Abstract: Aiming at the problem of supplementing the blind spots of intelligent driving vehicle sensors in dynamic traffic flow, a perception blind spot model in dynamic traffic flow is constructed to analyze sensor blind spots, and a sensor sharing node selection strategy based on the entropy weight method is proposed to select suitable vehicle nodes for blind spots supplement. Experimental results show that the dynamic traffic flow sensing blind spots model has a good representation of actual traffic scenarios. The nodes selected by the sensor sharing node selection strategy based on the entropy weight method can effectively supplement the vehicle sensing blind spots, expand the vehicle's perception range, and improve driving safety of intelligent driving vehicles.