Static and Dynamic Traffic Assignments: Sundsvall (Sweden) Case Study



Static and Dynamic Traffic Assignments: Sundsvall (Sweden) Case Study

Authors

Anna Contenti, V&B Software Services/Citilabs, Gabriella Sala, V&B Software Services/Citilabs

Description

This paper discusses the added benefits of mesoscopic DTA over macroscopic Static Assignment. A modelling exercise was carried out with the aim to compare results in a real context such as Sundsvall, a medium size Swedish town.

Abstract

Traditional macroscopic Static Assignment models cannot fully replicate conditions observed normally on congested road networks. Typical congestion phenomena such as the formation and dissipation of queues, the variability in departure times, the effect of bottlenecks and the effect of blocking back cannot be modelled with a macroscopic Static Assignment. Mesoscopic Dynamic Traffic Assignment (DTA) models offer the opportunity to overcome these limitations and enhance models’ ability to represent the behaviour of congested road networks.
This paper discusses the added benefits of mesoscopic Dynamic Traffic Assignment (DTA) over traditional macroscopic Static Assignment, presenting examples from a Cube traffic model implemented for Sundsvall, a medium size Swedish town.
The model was developed to run both static and dynamic assignments in parallel; this allowed the comparison of the two types of assignment. The static assignment was developed with Cube Voyager Highway, the dynamic assignment was developed with Cube Avenue, further Cube applications were added to the model to generate automatic comparison networks and report tables.
The model output comparison showed interesting differences between the two assignments. In the presence of bottlenecks the DTA assignment was shown to correctly model traffic being held back when exceeding capacity. Also, the DTA assignment was to able to better model the speed in proximity of key congested junctions by modelling the impact of blocking back on upstream links.
The paper will present the results of the comparison and show the key features of DTA; it will also discuss the challenges faced for the calibration of the Cube Avenue model and the lessons learned during the process.

Keywords:
• Macro and mesoscopic model, traffic congestion, transportation planning.

Bibliography:
• Cascetta, E. (2001) Transportation Systems Engineering: Theory and Methods, Springer.
• Citilabs (2013) Cube Voyager Reference Guide.

Publisher

Association for European Transport