Vehicular Path Planning for Balancing Traffic Congestion Cost and Fog Computing Reward: A Routing Game Approach.

With the rapid development of Internet-of-Vehicle (IoV) technologies (such as autonomousdriving and electrical vehicles), more and more smart vehicles are emerging on the road, resulting in not only traffic congestion, but also a waste of resource. In this paper, we study a novel vehicular path planning scheme, which aims to well balance each vehicle’s traffic congestion cost (incurred by the travelling delay between its origin and destination) and fog computing reward (obtained from providing its redundant computing resource to road-side units). Different from the existing work, we consider that vehicles with different driving speeds contribute differently to the traffic congestion (e.g., slower vehicles may lead to more severe traffic congestion), and at the same time they can act as mobile fog nodes while driving in exchange for certain rewards. To characterize the competition among multiple vehicles due to their strategic path planning and investigate the inherent tradeoff between the congestion cost and computing reward for each individual, an atomic pure strategy routing game is formulated. Then, we analyze the equilibrium performance and propose an efficient algorithm to derive the corresponding solution. Theoretical and simulation results examine the feasibility of our proposed scheme, and demonstrate its superiority over the counterparts.