Genetics of traffic assignment models for strategic transport planning

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 functionality (genes). We argue that all traffic assignment models can be described by two genes. The first gene determines the spatial functionality (unrestricted, capacity restrained, capacity constrained, capacity and storage constrained) described by five spatial interaction assumptions, while the second gene determines the temporal functionality (static, semi-dynamic, dynamic) described by two temporal interaction assumptions. This classification provides a deeper understanding of the often implicit assumptions made in traffic assignment models described in the literature, particularly with respect to networking loading where the largest differences occur. It further allows for comparing different models in terms of functionality, and opens the way for developing novel traffic assignment models.

Day-to-day dynamic traffic assignment with imperfect information, bounded rationality and information sharing

“…This macroscopic perspective of dynamic traffic flow is chosen here not only for its widely recognized capabilities of capturing realistic dynamic traffic network phenomena including shock wave, physical queues, and vehicle spillback, but also for its consistency with the macroscopic travel choice and information sharing models inherent in the day-to-day component. The LWR type kinematic wave model has been widely applied to DTA problems (Han el al., 2015;Garavello et al, 2016;Bliemer et al, 2017), sometimes in its discrete or variational forms such as the cell transmission model (Daganzo, 1994;1995), link transmission model (Yperman et al, 2005), and double-queue model (Osorio et al, 2011). We refer the reader to Nie and Zhang (2005), Garavello et al (2016) and Han et al (2016) for a review of relevant literature and computational examples.…”

“…A widely accepted classification of DTA models is influenced by Wardrop's principles (Wardrop, 1952), known as the dynamic extensions of system optimal (SO) and user equilibrium (UE). The reader is referred to Peeta and Ziliaskopoulos (2001), Boyce et al (2001), Lo (2005, 2006), and Bliemer et al (2017) for a comprehensive review of these DTA models.…”

Analysis of a joint entry- and distance-based cordon pricing scheme: a dynamic modeling approach

“…Equations (1-9) represent a dynamic tolled user equilibrium traffic assignment model which is appropriate for analyses of the cordon pricing strategies mentioned above. Based on the work of Bliemer et al [44], the proposed model is categorized as the class of the capacity-restrained dynamic traffic assignment models in which link physical capacities may be exceeded, and queues and spillbacks are not considered explicitly.…”

Computing Dynamic User Equilibria on Large-Scale Networks with Software Implementation

“…For a comprehensive review of DTA models, the reader is referred to Boyce et al (2001); Peeta and Ziliaskopoulos (2001); Lo (2005, 2006); Jeihani (2007) and Bliemer et al (2017). A discussion of DTA from the perspective of intelligent transportation system can be found in Ran and Boyce (1996a).…”