You start with the easy case then gradually make the model more robust by increasing the difficulty.
What you’re suggesting is akin to trying to develop a jetliner before building propeller aircraft. Too hard too soon and you don’t really know what the target even is. Much learning happens before you can successfully execute a complex plan like that.
Plus it’s better from a business standpoint because you can achieve probability profitability sooner with your MVP.
This doesn't suit the narrative that self-driving cars are close to taking over. Up in the northeast US, drivers are actually a lot better at controlling their vehicles than bay area and southwestern drivers thanks to the fact that everyone has to drive in ice and snow.