There are differing beliefs about the effects of autonomous vehicles on travel demand. On the one hand, we expect that automation of itself is a technology that makes travel easier, it pushes the demand curve to the right. For the same general cost, people are more willing to travel. Exurbanization has a similar effect (and automation and exurbanization form a nice positive feedback system as well).
On the other hand, the move from private vehicle ownership to mobility as a service, which is likely in larger cities means that the marginal cost of a trip might rise from very low (since the vehicle is already owned) to high (since the cost of the vehicle has to be recovered on a per-trip basis). This moves the demand curve to the left. It is similar in effect to urbanization (and urbanization and mobility-as-a-service form a nice positive feedback system). Lots of other changes also move the demand curve to the left, including demographic trends, substituting information technologies for work, socializing, and shopping, and dematerialization.
Income moves the willingness to pay for the same amount of travel up or down.
Changes in the price structure of travel move along the demand curve as shown here.
This is one scheme for thinking about the effects of new technologies on travel demand (which we will introduce in the . How these vectors net out is a problem that could be solved with analytical geometry, if only we knew their relative magnitudes. In The End of Traffic and the Future of Transport, we argue demand in the US is generally moving a bit more to the left than the right (though the last year saw sharp reductions in fuel costs and higher incomes and thus moved us more to the right than the left). But we also note that new automation technologies change the available capacity of roads through improved packing of vehicles in motion and smaller vehicles. Less demand plus more supply reduces congestion effects in the net.