Will AI change the case for automated transit networks? Probably not, and that works in ATN’s favor.
AI is the obvious technology to ask about when it comes to automated transit networks (ATN). ATN’s value depends on two things: how many people need to travel, and how fast, reliably and safely the system can move them. AI is unlikely to change either one much.
1. Travel demand is holding up. In 2015 the world made roughly 22 billion trips a day, about 3.0 per person. By 2025 that had grown to roughly 25 billion, still about 3.0 per person. Over the same period, the share of U.S. workers who mainly work from home almost tripled, from 4.6% to 13.3%. Most trips are for errands, school, healthcare and social visits rather than commuting, and people are still making them.
2. ATN performance depends on certified software, and that won’t change. Speed, capacity and reliability all depend on safety-critical control software: headway management, merging and fail-safe braking. That software has to be certified, independently verified and kept under strict configuration control. It can’t learn on its own or update itself.
Conclusion
Demand is driven by population and how people live, and performance is set by certified engineering. AI changes neither, and for agencies and investors
that stability counts in ATN’s favor.
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