Iteration-free microassignment

TL;DR: In this article, the authors present a methodology to model activity patterns, trips and trip chains, destination, mode and route choice of individual travellers in urban regions by time of day, including within-day and period-to-period adjustment of behaviour, by microsimulation without iteration.

Abstract: Integrated models of urban land-use and transport capture the two-way interaction between location and mobility decisions of households and firms over time. Because of the slowness by which the physical stock of cities, such as residences and commercial and industrial buildings, change, these models typically cover a twentyor thirty-year period. To implement feedback between land use and transport, they have to run their land-use parts and their transport parts once in each simulation period. This puts high demands on the speed by which the transport models embedded in landuse transport models are executed. Execution times of several hours, which may be acceptable if the transport model is applied only once, are prohibitive if it is to be executed once very year in a thirty-year simulation. This constraint is in conflict with the current tendency to make urban travel models more disaggregate or even entirely microscopic down to the individual traveller, which typically leads to even longer execution times even with fast parallel computers. A significant part of the computing time requirements of highly disaggregate transport models is due to the large number of iterations required to achieve user-optimal equilibrium in trip assignment. One way out of this dilemma is to review the rationale underlying these iterations. Obviously, reality does not iterate but produces a consistent sequence of trip patterns over the twenty-four hours of each day without trials. Why is it not possible to follow reality and produce consistent travel flows without iteration? This paper outlines a methodology to model activity patterns, trips and trip chains, destination, mode and route choice of individual travellers in urban regions by time of day, including within-day and period-to-period adjustment of behaviour, by microsimulation without iteration. The presentation is illustrated by a first simulation experiment using the urban region of Dortmund as a study region.