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

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Area of Science:

  • Urban planning and transportation science.
  • Crowdsourcing and the sharing economy.
  • Sustainable mobility solutions.

Background:

  • Current micro-mobility ride-sharing systems face challenges in efficiently managing charging and maintenance for large fleets of light vehicles like e-scooters and e-bikes.
  • Ensuring user needs are met requires innovative operational models for shared electric mobility.
  • The need for sustainable and scalable solutions in urban transportation is growing.

Purpose of the Study:

  • To propose and evaluate a novel crowdsourcing model for micro-mobility ride-sharing systems.
  • To address the operational challenges of charging and maintaining shared light vehicles by leveraging a supplier network.
  • To assess the feasibility and potential benefits of a crowdsourced approach for shared e-scooter and e-bike fleets.

Main Methods:

  • Development of a three-entity crowdsourcing model involving suppliers, customers, and a management party.
  • Agent-based simulation using a dataset of over 9 million e-scooter trips in Austin, Texas.
  • Testing the model with varying parameters, including maximum battery ranges (35, 45, 60 km) and fleet sizes (50, 100 e-scooters).

Main Results:

  • The proposed crowdsourcing model demonstrates promise in managing shared micro-mobility resources.
  • Simulation results indicate the potential for shifting charging and maintenance responsibilities to a crowd of suppliers.
  • The model's effectiveness is influenced by factors such as battery range and the number of available e-scooters.

Conclusions:

  • The crowdsourcing model offers a viable and potentially advantageous solution for the operational complexities of micro-mobility ride sharing.
  • Decentralizing charging and maintenance tasks to suppliers can enhance the efficiency and scalability of shared electric scooter and bike systems.
  • Further research and implementation are warranted to fully realize the benefits of this crowdsourced approach for urban mobility.