Intelligent Buses in a Loop Service: Emergence of No-Boarding and Holding Strategies

Vee-Liem Saw, Luca Vismara and Lock Yue Chew

Complexity, 2020, vol. 2020, 1-18

Abstract:

We study how intelligent buses serving a loop of bus stops learn a no-boarding strategy and a holding strategy by reinforcement learning. The no-boarding and holding strategies emerge from the actions of stay or leave when a bus is at a bus stop and everyone who wishes to alight has done so. A reward that encourages the buses to strive towards a staggered phase difference amongst them whilst picking up passengers allows the reinforcement learning process to converge to an optimal Q-table within a reasonable amount of simulation time. It is remarkable that this emergent behaviour of intelligent buses turns out to minimise the average waiting time of commuters, in various setups where buses move with the same speed or different speeds, during busy as well as lull periods. Cooperative actions are also observed, e.g., the buses learn to unbunch .

Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://downloads.hindawi.com/journals/8503/2020/7274254.pdf (application/pdf)
http://downloads.hindawi.com/journals/8503/2020/7274254.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:7274254

DOI: 10.1155/2020/7274254

Access Statistics for this article

More articles in Complexity from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().