https://www.youtube.com/watch?v=g6bOwQdCJrc
For example look at this section: https://youtu.be/g6bOwQdCJrc?t=1370
Also if you look into it you will find Google's self-driving car project ran into similar issues. They upgraded the radar in response to the issues rather than removing it, but there are actual issues.
Vision only was better than radar plus vision in their stack. For real world situations that frequently come up in driving radar wasn't worth it. The theoretical accuracy of the sensor fusion didn't happen in practice because in practice you needed to have vision tell you when sensor fusion wasn't going to be accurate. It isn't naive sensor fusion as in toy math models of sensor fusion. So when there was a disagreement you needed to go with vision. Yet vision was already able to predict both the failure of and the actual result of radar. In theory, you could just have done the more complicated sensor fusion. In practice, the relative advantage of improving other parts of the vision stack far exceeded improving the sensor fusion. Over time one would expect the relative advantage to change as other improvements were made such that this was no longer true. That doesn't mean the time at the decision wasn't correct, it just means people who evaluate it with future changes already in place are suffering from hindsight bias/committing an anachronistic fallacy.