The mutual interference between frequency modulated continuous wave (FMCW) radars seriously affects autonomous driving. The interference will cause a short-duration pulse-like signal, which contains several change points in the time domain. The change-point detection method called bottom-up segmentation (BOTUP) is applied to deal with a short duration pulse-like signal, which has excellent detection accuracy. However, the serial processing of BOTUP will cause considerable delay, which is not conducive to real-time detection of automatic driving. In this paper, an accelerated architecture of BOTUP (ACC-BOTUP) based on field-programmable gate array (FPGA) is proposed. As BOTUP has segmented characteristics and without data dependency between the cost functions, a parallel structure is proposed to reduce the latency. Further, a pipeline structure is proposed to execute the operations of the cost functions in an overlapping manner. Compared with the original BOTUP (O-BOTUP), the latency of ACC-BOTUP is reduced by 82%, which is more suitable for real-time detection in autonomous driving.