Mobile participatory sensing (MPS) could benefit many application domains. A major domain is smart transportation, with applications such as vehicular traffic monitoring, vehicle routing, or driving behavior analysis. However, MPS’s success depends on finding a solution for querying large numbers of smart phones or vehicular systems, which protects user location privacy and works in real-time. This paper presents PAMPAS, a privacy-aware mobile distributed system for efficient data aggregation in MPS. In PAMPAS, mobile devices enhanced with secure hardware, called secure probes (SPs), perform distributed query processing, while preventing users from accessing other users’ data. A supporting server infrastructure (SSI) coordinates the inter-SP communication and the computation tasks executed on SPs. PAMPAS ensures that SSI cannot link the location reported by SPs to the user identities even if SSI has additional background information. Moreover, an enhanced version of the protocol, named PAMPAS+, makes the system robust even against advanced hardware attacks on the SPs. Hence, the risk of user location privacy leakage remains very low even for an attacker controlling the SSI and a few corrupted SPs. Our experimental results demonstrate that these protocols work efficiently on resource constrained SPs being able to collect the data, aggregate them, and share statistics or derive models in real-time.