A Probabilistic Incentive Mechanism for Vehicular Crowdsensing System Based on Utility

This paper presents an Android-based vehicular crowdsensing system that integrates real-time data from the Google Maps API to enhance the efficiency of sensing tasks performed by autonomous vehicles (AVs). We model the system as a non-cooperative game, where AVs are rational players making strategic decisions. Our system incentivizes participant vehicles to deviate from their usual routes and visit designated Points of Interest (POIs). We provide detailed, step-by-step examples that illustrate the probabilistic framework that guides the vehicles decision-making on which POI to visit next. Finally, through extensive simulations, we demonstrate that our approach consistently outperforms others in terms of average participant utility and POI coverage.