The response speed of the intelligent systems embedded in an autonomous vehicle is crucial for its correct operation and reduction of the risks on the road derived from autonomous driving. For that reason, it is necessary to optimize the algorithms that process the data from the sensors; with that aim the Field-Programmable Gate Arrays (FPGAs) offer the possibility of parallelizing the tasks to be carried out by mentioned systems, accelerating their response and improving their performance. In this regard, this paper introduces a fuzzy absolute position correction system, which corrects the latitude and longitude data registered from a GPS Pmod sensor and its implementation on a FPGA to speed up the correction results. A necessary comparison of the algorithm execution time on different platforms such as: A Raspberry pi 4 model B, a personal computer (PC) with Ubuntu 18.04.4 64-bit and the FPGA model, was performed to validate the results and the effectiveness of the implementation. The correction system was validated in software and hardware on 4 different routes, each of them with a large number of samples. The results were highly similar in the three platforms; however, the FPGA-based implementation offers a speed up of 40000x compared to software-based implementations.

嵌入在自动驾驶汽车中的智能系统的响应速度对其正确运行和降低自动驾驶带来的道路风险至关重要。因此，有必要优化处理来自传感器的数据的算法；为此，现场可编程门阵列 (FPGA) 提供了将上述系统执行的任务并行化的可能性，从而加速了它们的响应并提高了它们的性能。对此，本文介绍了一种模糊绝对位置校正系统，该系统对从 GPS Pmod 传感器注册的经纬度数据进行校正，并在 FPGA 上实现，以加快校正结果。不同平台上算法执行时间的必要比较，例如：A Raspberry pi 4 model B，使用 Ubuntu 18.04.4 64 位和 FPGA 模型的个人计算机 (PC) 执行以验证结果和实现的有效性。校正系统在 4 条不同路线上的软件和硬件中进行了验证，每条路线都有大量样本。三个平台的结果高度相似；然而，与基于软件的实现相比，基于 FPGA 的实现速度提高了 40000 倍。