Many scenarios in mobility and traffic involve multiple different agents that need to cooperate
to find a joint solution. Recent advances in behavioral planning use Reinforcement Learning …

In recent years, with the rapid development of swarm control technology, the swarm system
has shown broad application prospects in military, civil, and other fields, which has gradually …

There is a growing interest in the optimization of vehicle fleets management in urban
environments. However, limited attention has been paid to the integrated optimization of …

While a variety of innovative travel modes, such as taxi service and ridesourcing service,
have been launched to improve the transportation efficiency, people still encounter travel …

In ride-sharing systems, platform providers aim to distribute the drivers in the city to meet
current and potential future demand and to avoid service cancellations. Ensuring such …

The popularity of ride-hailing platforms has significantly improved travel efficiency by
providing convenient and personalized transportation services. Designing an effective ride …

Great progress has been made in the domain of multi-agent reinforcement learning in recent
years. Most work concentrates on solving a single task by learning the cooperative …

Vehicle dispatching in the mobility-as-a-service (MaaS) market has gradually become a
situation of multi-service provider competition and coexistence. However, most existing …

Ride-hailing platforms have been facing the challenge of balancing demand and supply.
Existing vehicle reposition techniques often treat drivers as homogeneous agents and …

The rapid growth of Internet services dramatically drives the development of various
intelligent technologies. As an important composition, modern ride-hailing platforms allow …