MOVI: A model-free approach to dynamic fleet management
T Oda, C Joe-Wong - IEEE INFOCOM 2018-IEEE Conference …, 2018 - ieeexplore.ieee.org
Modern vehicle fleets, eg, for ridesharing platforms and taxi companies, can reduce
passengers' waiting times by proactively dispatching vehicles to locations where pickup …
passengers' waiting times by proactively dispatching vehicles to locations where pickup …
Supply-demand-aware deep reinforcement learning for dynamic fleet management
Online ride-hailing platforms have reduced significantly the amounts of the time that taxis are
idle and that passengers spend on waiting. As a key component of these platforms, the fleet …
idle and that passengers spend on waiting. As a key component of these platforms, the fleet …
Real-time dispatching of large-scale ride-sharing systems: Integrating optimization, machine learning, and model predictive control
This paper considers the dispatching of large-scale real-time ride-sharing systems to
address congestion issues faced by many cities. The goal is to serve all customers (service …
address congestion issues faced by many cities. The goal is to serve all customers (service …
Deep reinforcement learning for multi-driver vehicle dispatching and repositioning problem
Order dispatching and driver repositioning (also known as fleet management) in the face of
spatially and temporally varying supply and demand are central to a ride-sharing platform …
spatially and temporally varying supply and demand are central to a ride-sharing platform …
Deeppool: Distributed model-free algorithm for ride-sharing using deep reinforcement learning
AO Al-Abbasi, A Ghosh… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
The success of modern ride-sharing platforms crucially depends on the profit of the ride-
sharing fleet operating companies, and how efficiently the resources are managed. Further …
sharing fleet operating companies, and how efficiently the resources are managed. Further …
Deep reinforcement learning with knowledge transfer for online rides order dispatching
Ride dispatching is a central operation task on a ride-sharing platform to continuously match
drivers to trip-requesting passengers. In this work, we model the ride dispatching problem as …
drivers to trip-requesting passengers. In this work, we model the ride dispatching problem as …
Value function is all you need: A unified learning framework for ride hailing platforms
Large ride-hailing platforms, such as DiDi, Uber and Lyft, connect tens of thousands of
vehicles in a city to millions of ride demands throughout the day, providing great promises …
vehicles in a city to millions of ride demands throughout the day, providing great promises …
Mobility-aware dynamic taxi ridesharing
Taxi ridesharing becomes promising and attractive because of the wide availability of taxis
in a city and tremendous benefits of ridesharing, eg, alleviating traffic congestion and …
in a city and tremendous benefits of ridesharing, eg, alleviating traffic congestion and …
Can sophisticated dispatching strategy acquired by reinforcement learning?-a case study in dynamic courier dispatching system
Y Chen, Y Qian, Y Yao, Z Wu, R Li, Y Zhou… - arXiv preprint arXiv …, 2019 - arxiv.org
In this paper, we study a courier dispatching problem (CDP) raised from an online pickup-
service platform of Alibaba. The CDP aims to assign a set of couriers to serve pickup …
service platform of Alibaba. The CDP aims to assign a set of couriers to serve pickup …
Coride: joint order dispatching and fleet management for multi-scale ride-hailing platforms
How to optimally dispatch orders to vehicles and how to trade off between immediate and
future returns are fundamental questions for a typical ride-hailing platform. We model ride …
future returns are fundamental questions for a typical ride-hailing platform. We model ride …