Jeremy Foote

Jeremy Foote

Computational social scientist studying cooperation and collaboration in online communities; faculty at Purdue University.

Local vs. Global Control

2 minute read

Published:

Photo via smoothgroover22 on flickr
As a kid, I was fascinated by the idea of self-driving cars. This may be the very definition of a nerdy child, but I remember sitting awake one night, thinking about how self-driving cars might work. All of my schemes involved a centralized computer that would be aware of where every car was, and would calculate ahead of time when collisions might occur, and make minor adjustments to vechicle speeds to avoid them.

However, the actual self-driving cars which are coming are very different from what I envisioned. Instead of operating via a centralized "hive mind", each car operates autonomously and locally, without any direct knowledge about other cars. Instead of a centralized knowledge about the whole system, they each gather their own information about their local environment, and operate in a decentralized way, with only local knowledge of their portion of the system.

There are some reasons for this, some of which can point toward general principles for when systems are better as decentralized and when they are better centralized:

  • There are important aspects of the environment which are unknown. A centralized system doesn't know about cyclists or children running into the road, or debris, etc.
  • Centralized systems create a single point of failure. If there is a bug in the system, all cars are affected. A bug in a single car (or even a single model) is much less catastrophic
  • Centralized systems are less adaptable. If you decide that you don't want to go to that restaurant after all, and you'd rather just go to Wendy's, with a local system, your car simply adjusts its route accordingly. With a centralized system, an adjustment to one car propagates through the system, and hundreds or thousands of route adjustments need to be calculated and applied (similarly every time someone starts a new route or there is an accident, etc.). These are complex optimizations problems which can be approximated by local systems without all of the overhead.
I think that the eventual system of transportation will be a mix of local and centralized. As I understand it, current cars have access to centralized maps, and I can imagine that the richness of the sort of data that can be centralized will grow: information about when lights will change, information about traffic jams, even information about the destination of other cars in the area. However, for the reasons outlined above, I think that these will be information systems, not decision systems. They will always be accompanied by a rich understanding of the local situation, with the actual decision making done at that level.

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