Incentive Mechanism for Collaborative Sensing in Intelligent Transportation Systems with Mixed Traffic: A Stackelberg Game Approach

Intelligent Transportation Systems (ITS) simultaneously collects driving data of both the Intelligent Connected Ve-hicles (ICVs) and non-ICVs for traffic management in the mixed traffic environment. To this end, a set of ICVs can be scheduled to cooperatively sense a target non-ICV and collect the traffic data to a roadside unit (RSU). An incentive mechanism is necessitated to provide proper incentives for the selfish ICVs. In this paper, we resolve the incentive problem of collaborative sensing in the ITS with the mixed traffic, according to a Stackelberg game approach. We investigate the strategic interactions of the RSU and ICVs in which there exist leader-follower relationships among them. After that, we analyze the Stackelberg equilibrium, and derive the close-form solution of the Stackelberg game. Finally, we provide numerical results to demonstrate the effectiveness and efficiency of the proposed Stackelberg game.