Transportation professionals have, for a long time, been challenged by the problem of accurately estimating how travelers select particular travel path out of many alternatives and also how they will change their path in reaction to changes in the road network such as work zones, crashes, road closures, etc. The answers to these questions are essential for determining the expected variations of traffic flow with time, and forms the basis for developing effective operational strategies that would effectively respond to traffic flow variations on the network.
Due to the inability of the traditional four-step transportation planning models to address the dynamic nature of path finding problem, these models are not very useful for developing effective traffic management strategies. A complex mathematical solution for this path finding/traffic assignment problem has been derived and is known as Dynamic Traffic Assignment (DTA). With the assistance of the University of Arizona, MAG has begun to use a new simulation model called DynusT for the region. A unique Dynamic Traffic Assignment (DTA) capability has been incorporated within DynusT aimed at replicating driver decision making and path finding, from origin to destination, under normal long-term conditions. In addition, a series of route choice rules based on human behavior are applied for vehicle rerouting in different scenarios. These will lead to more reliable outputs of the space and time dependent volumes and experienced travel time, which is critical for traffic engineers, transportation planners and decision makers to make informed decisions about our transportation system.
In implementing Dynamic Traffic Assignment, DynusT applies a mesoscopic simulation model. The model reflects the interaction between vehicles and facilities and among vehicles. Thus, the congestion forming and dissipation has meaningful space and time essence. At the same time, the mesoscopic model allows for cost efficient area wide impact studies and enables large scale region wide analyses.
With the DynusT Dynamic Traffic Assignment model, we will be able to answer some of the most challenging questions regarding our transportation system in the region through Multi-Resolution Modeling (MRM). We can utilize the network and output of the Travel Demand model as inputs of the mesoscopic DTA model for analysis. We can also import the outputs and network of the mesoscopic DTA model into a microscopic simulation model for more detailed study. Multi-resolution modeling utilizes a specific model or a combination of models for a specific problem.
The regional road network has been incorporated in the DynusT model and the model has been calibrated. The first case study/application of this model will involve the examination of operational strategies that could have been used to mitigate the impact of a real life crash on I-10 that affected thousands of commuters on a weekday morning in February 2010.
If you would like to take a look at the DTA model simulation, please follow this link: MAG Regional DTA model Simulation. The simulation includes about 2.7M vehicles traveling over 20,000 links (roadway segments) and close to 10,000 nodes (intersections) during a 5-hour span in the morning peak period.
The case study crash location and the impacted area are shown in figure 1. The Subarea covers over 8700 links, 4500 nodes and 848 traffic analysis zones.
To find out more about the DynusT model and how it might serve your needs, please contact Eric Nava at 602-254-6300.