And if you are currently an undistracted, alert, sober driver [...], your chances of an accident during this particular drive are notably lower.

Lower maybe. But they are still in the order of 1:10^6.

The border between the categories 1:100, 1:10^6 and 1:10^10 is - well - no border but continuous. The categorization into three rough areas expresses insufficient experience with all the shades in between. I don't mean that offensively. Dealing with risks appears to be normally done by the subconscious. Lifting it into the conscious is sensible but just assigning three categories will not do. Neither will do assigning words to more differentiated categories like in Lojban ( http://lesswrong.com/lw/9jv/thinking_bayesianically_with_lojban/ ).

Real insight comes from training. Training with a suitable didactic strategy. One strategy obviously being to read the sequences as that forces you to consider lots of different more or less unlikely situations.

What I am missing is a structured way to decompose these odds. 1:10^6 for a car accident in a 100 mile drive is arbitrary in so far as you can decompose it into either a 10 meter drive (say out of the parking lot) which then immediately moves the risk formally into the latter category. Or alternatively dying in a car accident in your life time which moves it into the first category.

So why is it that a 100 mile drive was chosen?