Travelling salesman is a largely solved problem, but I'd say this problem is larger.
As soon as humans and the real world are involved, seemingly contradictory criteria need to be met.
Algorithms like A* search may not be able to capture these criteria robustly enough.
Example: a driver may be assigned the optimal route, but because they are human will not want to sit and wait for 15 minutes between several of their rides
A* is great for path finding but it's not a global panacea for all subproblems related to ridesharing
This is true, however these known criteria can be added in, thats the whole point of the heuristic in A*.
Likely one of Uber/Lyfts greatest strengths in their algos is discovering the E[X] of those heuristics. This could probably be captured from the human dispatchers as well.
As soon as humans and the real world are involved, seemingly contradictory criteria need to be met.
Algorithms like A* search may not be able to capture these criteria robustly enough.
Example: a driver may be assigned the optimal route, but because they are human will not want to sit and wait for 15 minutes between several of their rides
A* is great for path finding but it's not a global panacea for all subproblems related to ridesharing