Self-driving technology is advancing rapidly---albeit with significant challenges and
limitations. This progress is largely due to recent developments in deep learning algorithms.
To date, however, there has been no systematic comparison of how different deep learning
architectures perform at such tasks, or an attempt to determine a correlation between
classification performance and performance in an actual vehicle, a potentially critical factor
in developing self-driving systems. Here, we introduce the first controlled comparison of …