking and congestion problems. It is not easy to maximize the benefits of all the mobile users for finding the available parking locations to ensure the sustainability of urban environments [3], which is viewed as a change that improves the quality of life and conserves the time and natural resources. Several existing works [4]–[7] compute

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Conclusion