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Autonomous driving systems, enabled by artificial intelligence and sensing technologies, empower vehicles to navigate autonomously. However, during rainy weather, raindrops may interfere with the vehicle's sensors, leading to inaccuracies in object detection and recognition, which can compromise the safety of autonomous driving. To address these challenges, the magnetic guided autonomous driving system emerges as a promising solution due to its potential to mitigate the impact of rainy weather on autonomous vehicles. Currently, magnetic guided autonomous vehicles rely on continuous or short-distance magnetic tracks for directional control, limiting their practical applicability. To overcome this limitation, we propose an improved technology that not only addresses issues of poor maneuverability but also preserves the inherent advantages of magnetic guided autonomous driving.

In recent years, many attentions have been paid on global environmental protection and energy saving; more people, therefore, have chosen bikes for commuting to work or school. For longer distance transportation and less effort, electric power assist bikes have re-entered the market. Due to regulation of some countries, electric bikes that must be pedaled were developed. These machines utilize the pedals as the dominant form of propulsion, with the motor used only to give extra assistance when needed for hills or long journeys. The ratio of electric power to human power may affect the riding feel. As a result, a torque sensor, which detects the pedaling force, is crucial in this application. This paper proposes a new design of torque sensor by way of twist angle measurement. It is composed of a torsion bar, input and output shaft with ring magnets and Hall sensors to achieve contactless sensing.