A Data-Driven System for Optimal Vehicle Fleet Dimensioning and Real-Time Dispatching Based on Shareability Networks

Real-time, point-to-point, on-demand ride dispatching system. The system provides for optimal operation including a fleet dimensioning module for determining an optimal number of vehicles in a fleet needed to serve a collection of trip requests, and a vehicle dispatching module for dispatching the fleet of vehicles to serve a selected number of trip requests. The fleet dimensioning module employs a shareability network to model trip requests that can be served by a same vehicle to find the minimum number of vehicles in the fleet to serve all trip requests in the collection of trip requests.

Researchers

Paolo Santi / Giovanni Resta / Carlo Ratti

Departments: Senseable City Lab
Technology Areas: Artificial Intelligence (AI) and Machine Learning (ML) / Industrial Engineering & Automation: Logistics

  • data-driven system for optimal vehicle fleet dimensioning and real-time dispatching based on shareability networks
    United States of America | Published application
  • a data-driven system for optimal vehicle fleet dimensioning, ride-sharing, and real-time dispatching based on shareability networks
    European Patent Convention | Published application
  • a data-driven system for optimal vehicle fleet dimensioning, ride-sharing, and real-time dispatching based on shareability networks
    Russian Federation | Pending
  • a data-driven system for optimal vehicle fleet dimensioning and real-time dispatching based on shareability networks
    Mexico | Published application
  • a data-driven system for optimal vehicle fleet dimensioning and real-time dispatching based on shareability networks
    China | Published application
  • a data-driven system for optimal vehicle fleet dimensioning, ride-sharing, and real-time dispatching based on shareability networks
    Indonesia | Published application

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