  With the rising demand of smart mobility, ride-hailing service is getting
popular in the urban regions. These services maintain a system for serving the
incoming trip requests by dispatching available vehicles to the pickup points.
As the process should be socially and economically profitable, the task of
vehicle dispatching is highly challenging, specially due to the time-varying
travel demands and traffic conditions. Due to the uneven distribution of travel
demands, many idle vehicles could be generated during the operation in
different subareas. Most of the existing works on vehicle dispatching system,
designed static relocation centers to relocate idle vehicles. However, as
traffic conditions and demand distribution dynamically change over time, the
static solution can not fit the evolving situations. In this paper, we propose
a dynamic future demand aware vehicle dispatching system. It can dynamically
search the relocation centers considering both travel demand and traffic
conditions. We evaluate the system on real-world dataset, and compare with the
existing state-of-the-art methods in our experiments in terms of several
standard evaluation metrics and operation time. Through our experiments, we
demonstrate that the proposed system significantly improves the serving ratio
and with a very small increase in operation cost.
