In an automated steering system of the self-driving vehicles, the steering wheel angle is measured by the absolute angular displacement sensors or relative angle sensors. However, these sensors either encompass global navigation satellite systems (GNSS)/gyroscope – Micro Electromechanical-Sensor (MEMS) based solutions or comprise of the complex gear-based mechanical structure which results in latency and additive bias in the accumulative steering angle assessment. To address these issues, we propose a novel steering angle assessment system based on enhanced gear mechanism along with the adapted rotation paradigm for the customized self-driving vehicles. Additionally, a digital signal processing system has been introduced to resolve the issues in the identification of absolute central and max-bounding steering wheels position in self-driving vehicles. In assistance with the proposed mechanism, an algorithm has also been proposed to optimize the computed steering angle to minimalize the effect of additive bias in the accuracy. The proposed mechanism has been installed in the customized self-driving testbed vehicle and rigor validation has been performed in the straight and curvy road scenarios. Finally, the comparison study has been carried out between the conventional relative sensor and the proposed mechanism to show the accuracy and effectiveness of the proposed mechanism in terms of error rate, stability, and deviation.

在自动驾驶汽车的自动转向系统中，方向盘角度是通过绝对角位移传感器或相对角度传感器测量的。但是，这些传感器要么包含基于全球导航卫星系统（GNSS）/陀螺仪–基于微机电传感器（MEMS）的解决方案，要么包含基于复杂齿轮的机械结构，这会导致累积转向角评估中的等待时间和附加偏差。为了解决这些问题，我们提出了一种新颖的转向角评估系统，该系统基于增强型齿轮机构以及针对定制自动驾驶车辆的自适应旋转范例。此外，引入了数字信号处理系统来解决自动驾驶车辆中绝对中央和最大边界方向盘位置的识别问题。在所提出的机制的辅助下，还提出了一种算法来优化计算的转向角，以最大程度地减小加性偏差对精度的影响。拟议的机制已安装在定制的自动驾驶试验台车辆中，并已在直线和弯曲的道路场景中进行了严格的验证。最后，在传统的相对传感器和所提出的机构之间进行了比较研究，以从错误率，稳定性和偏差方面证明所提出的机构的准确性和有效性。还提出了一种算法来优化计算的转向角，以最大程度地减小加性偏差对精度的影响。拟议的机制已安装在定制的自动驾驶试验台车辆中，并已在直线和弯曲的道路场景中进行了严格的验证。最后，在传统的相对传感器和所提出的机构之间进行了比较研究，以从错误率，稳定性和偏差方面证明所提出的机构的准确性和有效性。还提出了一种算法来优化计算的转向角，以最大程度地减小加性偏差对精度的影响。拟议的机制已安装在定制的自动驾驶试验台车辆中，并已在直线和弯曲的道路场景中进行了严格的验证。最后，在传统的相对传感器和所提出的机构之间进行了比较研究，以从错误率，稳定性和偏差方面证明所提出的机构的准确性和有效性。