This paper investigates the neuroadaptive fault-tolerant control of nonlinear vehicular platoon with unmodeled dynamics, actuator faults and distance restrictions. To address the coexisting challenges, this paper develops a neural network-based adaptive fault-tolerant control (FTC) scheme based on Barrier Lyapunov Function (BLF). The proposed architecture enables autonomous expansion of performance bounds when spacing errors approach the constraints defined by BLFs, thereby providing supplementary regulatory margin for the control system. This mechanism effectively addresses the limitations of traditional Prescribed Performance Control (PPC) in fixed boundary configuration.