  Package delivery via the UAVs is a promising transport mode to provide
efficient and green logistic services, especially in urban areas or complicated
topography. However, the energy storage limit of the UAV makes it difficult to
perform long-distance delivery tasks. In this paper, we propose a novel
multimodal logistics framework, in which the UAVs can call on ground vehicles
to provide hitch services to save their own energy and extend their delivery
distance. This multimodal logistics framework is formulated as a two-stage
model to jointly consider the incentive mechanism design for ground vehicles
and path planning for UAVs. In Stage I, to deal with the motivations for ground
vehicles to assist UAV delivery, a dynamic pricing scheme is proposed to best
balance the vehicle response time and payments to ground vehicles. It shows
that a higher price should be decided if the vehicle response time is long to
encourage more vehicles to offer a ride. In Stage II, the task allocation and
path planning of the UAVs over traffic network is studied based on the vehicle
response time obtained in Stage I. To address pathfinding with restrictions and
the performance degradation of the pathfinding algorithm due to the rising
number of conflicts in multi-agent pathfinding, we propose the suboptimal
conflict avoidance-based path search (CABPS) algorithm, which has polynomial
time complexity. Finally, we validate our results via simulations. It is shown
that our approach is able to increase the success rate of UAV package delivery.
Moreover, we estimate the delivery time of the UAV in a pessimistic case, it is
still twice as fast as the delivery time of the ground vehicle only.
