A Vehicular Crowd-sensing Incentive Mechanism for Temporal Coverage

Vehicular Crowd-sensing (VCS) is a new data collection paradigm that leverages the unique characteristics of vehicular mobility to collect sensing data. One of the main challenges for VCS is how to assign sensing tasks among participant so as to maintain the required Quality of Sensing Data (QoSD), while keeping participation profitable. We tackle this challenge by designing an incentive mechanism that encourages the collection of high QoSD, while improve participant utilities. The proposed mechanism includes a platform which post a set of sensing tasks and the associated rewards, and a set of participant vehicles equipped with sensors, who compete for these rewards. We model this competition as a non-cooperative game in which the set of vehicles are the players, and their trajectories are their strategies. Using open-street maps, SUMO vehicular traffic simulator, and extensive simulations, we show that our algorithm significantly outperforms a greedy approach in terms of QoSD, average vehicle utility, spatial coverage, and road utilization.