Autonomous driving has been successfully implemented in such particular areas as logistics
distribution centers, container terminals, and university campuses. Robotaxi represents one …

Autonomous vehicles (AVs) are expected to operate on mobility-on-demand (MoD)
platforms because AV technology enables flexible self-relocation and system-optimal …

Within half a year, COVID-19 spreads to most countries in the world, as well as posed a
great threat to the public health of human beings. The implementation of non …

This paper presents a real-time dispatching model for electric autonomous vehicle (EAV)
taxis that combines mathematical programming and machine learning. The EAV taxi …

With the advent of 4G/5G mobile networks and vehicle-to-everything (V2X) technology, ride-
sharing platforms have brought unparalleled convenience to personal mobility. However …

The increasing popularity of on-demand ride-hailing services has introduced research
problems, including those related to fleet management. Many existing fleet management …

This paper addresses the taxi fleet dispatch problem, which is critical for many transport
service platforms such as Uber, Lyft, and Didi Chuxing. We focus on maximizing the revenue …

Shared Mobility-on-Demand (MoD) has tremendously reshaped the transportation patterns
in urban areas. The prosperity of Big Data and 5G network technology brings new …

This study addresses the inefficiencies in how idle taxis determine their cruising strategy,
which currently rely heavily on drivers' personal experiences. Such reliance often leads to …

To reduce the amount of empty taxies and make passengers more easily to take a taxi in
peak hours, a model-free deep reinforcement learning framework was proposed to dispatch …