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Article

A Novel Crowdsourcing Model for Micro-Mobility Ride-Sharing Systems

1
Centre for Accident Research and Road Safety, Queensland University of Technology, Brisbane 4059, Australia
2
School of Economics and Management, Fuzhou University, Fuzhou 350108, China
3
Booz Allen Hamilton, Washington, DC 20003, USA
4
Civil Engineering Department, King Saud University, Riyadh 11362, Saudi Arabia
5
Engineering and Director of the Center for Sustainable Mobility, Virginia Tech Transportation Institute, Blacksburg, Virginia 24060, Australia
*
Author to whom correspondence should be addressed.
Academic Editor: Felipe Jiménez
Sensors 2021, 21(14), 4636; https://doi.org/10.3390/s21144636
Received: 9 May 2021 / Revised: 26 June 2021 / Accepted: 29 June 2021 / Published: 6 July 2021
(This article belongs to the Section Intelligent Sensors)
Substantial research is required to ensure that micro-mobility ride sharing provides a better fulfilment of user needs. This study proposes a novel crowdsourcing model for the ride-sharing system where light vehicles such as scooters and bikes are crowdsourced. The proposed model is expected to solve the problem of charging and maintaining a large number of light vehicles where these efforts will be the responsibility of the crowd of suppliers. The proposed model consists of three entities: suppliers, customers, and a management party responsible for receiving, renting, booking, and demand matching with offered resources. It can allow suppliers to define the location of their private e-scooters/e-bikes and the period of time they are available for rent. Using a dataset of over 9 million e-scooter trips in Austin, Texas, we ran an agent-based simulation six times using three maximum battery ranges (i.e., 35, 45, and 60 km) and different numbers of e-scooters (e.g., 50 and 100) at each origin. Computational results show that the proposed model is promising and might be advantageous to shift the charging and maintenance efforts to a crowd of suppliers. View Full-Text
Keywords: micro-mobility; ride-sharing; agent-based modelling; crowdsourcing micro-mobility; ride-sharing; agent-based modelling; crowdsourcing
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MDPI and ACS Style

Elhenawy, M.; Komol, M.R.; Masoud, M.; Liu, S.Q.; Ashqar, H.I.; Almannaa, M.H.; Rakha, H.A.; Rakotonirainy, A. A Novel Crowdsourcing Model for Micro-Mobility Ride-Sharing Systems. Sensors 2021, 21, 4636. https://doi.org/10.3390/s21144636

AMA Style

Elhenawy M, Komol MR, Masoud M, Liu SQ, Ashqar HI, Almannaa MH, Rakha HA, Rakotonirainy A. A Novel Crowdsourcing Model for Micro-Mobility Ride-Sharing Systems. Sensors. 2021; 21(14):4636. https://doi.org/10.3390/s21144636

Chicago/Turabian Style

Elhenawy, Mohammed, Mostafizur R. Komol, Mahmoud Masoud, Shi Q. Liu, Huthaifa I. Ashqar, Mohammed H. Almannaa, Hesham A. Rakha, and Andry Rakotonirainy. 2021. "A Novel Crowdsourcing Model for Micro-Mobility Ride-Sharing Systems" Sensors 21, no. 14: 4636. https://doi.org/10.3390/s21144636

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