Traffic monitoring services show great potential for improving traffic efficiency in vehicular networks. With the assistance of 5G innovation, vehicles can report information such as driving misbehavior and traffic status to the traffic monitoring server which then returns feedback to the network to enhance the efficiency of traffic management. However, some challenging issues in information reporting need to be addressed first. Trivial reported information significantly increases the workload of the server. Moreover, a server is difficult to distinguish the truth of reported messages. As a result, the server is incapable of returning immediate feedback to the network, thereby reducing the quality of traffic services. Meanwhile, uploading location-based information to the server exposes vehicles' privacy. Although some existing techniques such as trust management benefit information reporting, a complete framework is still missing. In this paper, we propose an information reporting framework for solving both efficiency and privacy issues. Specifically, messages are probabilistically reported to the server depending on their importance. Furthermore, the DAG-based blockchain ensures that messages reported for a specific event are all gathered in the same ledger. We also present a scheme based on the geo-indistinguishability to protect the location privacy of vehicles. Extensive experiments demonstrate that the proposed framework preserves the location privacy of vehicles and achieves efficiency with acceptable overheads.