Recently, the Research Institute for Trustworthy Autonomous Systems (RITAS) at the Southern University of Science and Technology and Streamax Technology Co., Ltd. formally entered into a strategic cooperation agreement, jointly establishing the “SUSTech Streamax X RITAS Joint Lab for Intelligent Driving Systems.” This collaboration marks a critical step for the Institute in advancing the deep industry integration of cutting-edge research in trustworthy autonomous systems and addressing major real-world challenges. Both parties will focus on the commercial vehicle sector, centering their efforts on the continuous validation and engineering implementation in real-world scenarios, jointly committed to promoting the global, large-scale, and trustworthy application of L4-level autonomous driving technology.
Building upon the visionary leadership of Turing Award winner Professor Joseph Sifakis, RITAS possesses profound theoretical expertise and influence in computational intelligence, trustworthy software, and autonomous driving. The team led by Professor Qi Hao, who is spearheading this collaboration, has achieved significant results and gained extensive experience in autonomous driving, unmanned aerial vehicles, robotics, and multi-agent control. The team has previously been deeply involved in core autonomous driving technology R&D for internationally renowned enterprises. This joint lab will pioneer a dual-driven paradigm centered on “real-world operational data” and a “verifiable technological framework,” establishing a complete closed loop from capability assessment and system optimization to model replication. It aims to deeply integrate RITAS’s theoretical innovations in trustworthy autonomous systems with the large-scale real-world scenarios and engineering capabilities brought by Streamax Technology, ultimately serving to enhance the efficiency and safety of real-world sectors such as commercial logistics and public transportation.
In the future, RITAS will leverage this joint innovation platform to actively participate in defining and resolving fundamental challenges related to trustworthiness, safety, and reliability faced by autonomous driving in real-world commercial scenarios.
