In recent years, online ride-hailing services have emerged as an important component of
urban transportation system, which not only provide significant ease for residents' travel …

Applying and adapting deep reinforcement learning (DRL) to tackle transportation problems
is an emerging interdisciplinary field. While rapidly growing, a comprehensive and synthetic …

The vehicle dispatching system is one of the most critical problems in online ride-hailing
platforms, which requires adapting the operation and management strategy to the dynamics …

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 …

The vehicle routing problem (VRP) is a typical discrete combinatorial optimization problem,
and many models and algorithms have been proposed to solve the VRP and its variants …

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 …

We consider the problem of an operator controlling a fleet of electric vehicles for use in a
ride-hailing service. The operator, seeking to maximize profit, must assign vehicles to …

We present a new practical framework based on deep reinforcement learning and decision-
time planning for real-world vehicle repositioning on ride-hailing (a type of mobility-on …

In this paper, we present a comprehensive, in-depth survey of the literature on reinforcement
learning approaches to decision optimization problems in a typical ridesharing system …

Autonomous mobility-on-demand (AMoD) systems represent a rapidly developing mode of
transportation wherein travel requests are dynamically handled by a coordinated fleet of …