Multi-agent Service Area Adaptation for Ride-Sharing Using Deep Reinforcement Learning

Naoki Yoshida, Itsuki Noda, Toshiharu Sugawara

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

This paper proposes a method for adaptively assigning service areas to self-driving taxi agents in ride-share services by using a centralized deep Q-network (DQN) and demand prediction data. A number of (taxi) companies have participated in ride-share services with the increase of passengers due to the mutual benefits for taxi companies and customers. However, an excessive number of participants has often resulted in many empty taxis in a city, leading to traffic jams and energy waste problems. Therefore, an effective strategy to appropriately decide the service areas where agents, which are self-driving programs, have to wait for passengers is crucial for easing such problems and achieving the quality service. Thus, we propose a service area adaptation method for ride share (SAAMS) to allocate service areas to agents for this purpose. We experimentally show that the SAAMS manager can effectively control the agents by allocating their service areas to cover passengers using demand prediction data with some errors. We also evaluated the SAAMS by comparing its performance with those of the conventional methods.

本文言語English
ホスト出版物のタイトルAdvances in Practical Applications of Agents, Multi-Agent Systems, and Trustworthiness. The PAAMS Collection - 18th International Conference, PAAMS 2020, Proceedings
編集者Yves Demazeau, Tom Holvoet, Juan M. Corchado, Stefania Costantini
出版社Springer
ページ363-375
ページ数13
ISBN(印刷版)9783030497774
DOI
出版ステータスPublished - 2020
イベント18th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2020 - L’Aquila, Italy
継続期間: 2020 10 72020 10 9

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12092 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference18th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2020
CountryItaly
CityL’Aquila
Period20/10/720/10/9

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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