The electrical and electronic ( E / E) architecture of modern automotive bus has started to evolve from a distributed architecturebased on CAN bus to a centralized architecture based on Automotive Ethernet with larger communication capacity,but the computationalresources are not evenly distributed in the vehicle,and the computational capacity of the centralized network?is significantly higher thanthat of other edge devices. Since the computational tasks of edge devices in smart cars are growing,in order to cope with the growingdemand of edge computational tasks and reduce the computational latency,an effective computational task offloading scheme is studied inthe centralized E / E architecture,and the communication characteristics of Automotive Ethernet are analyzed to offload the computationaltasks of in-vehicle domain controllers to the in-vehicle central computer. For the characteristics of AVB communication protocol of Automotive Ethernet,the delay model of computation offloading is obtained by combining data classification and traffic shaping algorithms,and then the objective optimization equation for minimizing the delay of edge computation tasks is established and iteratively solved byusing improved genetic algorithm,and finally the optimal parameters of task offloading are converged. The objective of reducing the in-vehicle computation task latency under the constraints of complex automotive conditions is achieved,and the simulation results show thatthe proposed method can effectively reduce the in - vehicle computation task latency and realize the full utilization of computationalresources on the in-vehicle network of centralized E / E architecture.