【报告摘要】The intelligence of modern road traffic systems has been significantly enhanced by advances in network, communication, and sensing technologies. Autonomous vehicles (AVs) play an increasingly vital role in improving traffic mobility and sustainability in smart cities. In mixed traffic scenarios, AVs can help alleviate congestion, enhance fuel efficiency, and reduce emissions by smoothing traffic flow. This talk addresses the traffic flow smoothing problem, where AVs guide traffic by adjusting their motion based on available information. To reduce communication overhead, an intermittent vehicle-to-vehicle communication mechanism (I2CM) is introduced, limiting data exchange to discrete intervals. This results in a random sparse structure constraint (RSSC) in the control design. We formulate the cruise control problem under I2CM as a distributed optimal control problem with RSSC, and develop a gradient-based distributed algorithm for its solution. A case study on a connected vehicle system (CVS) demonstrates the effectiveness of the proposed method.