neural network - Hackaday 2024年11月27日
Full Self-Driving, on a Budget
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本文介绍了一个基于Arduino和机器学习的简易高速公路自动驾驶系统。该系统仅专注于方向盘控制,通过摄像头获取道路图像,并利用Arduino采集方向盘角度数据进行训练。通过数学处理和神经网络算法,该系统能够在特定高速公路上实现自动转向,并取得了令人惊喜的效果。虽然该项目尚处于概念验证阶段,且存在安全隐患,但它证明了使用低成本硬件和机器学习算法实现部分自动驾驶的可行性,并为未来更复杂系统的开发提供了参考。

🚗 该系统专注于高速公路场景下的自动转向,不涉及油门和刹车控制,旨在简化自动驾驶问题。

📷 系统使用摄像头获取道路图像,并利用Arduino采集方向盘角度数据,作为训练数据来源。

📊 训练数据经过数学处理,以区分方向盘的正常状态和转向事件,避免误判。

🧠 系统利用机器学习算法,特别是神经网络,对训练数据进行学习,从而实现自动转向控制。

🤔 该项目证明了利用低成本硬件和简单算法实现部分自动驾驶的可行性,但尚处于概念验证阶段,不建议实际应用。

Self-driving is currently the Holy Grail in the automotive world, with a number of companies racing to build general-purpose autonomous vehicles that can get from point A to point B with no user input. While no one has brought one to market yet, at least one has promised this feature and had customers pay for it, but continually moved the goalposts for delivery due to how challenging this problem turns out to be. But it doesn’t need to be that hard or expensive to solve, at least in some situations.

The situation in question is driving on a single stretch of highway, and only focuses on steering, so it doesn’t handle the accelerator or brake pedal input. The highway is driven normally, using a webcam to take images of the route and an Arduino to capture data about the steering angle. The idea here is that with enough training the Arduino could eventually steer the car. But first some math needs to happen on the training data since the steering wheel is almost always not turning the car, so the Arduino knows that actual steering events aren’t just statistical anomalies. After the training, the system does a surprisingly good job at “driving” based on this data, and does it on a budget not much larger than laptop, microcontroller, and webcam.

Admittedly, this project was a proof-of-concept to investigate machine learning, neural networks, and other statistical algorithms used in these sorts of systems, and doesn’t actually drive any cars on any roadways. Even the creator says he wouldn’t trust it himself, but that he was pleasantly surprised by the results of such a simple system. It could also be expanded out to handle brake and accelerator pedals with separate neural networks as well. It’s not our first budget-friendly self-driving system, either. This one makes it happen with the enormous computing resources of a single Android smartphone.

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自动驾驶 机器学习 Arduino 神经网络 高速公路
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