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The objective of this research is to build and calibrate a DTA model for Northern Nevada (Reno Sparks Area) based on the network profile and travel demand information updated to date. The critical procedures include development of consistent and readily adaptable DTA model, model validation, and calibration based on observed field data. The DTA software package used to develop the DTA model in this project is NeXTA/DTALite. Major findings: (1) Capabilities and benefits of DTA. (1a) DTA is mesoscopic in nature, providing a connection between regional travel demand forecasting and micro-simulation models. It is one step further from the planning level travel forecasting towards the operating details of micro-simulation, i.e., DTA analyzes large networks as a travel demand forecasting tool and provides time-varying traffic network performance (e.g., queue formation, bottleneck identification) but not as much detailed as micro-simulation models. (1b) Comparing with micro-simulation models which normally represent known traffic flow patterns, DTA can both represent current traffic performance and evaluate near-term traffic flow impacts from network changes. It is particularly useful to model a regional level network to forecast traffic flow pattern changes and operational impacts due to incidents such as work zone, special events, and accidents. (2) Requirements for DTA Development and Applications (2a) Geometric data, traffic control data, traffic demand, OD demand data and transit demand are basic requirements for network development. (2b) For model calibration, the fidelity of a DTA model depends on more than link volumes. Typical types of data for calibration strategies can include: travel times, travel speeds, queue information, and transit operations. (2c) Transportation modeling techniques and various levels of efforts are needed depending on the model complexity and data availability. (3) Limitations of DTA Applications. (3a) For long-term planning, DTA may not be
This project covered the development and calibration of a Dynamic Traffic Assignment (DTA) model and explained the procedures, constraints, and considerations for usage of this model for the Reno-Sparks area roadway network in Northern Nevada. A literature review was conducted regarding DTA model development and applications. The details of the DTA model development for the Reno-Sparks network were documented along with necessary model calibration. DTALite was used for developing the DTA model and Network eXplorer for Traffic Analysis (NeXTA) was implemented as the user interface. Since the Regional Transportation Commission of Washoe County (RTC) maintains the regional TransCAD travel demand model, the up-to-date network and Origin Destination (OD) demand data was obtained from RTC. After initial model preparation, the model was calibrated by comparing the DTA generated link volumes and those obtained from the Nevada Department of Transportation's (NDOT's) Traffic Record Information Access (TRINA) database, which includes 24-hour link volumes on major roadway links collected from permanent and temporary traffic count stations. The DTA model development included the following major steps: (1) Import the network and demand data from TransCAD into NeXTA; (2) Perform a dynamic traffic assignment in DTALite to achieve an equilibrium to produce an initial DTA model; (3) Prepare field data and run Origin Destination Matrix Estimation (ODME) for initial network calibration; (4) Validate and demand modifications to better match the observed counts versus simulation volumes; and (5) Cut a sub-area and perform further analysis in micro-simulation software packages (optional).
Development of a simulation-based heuristic DTA model that can be implemented for real world applications is also presented. The model uses a mesoscopic simulator and a time-dependent shortest path algorithm and is tested on an actual urban network with more than 16,000 links.
Large-scale Mesoscopic traffic simulation is a newly adopted tool due to recent advancements in traffic modeling as well as computer hardware. New studies show that modeling on a scale necessary to answer complicated questions such as diversion patterns around multi-corridor work zones is feasible. As with many research projects, the original objective of this project was adjusted to maximize the benefit from the final product. The initial objective was to create a framework and guidelines for the development of a Twin Cites Mesoscopic Dynamic Traffic Assignment (DTA) model. Discoveries during the course of the project as well as MnDOT priorities and urgent needs directed the project away from the development of guidelines and more toward the proof-of-concept and the development of the foundation for such a metro-wide model. In addition, a parallel MnDOT project, undertaken by a consulting group using the DynusT application, developed an almost metro-wide model. The project described in this report, changed its scope to treat this parallel project as a case study and identify its future utility beyond its immediate goals, which were to determine the most cost-effective construction phasing for several projects during the 2017-2020 construction seasons.