Except that often the driver does react and reduces the impact speed. Up here many sheep have been spared due to the vigilance of the driver.
Is your desired outcome for the train to slow down when there's an obstacle on the line, or for it to not slow down when there's an obstacle on the line? Because either can be done.
The sensor suites fitted to autonomous cars aim to tell the difference between an obstacle with which the vehicle may collide, and one merely moving parallel to its course. A similar setup could be fitted to a train. The detection range would need to be increased, but that's a solvable engineering problem. Real-time measurement of visibility and railhead conditions would allow for speed to be moderated to a safe level in a similar way to a human driver.
Likewise, if an autonomous car can tell the difference between a red traffic light and a green traffic light, an autonomous train can tell the difference between a red signal and a green signal. It can even be programmed with the necessary route data to tell it where to look, which isn't possible for cars - and is limited only by the storage available. Semaphore signals might be more of an issue, I'll grant.
Yes, there are still significant problems with obstacle detection. That applies to both rail and road. Silicon Valley tech investors have decided they want to see a return on their money from road vehicles, and have the political influence to force acceptance despite the issues. There isn't so much money riding on autonomous rail vehicles, and rail unions are strong enough to resist the pressure of capital. For now.