Parking Lot Allocation Based on Matching Theory using Prediction-based Optimal Vehicle Routing

T. Nakazato, T. Namerikawa

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

The purpose of this paper is to relax traffic congestion caused by the decrease in vehicle speed in case of a driver searching for a parking lot in traffic network, by using Smart Parking System. Smart Parking System is a system that allocates parking lot considering both the driver's preference and the parking lot manager's preference in advance. At that time, driver should know the optimal route and its time from currrent location to each parking lot. In this paper, Smart Parking System consider the road condition in traffic network and present the driver time by the optimal route from the driver's current location to each parking lot. Then, the parking lot allocation is determined by using matching theory considering both the driver's preference including information of optimal route and its time and the parking lot manager's preference. Finally, the effectiveness is confirmed by numerical simulations and results of parking lot allocation using optimal vehicle routing.

Original languageEnglish
Title of host publicationICCAS 2019 - 2019 19th International Conference on Control, Automation and Systems, Proceedings
PublisherIEEE Computer Society
Pages1004-1009
Number of pages6
ISBN (Electronic)9788993215182
DOIs
Publication statusPublished - 2019 Oct
Event19th International Conference on Control, Automation and Systems, ICCAS 2019 - Jeju, Korea, Republic of
Duration: 2019 Oct 15 → 2019 Oct 18

Publication series

NameInternational Conference on Control, Automation and Systems
Volume2019-October
ISSN (Print)1598-7833

Conference

Conference19th International Conference on Control, Automation and Systems, ICCAS 2019
CountryKorea, Republic of
CityJeju
Period19/10/15 → 19/10/18

Keywords

  • ITS
  • Smart Parking System
  • matching theory
  • optimal routing algorithm
  • parking lot allocation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

UN SDGs

This output contributes to the following Sustainable Development Goal(s)

  • SDG 9 - Industry, Innovation, and Infrastructure

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