Making self-driving cars for mass consumption is difficult. Why?
1. The software. Problems involving computer vision and perception, processing low resolution information and decision-making.
2. The sensors. Far from solved in ambiguous environments. It seems like the current approach is a cocktail of sensors that mitigate failure or low resolution in any particular type of sensor and environment. How do these collections of sensors handle grime, snow and rain?
3. Cars are dangerous, which creates a whole set of regulatory and ethical questions, as well as requiring extremely high precision for (1) and (2.)
4. Cars themselves are difficult and costly to manufacture. They require hundreds of thousands of parts to be acquired on time, pieced together and tested– this is no trivial feat.
But what if you didn’t have to worry about (3) and (4)?
Well, you wouldn’t have a car. But you might have something very useful that can be built today, on the back of the expertise and technology that has been developed in the labs of Stanford, CMU, Google, BMW, Mercedes, Volkswagen and many more. The expertise developed in these labs manifests itself not just in the final self-driving vehicle, but in its byproduct as well: papers, algorithms, sensors, software libraries and people.
Chris Anderson has a wonderful phrase, “the peace dividends of the smartphone wars.” What he means is this: Apple, Google, Samsung and others have invested billions of dollars in smartphones, and the benefits of their investments have far-reaching effects outside of our pocket supercomputers. Think better, faster and cheaper ARM processors, newly commoditized sensors (cameras, GPS, accelerometers) and SSDs that are cheaper, more reliable and perform better. The Raspberry Pi would not have been possible without the smartphone, nor would the array of smart wristbands or drones that are available today.
What, in essence, you might be able to do for self-driving cars is harvest the dividend before the war is over. While the complexity of self-driving cars (regulatory, ethical and otherwise) will delay the arrival of the fully autonomous car by five, ten or fifteen years, the technology in some deployable form will exist before then.
The other advantage you’ll have in applying self-driving technology outside of automotive vehicles is that you’ll be able to deploy it in an environment where you control the surrounding infrastructure– augmenting onboard sensors with data from the environment and creating more predictable surroundings.
Where might this approach work? Toys, factory automation, household robotics and farming are all areas where this has already begun, but I think we are only at the beginning of discovering our great automated world.