  This paper studies the joint fleet sizing and charging system planning
problem for a company operating a fleet of autonomous electric vehicles (AEVs)
for passenger and goods transportation. Most of the relevant published papers
focus on intracity scenarios and adopt heuristic approaches, e.g., agent based
simulation, which do not guarantee optimality. In contrast, we propose a mixed
integer linear programming model for intercity scenarios. This model
incorporates comprehensive considerations of 1) limited AEV driving range; 2)
optimal AEV routing and relocating operations; 3) time-varying
origin-destination transport demands; and 4) differentiated operation cost
structure of passenger and goods transportation. The proposed model can be
computational expensive when the scale of the transportation network is large.
We then exploit the structure of this program to expedite its solution.
Numerical experiments are conducted to validate the proposed method. Our
experimental results show that AEVs in passenger and goods transportation have
remarkable planning and operation differences. We also demonstrate that
intelligent routing and relocating operations, charging system and vehicle
parameters, e.g., charging power, battery capacity, driving speed etc., can
significantly affect the economic efficiency and the planning results of an AEV
fleet.
