ABSTRACT
This paper presents a review and classification of traffic assignment models for strategic transport planning purposes by using concepts analogous to genetics in biology. Traffic assignment models share the same theoretical framework (DNA), but differ in capability (genes). We argue that all traffic assignment models can be described by three genes. The first gene determines the spatial capability (unrestricted, capacity restrained, capacity constrained, and capacity and storage constrained) described by four spatial assumptions (shape of the fundamental diagram, capacity constraints, storage constraints, and turn flow restrictions). The second gene determines the temporal capability (static, semi-dynamic, and dynamic) described by three temporal assumptions (wave speeds, vehicle propagation speeds, and residual traffic transfer). The third gene determines the behavioural capability (all-or-nothing, one shot, and equilibrium) described by two behavioural assumptions (decision-making and travel time consideration). This classification provides a deeper understanding of the often implicit assumptions made in traffic assignment models described in the literature. It further allows for comparing different models in terms of functionality, and paves the way for developing novel traffic assignment models.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1. Although there is debate in the literature whether behaviour is determined by genes or by the environment (or both), in biology the field of study called behavioural genetics examines the origins of individual differences in behaviour.
2. In other words, this relationship only describes first-order effects and does not explicitly describe transitions between traffic states (which requires explicit modelling of braking and acceleration as second-order effects). As mentioned in Section 1.2, second-order effects are usually not considered in large-scale strategic transport planning not only for tractability reasons, but also to avoid illogical behaviour such as negative flows and traffic going backwards as outlined by Daganzo (Citation1995b).
3. Note that the line that separates traffic conditions C and D in is plotted somewhat arbitrarily between the critical density and jam density since it is case specific, that is, depends on the inflow rate and the link length.