What is Dynamic Traffic Assignment? A Dynamic Traffic Assignment, known as DTA, model estimates the evolution and propagation of congestion through detailed models that capture travel demand, network supply and their complex interactions. Unlike a static model, a DTA model can describe time-dependent dynamics of traffic and replicate the interactions between travelers and the transportation network. A simulation-based DTA model is an analysis tool to address complex and dynamic transportation operations and planning issues of urban road networks. It overcomes the limitations of traditional static assignment models by using advanced traffic modeling techniques to capture the dynamics of congestion formation and dissipation associated with time-dependent demand and network conditions.
Benefits and Applications: A simulation-based DTA model supports transportation network planning and traffic operations decisions. It overcomes many of the known limitations of static models used in current planning practice. It can be used to assess the impacts of ITS and non-ITS technologies on the transportation network, to support decision-making for work zone planning and traffic management, to evaluate different congestion pricing schemes, to plan for special events and emergency situations including evacuation scenarios, and more importantly to perform traffic assignment analyses in conjunction with classical four-step demand models or emerging activity-based and tour-based models..
Figure 1 A snapshot of the simulation-based dynamic traffic assignment model of Melbourne
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DynaMel
DynaMel is a dynamic traffic assignment model and analysis tool to address complex and dynamic transportation operations and planning issues of Melbourne road network. It overcomes the limitations of traditional static assignment models by using advanced traffic modeling techniques to capture the dynamics of congestion formation and dissipation associated with time-dependent demand and network conditions. The model is developed in AIMSUN. |
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CONDITION OF USE
DynaMel is distributed free of charge. It is an open access model. We are a strong advocate of open science. We ask all users to mention explicitly the use of the model when publishing results and/or further development of the model using the provided reference below:
DISCLAIMER
The model is provided free of charge and "AS IS" WITHOUT ANY WARRANTY of any kind. The implied warranties of merchantability, fitness for a particular purpose and non-infringment are expressly disclaimed. In no event will the developers and/or their employers be liable to any party for any direct, indirect, special or other consequential damages for any use of the model and its variants including, without limitation, any lost profits, business interruption, loss of programs or other data on your information handling system or otherwise, even if we are expressly advised of the possibility of such damages.
SOFTWARE AND HARDWARE REQUIREMENTS
Advanced or Expert license of AIMSUN (https://www.aimsun.com/)
Windows® Vista/7/8/8.1/10, Windows Server 2008 R2 and Windows Server 2012, 64-bit processor or Mac OS X 10.9, 10.10, 10.11, 10.12 64-bit processor
Multi-core CPU faster than 3 GHz
16 GB of RAM (32 GB recommended),
and support for 1 GB data exchange.
DOWNLOAD
AIMSUN model
The model consists of 55,719 links and 24,502 nodes.
It simulates near 2.1 million vehicles in a 4-hour morning peak period 6-10 AM.
10.07.2017
Dynamel 1.0
06.09.2018
Dynamel 2.0
Detailed simulated trajectories
Entire network trajectories 1.0
CBD network trajectories 1.0
DynaMel is distributed free of charge. It is an open access model. We are a strong advocate of open science. We ask all users to mention explicitly the use of the model when publishing results and/or further development of the model using the provided reference below:
- Shafiei, S., Gu Z., Saberi M. (2018) Calibration and Validation of a Simulation-based Dynamic Traffic Assignment Model for a Large-Scale Congested Network. Simulation Modelling Practice and Theory, 86, 169-186.
DISCLAIMER
The model is provided free of charge and "AS IS" WITHOUT ANY WARRANTY of any kind. The implied warranties of merchantability, fitness for a particular purpose and non-infringment are expressly disclaimed. In no event will the developers and/or their employers be liable to any party for any direct, indirect, special or other consequential damages for any use of the model and its variants including, without limitation, any lost profits, business interruption, loss of programs or other data on your information handling system or otherwise, even if we are expressly advised of the possibility of such damages.
SOFTWARE AND HARDWARE REQUIREMENTS
Advanced or Expert license of AIMSUN (https://www.aimsun.com/)
Windows® Vista/7/8/8.1/10, Windows Server 2008 R2 and Windows Server 2012, 64-bit processor or Mac OS X 10.9, 10.10, 10.11, 10.12 64-bit processor
Multi-core CPU faster than 3 GHz
16 GB of RAM (32 GB recommended),
and support for 1 GB data exchange.
DOWNLOAD
AIMSUN model
The model consists of 55,719 links and 24,502 nodes.
It simulates near 2.1 million vehicles in a 4-hour morning peak period 6-10 AM.
10.07.2017
Dynamel 1.0
06.09.2018
Dynamel 2.0
Detailed simulated trajectories
Entire network trajectories 1.0
CBD network trajectories 1.0
Publications
- Shafiei, S., Gu, Z., Saberi M. (2018) Calibration and validation of a simulation-based dynamic traffic assignment model for a large-scale congested network. Simulation Modelling Practice and Theory 86, 169-186.
- Shafiei, S., Gu Z., Sarvi M., Saberi M. (2017) Deployment and Calibration of a Large-Scale Mesoscopic Dynamic Traffic Assignment Model of Melbourne, Australia. Proceedings of The Transportation Research Board (TRB) 96th Annual Meeting, Transportation Research Council of the U.S. National Academies, Washington, D.C., January 8–12, 2017.
- Shafiei, S., Saberi M., Zockaie, A., Sarvi, M. (2017) A Sensitivity-Based Linear Approximation Method to Estimate Time-Dependent Origin-Destination Demand in Congested Networks. Transportation Research Record: Journal of the Transportation Research Board.
- Shafiei, S., Saberi, M., Sarvi M. (2016) Application of an Exact Gradient Method to Estimate Dynamic Origin-Destination Demand for Melbourne Network. The 19th International IEEE Conference on Intelligent Transportation Systems (ITSC), Rio de Janeiro, November 1-4, 2016.
- Gu, Z., Saberi, M., Sarvi, M., Liu, Z. (2016) Calibration of Traffic Flow Fundamental Diagrams for Network Simulation Applications: A Two-Stage Clustering Approach. Proceedings of The 19th International IEEE Conference on Intelligent Transportation Systems (ITSC), Rio de Janeiro, November 1-4, 2016.