Connected Autonomous Vehicles (CAVs) are Not-So-Futuristic. CAVs will be highly dynamic by intelligently exploiting multipath communication over several radio technologies, such as high-speed WiFi and 5G and beyond networks. Yet, the likelihood of data communication loss can be very high and/, or packets arrive at the destination not in correct working order due to erratic and mixed time-varying wireless links. Furthermore, the vehicular data traffic is susceptible to loss and delay variation,which recommends the need to investigate new multipath TCP(MPTCP) protocols for ultra-reliable low latency communication(URLLC) over such heterogeneous networks while reassuring CAVs’ needs. We undertake the challenge by jointly considering network coding and balanced linked adaptation for performing coupled congestion control across multiple wireless paths.Consequently, the proposed low delay MPTCP framework for connecting autonomous vehicles is efficient and intelligent by design. We conduct a rigorous convergence analysis of the MPTCP design framework. In summation, we provide a detailed mathematical study and demonstrate that the latency penalty for the URLLC-MPTCP developed over these networks becomes negligible when considering the possible benefits that multiple network convergence could offer. Our extensive emulation results demonstrate all these lucrative features of URLLC-MPTCP.