Combinatorial optimization meets reinforcement learning: Effective taxi order dispatching at large-scale
Ride hailing has become prevailing. Central in ride hailing platforms is taxi order
dispatching which involves recommending a suitable driver for each order. Previous works …
dispatching which involves recommending a suitable driver for each order. Previous works …
Context-aware taxi dispatching at city-scale using deep reinforcement learning
Proactive taxi dispatching is of great importance to balance taxi demand-supply gaps among
different locations in a city. Recent advances primarily rely on deep reinforcement learning …
different locations in a city. Recent advances primarily rely on deep reinforcement learning …
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 …
An integrated reinforcement learning and centralized programming approach for online taxi dispatching
Balancing the supply and demand for ride-sourcing companies is a challenging issue,
especially with real-time requests and stochastic traffic conditions of large-scale congested …
especially with real-time requests and stochastic traffic conditions of large-scale congested …
A robust deep reinforcement learning approach to driverless taxi dispatching under uncertain demand
With the progressive technological advancement of autonomous vehicles, taxi service
providers are expected to offer driverless taxi systems that alleviate traffic congestion and …
providers are expected to offer driverless taxi systems that alleviate traffic congestion and …
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 …
Fed-LTD: Towards cross-platform ride hailing via federated learning to dispatch
Learning based order dispatching has witnessed tremendous success in ride hailing.
However, the success halts within individual ride hailing platforms because sharing raw …
However, the success halts within individual ride hailing platforms because sharing raw …
Ride-hailing order dispatching at didi via reinforcement learning
Order dispatching is instrumental to the marketplace engine of a large-scale ride-hailing
platform, such as the DiDi platform, which continuously matches passenger trip requests to …
platform, such as the DiDi platform, which continuously matches passenger trip requests to …
Multi-agent reinforcement learning for order-dispatching via order-vehicle distribution matching
Improving the efficiency of dispatching orders to vehicles is a research hotspot in online ride-
hailing systems. Most of the existing solutions for order-dispatching are centralized …
hailing systems. Most of the existing solutions for order-dispatching are centralized …
Large-scale order dispatch in on-demand ride-hailing platforms: A learning and planning approach
We present a novel order dispatch algorithm in large-scale on-demand ride-hailing
platforms. While traditional order dispatch approaches usually focus on immediate customer …
platforms. While traditional order dispatch approaches usually focus on immediate customer …