When forecasting the future of travel demand, we have two possible outcomes, compared to the present. People may either:

  • Travel more, or
  • Travel less

(There is an infinitesimally small possibility they travel exactly the same amount, so we will ignore that). Of course they may travel more in some places or at some times or by some modes, and less for others, so we need to distinguish between micro and macro-outcomes. That depends on changes in a variety of inputs: In travel demand forecasting we have a variety of dimensions of travel we try to model:

  • Who:
  • When: Schedule
  • Why: Purpose
  • Where: Destination
  • How: Mode, Route

If people in the future behave exactly the same as people today, and their demographics are similar, the built environment is similar, and policies are similar, and there are more of them, the travel demand model would produce roughly the same amount of travel per person, and more in the aggregate.

But that is a big “If”.  This travel demand model does not capture behavioral changes, market changes, or technology changes, for starters.

First, technology may change. A model built before a new class of modes became available cannot accurately forecast their use. For instance commercial ride sharing (“transportation network companies”, e.g. Lyft, Uber) might look like taxi, but in most US markets, taxi is so seldom used it is excluded from the model for lack of data. But it differs from taxi not only in fare (lower), but also response time (faster), whether you are sharing a ride with another party (perhaps: LyftLine, UberPool), quality of vehicle (nicer?), friendliness of driver (sociable?) and many other dimensions. That is an easy problem to identify, it is already here. Now, from a regional perspective, it may still be small enough to ignore, but who can say that will remain true in the 20 or 30 time frame of official forecasts.

Car sharing and autonomous vehicles are among the other technology shifts that are both possible and unforecasted.

Willingness to share vehicles is a behavioral question for which we have no answer about its likelihood. One of the purposes of money is to buy better services. Most people think riding separately is preferred to riding in a shared vehicle, but this is as much a social norm as a law of nature.

Willingness to travel farther when the vehicle is autonomous is something we can only guess at (theory suggests if we don’t have to exert effort in driving, we may be willing to be mobile for longer times (and distances)).

In theory we could model the supply side effects of an autonomous fleet in terms of road capacity, but we will have a mixed human-robot fleet for decades. In practice this seems quite difficult. Harder still is modeling the presence of vehicles, the response time of shared vehicles, the range of electric vehicles, distance to walk to car-sharing, and the like. Not that it cannot be done, but it cannot be done with confidence. These are a mix of technology, market, and behavioral problems which are likely to become relevant over the timeframe of forecasts.

A plausible strategy given uncertainty is to look at scenarios in addition to expected values. Instead of making the deterministic forecast that in 20 years the line will have 40,000 passengers or 100,000 AADT, consider what it will be like under a variety of different assumptions. Bureaucrats don’t like uncertainty, which is why the rules are written the way they are. Politicians will choose whatever value in the range of numbers suits their rhetorical purpose. But the public should not be mislead by the false confidence associated with forecasts of expected values given without ranges and caveats — forecasts that have historically been quite poor.

Sadly, people follow whoever expresses the most confidence, not whoever is the most accurate or honest or thoughtful. That is an evolutionary biological outcome to avoid  paralysis when the lion is actually chasing you: follow either whoever quickly decides to hold ground with spears or runs  the farthest the fastest, but don’t stand around contemplating the decision. But with new transportation investment, nothing is actually urgent.