Privacy of Smart Traffic Lights Systems

Abstract

Smart traffic lights systems (STLSs) are a promising approach to improve traffic efficiency at intersections. They rely on the information sent by vehicles via C2X communication (like in cooperative awareness messages (CAMs)) at the managed intersection. While there exists a large body of work on privacy-enhancing technologies (PETs) for cooperative Intelligent Transport Systems (cITS) in general, such PETs like changing pseudonyms often impact the performance of cITS applications. This paper analyzes the extent to which different PETs affect the performance of two types of STLSs, a phase-based and a reservation-based STLS. These are implemented in SUMO and combined with four different PETs. Through extensive simulations we then investigate the impact of those PETs on STLS performance metrics like time loss, waiting time, fuel consumption, and average velocity. Our analysis shows that the impact of PETs on performance varies greatly depending on the type of STLS. Finally, we propose a hybrid STLS which is a combination of the two STLS types as a potential solution for limiting the negative impact of PETs on performance.