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TRANSIMS Research and Deployment Project TRACC TSM Staff Dr. Vadim Sokolov Dr. Joshua Auld Dr. Kuilin Zhang Mr. Michael Hope.

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Presentation on theme: "TRANSIMS Research and Deployment Project TRACC TSM Staff Dr. Vadim Sokolov Dr. Joshua Auld Dr. Kuilin Zhang Mr. Michael Hope."— Presentation transcript:

1 TRANSIMS Research and Deployment Project TRACC TSM Staff Dr. Vadim Sokolov Dr. Joshua Auld Dr. Kuilin Zhang Mr. Michael Hope

2 Model Goals  Develop an extensible software framework which can be easily adapted to solve problems which are currently difficult for FHWA to address  The effects of developing ITS infrastructure –3CI centers –Intelligent signal systems  Interoperability: looking at the co-variant effects of historically separate models –The regional effects of a car following simulation informed dynamically by an activity based model  Enabling future models which may become of increased interest given the appropriate framework –Regional emission calculations –Special event planning  Hold as a design criteria the needs of metropolitan planners to be able to answer a question at hand with limited information, time, and budget 2

3 Initial Design Concept  Survey the full range of problems which are or may become of interest to transportation planners and the performance metrics which are necessary to answer these questions  Distill these ideas into a generalized transportation modeling language  Construct a framework which is transparent enough for a developer to easily write in this modeling language, but is robust enough to ensure that the level of work they must do is minimal  Illustrate how the framework may be used and how easily it may be extended by using it to build a model which can address questions related to interoperability and ITS infrastructure  Interact closely with FHWA to ensure the framework and models maintain their design criteria of extensibility, ease of use, and modeling accuracy 3

4 Model Conceptual Framework Go to ”Insert (View) | Header and Footer" to add your organization, sponsor, meeting name here; then, click "Apply to All" 4 Land UseSynthetic PopulationNetwork ITS Architecture Activity Modeling Trip Routing Traffic Simulation Learning 30 sec 5 min / triggers

5 Writing a “Transportation Modeling Language”  The best language to look for inspiration is perhaps that of agent-based models and of machine learning.  A key focus of the agent-based modeling community has been to provide a sufficiently generalized language which may be used to solve an incredibly diverse range of problems in an inherently modular way.  It is not necessary for our language to be as general as that of traditional agent- based models, we can make a number of simplifying assumptions which are specific to transportation while still preserving the modularity necessary to address a diverse set of planning problems. 5

6 Conceptual Framework Elements  Transportation Agent Building Blocks  Transportation Environment Building Blocks  Task Scheduling Engine and Execution Cells  Global System State Coherency based on ACID Principles  Developer APIs, Utility Functions, and Data Structures  Clear and Accessible Documentation 6

7 Putting the Framework into Action  The initial application of the framework is to develop a model which may be used to test “what if” scenarios related to: –The efficacy of implementing new ITS infrastructure –Traditional highway capacity and long range planning –The effects of activity choice on higher resolution model components  The following transportation planning elements will be modeled in a fully integrated fashion: –Intelligent Transportation System Behavior –Activity Choice –Mode Choice –Parcel-Level Destination Choice –Departure Time Choice –Route Choice –En Route Path Choice –High Resolution Traffic Simulation: Car Following, Lane Changing –Low Resolution Traffic Simulation: Queue-based Model 7

8 Putting the Framework into Action cont’d  The model takes as input a supply network, a base population, ITS infrastructure, and land use information  The model executes continuously (does not iterate)  Agents learn over time; these “lessons” can be saved and re-used in future models  The user specifies a “virtual observer” to watch and output parameters of interest 8

9 Anticipated Extensions  A crucial design criteria of the framework is that the above model may be easily extended or re-molded to investigate these other topics of interest to FHWA.  Emissions: evaluate the change in emissions following a policy change  Transit: evaluate the level of service of a new high speed rail system  Novel ITS Concepts: observe the regional effects of an Intellidrive system  Research Community: drop in and test alternative models for car following, route choice, mode choice, etc…  Freight: identify the regional logistical impacts of a new freight system 9

10 Anticipated Extensions cont’d  Safety: test alternative highway and intersection geometries to improve driver safety  Parking: test alternative parking system layouts in a municipality, determine the effects of allowing on-street parking  Energy: determine the impact of increased hybrid vehicle market penetration  Pedestrians/Bicyclists: examine the effects of pedestrian behavior on a transportation system, test new pedestrian walkways or bicycle lanes  Weather: test models for how weather affects a transportation system  Social Networks: examine the effects a social network can have on activity choice and further on a transportation system as a whole 10

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