A dynamic traffic assignment model for highly congested urban networks

Abstract

The management of severe congestion in complex urban networks calls for dynamic traffic assignment (DTA) models that can replicate real traffic situations with long queues and spillbacks. DynaMIT-P, a mesoscopic traffic simulation system, was enhanced and calibrated to capture the traffic characteristics in the city of Beijing, China. All demand and supply parameters were calibrated simultaneously using sensor counts and floating car travel time data. Successful calibration was achieved with the Path-size Logit route choice model, which accounted for overlapping routes. Furthermore, explicit representations of lane groups were required to properly model traffic delays and queues. A modified treatment of acceptance capacity was required to model the large number of short links in the transportation network (close to the length of one vehicle). In addition, even though bicycles and pedestrians were not explicitly modeled, their impacts on auto traffic were captured by dynamic road segment capacities.

Green travellers? Exploring the spatial context of sustainable mobility styles

“…These results demonstrate in more accurate estimates if it is possible to identify the user behavior when a particular event occurs in the network, such as a restriction to one-way traffic (Cascetta and Cantarella, 1993;Long et al, 2011). However, DTA models still have some limitations (Ran et al, 1992;Nie, 2010;Ben-Akiva et al, 2012); the implementation of these models in traffic assignment is not as efficient as the use of other techniques and it is difficult to replicate the network congestion realistically.…”

“…These functions are related to the service level of each network segment, the generalized costs associated with daily trips in one or more modes of transport, and the potential demand to carry out these movements, which in turn refers to the behavior patterns with regard to the choice of route re-lated to the demand (Cameron et al, 2003;Ortúzar and Roman, 2003). The benefit of this type of model is that, based on these simulations, mobility managers can accurately predict the mobility guidelines that are followed by the users of an urban system, meaning that they can anticipate potential problems arising from a change in supply point (Fernández et al, 2003;Ben-Akiva et al, 2012).…”

Stochastic user equilibrium with equilibrated choice sets: Part II – Solving the restricted SUE for the logit family

“…This disadvantage is critical in a route choice application, as paths typically overlap with other considered paths on segments. The Path Size Logit (PSL) model (Ben-Akiva and Bierlaire, 1999) overcomes this deficiency, and has been applied with success in various route choice studies (e.g., Bekhor and Prato, 2009;Frejinger et al, 2009;Ramming, 2001;Ben-Akiva et al, 2012). In the following it is shown that by applying the transformed cost-function (22) …”

Simulating Transport and Land Use Interdependencies for Strategic Urban Planning—An Agent Based Modelling Approach

“…The traffic micro-simulator is in charge of executing the daily plans of the agents, hence reproduce the dynamics of traffic density on the road network. It resembles the central part of established traffic micro-simulators such as MATSim [23], TRANSIMS [24], DynaMIT [25] and AIMSUN [26].…”