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Focus Model Overview CLASS FIVE

Focus Model Overview CLASS FIVE. Denver Regional Council of Governments July27, 2011. Tentative Schedule. Model Steps July 28 Model Steps & More about Application to unconfuse you August 4. Focus Model Duality. SQL Server Database and TransCAD files (bin, matrix)

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Focus Model Overview CLASS FIVE

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  1. Focus Model OverviewCLASS FIVE Denver Regional Council of Governments July27, 2011

  2. Tentative Schedule Model Steps July 28 Model Steps & More about Application to unconfuse you August 4

  3. Focus Model Duality • SQL Server Database and TransCAD files (bin, matrix) • T-SQL/C# Code And GISDK Code

  4. Focus Model Flow: 28 Steps Outside The Speed Feedback Loop: Run Once- STAGE 1 GISDK called from C#: GISDK Preprocess Java: 3. Population Synthesizer C# 4. PopSyn Output Processor 5. Size Sum Variable Calculator STAGE 2 GISDK called from C#: For DIA, I-E, E-E and Commercial Trips 1. DRCOG Multi-Period Highway Preprocess 2. DRCOG Multi-Period Transit Preprocess 3. DRCOG Transit Preprocess 4. Trip Generation 5. Highway and Transit Skimming 6. Trip Distribution 7. Mode Choice STAGE 3 C# Regular Trips 8. Regular Work Location Choice 19 . Tour Main Mode Choice 9. Regular School Location Choice 20. Tour Time of Day Choice 10. Auto Availability 21. Intermediate Stop Generation 11. Aggregate Logsum Generation 22. Trip Time of Day Simulation 12.Daily Activity Pattern 23. Trip Time Copier 13. Exact Number of Tours 24. Intermediate Stop Location 14.Work Tour Destination Type 25. Trip Mode Choice 15.Work-Based Subtour Generation 26. Trip Time of Day Choice 16. Tour Time of Day Simulation 27. Write Trips to TransCAD 17. Tour Primary Destination Choice 18. Tour Priority Assignment STAGE 4 GISDK called from C#: 28. Highway and Transit Assignment FEEDBACK

  5. Focus Model Flow FEEDBACK

  6. Review • We have represented and skimmed the network. • We have created external DIA and commercial trips. • People have a regular workplace and school. • Households have a number of cars. • We know how tours a person makes. What is a tour again? What is a half-tour? What is an intermediate stop? How is a half-tour stop different from an intermediate stop?

  7. Review • We know where the tour is going, what mode it uses, and it times. • Now it’s time to make stops on the tour. • Why do you stop places instead of leaving your house and coming back again? • When you stop what is guiding what time you stop at and what mode you use?

  8. Intermediate Stop Generation • Choice: Applied to Each Half Tour, if daily activity pattern includes a stop, Predicts work, school, escort, personal business, meal, shop, social/rec or no more stops • Model Type: Multinomial Logit • Inputs: (What do you think predicts?) Tour Purpose Person Type Number of Stops already made Tour Mode

  9. Can Now Create Trips and Half Tour Stops: Fill These Tables

  10. Here’s what the trip table looks like

  11. Trip Time of Day Simulation • We need a time of day on each intermediate stop to pick which skim to use. • Use the distribution of observed times for intermediate stops by purpose, and montecarlo. • For example, 15% of meal stops happen between 12 pm – 1 pm

  12. Intermediate Stop Location • We know the anchoring locations of home and primary destination. We know how many stops they will make. • Where will the person stop? • Model Type: Multinomial Logit • Choices: Zones, Point Locations • Inputs: (What do you think predicts this?) - Distance Out of Direction the stop will take you - Stop Purpose - Number of Jobs in Each Zone - Mixed Use Density

  13. Now we know where the stops are.

  14. Trip Mode Choice • Choice: Drive Alone, Shared Ride 2, Shared Ride 3+, Walk to Transit, Drive to Transit, Walk, Bike School Bus • Known: Tour Mode • Model Type: Multinomial Logit (separate by purpose) • Inputs: (What do you think?) Tour Mode Trip Purpose Travel Time Time of Day Income Destination Density

  15. Only Certain Trip Modes allowed by Tour Mode

  16. Trip Time of Day • Predicts: Time of Day for Intermediate Stops (we already know for primary destination • Choice: twenty four one-hour increments 12 AM- 1 AM..etc; A little tricky Predict Stop Departure Time On Inbound Half Tour

  17. We don’t know time we left home, so Predicts Stop Arrival Time on Outbound Half Tour

  18. Trip Time of Day Choice Model Type: Multinomial Logit • Inputs: (What do you think?) Previously Scheduled Tours and Stops (Process is Iterative) Trip Purpose Travel Mode Age Worker Status Constants by Time of Day

  19. Finally we have a full set of trips: we’re done with stage 3 • We know: • Trip Origin, Destination X, Y • Trip Time Period to Within an Hour • Trip Mode • Trip Purpose For Each Person, For Each Trip in the Region

  20. Here’s what the trips look like (again)

  21. Focus Model Flow FEEDBACK

  22. Write Trips to TransCAD • We take these flat table trips and write them into matrices by mode by purpose. Thisw ill have all integer values. • We combine these trips with internal-external trips, external-external trips, and DIA trips by replacing the appropriate rows and columns in the matrices. • Now we can assign the • Trips Finally!

  23. Aggregate Trips into Assignment Periods • TIMES OF DAY • Highway Times of DayTransit Times of Day • AM1: 6:30 – 7:00 AM; AM: 6:30- 9:00 AM • AM2: 7:00 – 8:00 AM; • AM3: 8:00 – 9:00 AM; • OP2: 9:00 – 11:30 AM; MD: 9:00 AM- 3:00 PM PM • OP3: 11:30 AM – 3:00 PM; • PM1: 3:00 – 5:00 PM; PM: 3:00 PM -7:00 PM • PM2: 5:00 – 6:00 PM; • PM3: 6:00 – 7:00 PM; • OP4: 7:00 – 11:00 PM. EL: 7:00 PM – 6:00 AM • OP1: 11:00 PM – 6:30 AM;

  24. Trip Time – Distance Matrix Copier • Take the Skimmed Travel Times and Distances and Write Them Back Into the Database • Looks like this:

  25. Stage 4: GISDK Assignment • Run Highway Assignment for 10 time periods • Run Transit Assignment for 4 time periods • Remember those DIA trips, external trips, and commericial trips from way long ago: they get thrown in. Then we know: Model Assignment Outputs And we can feed the speeds back to the trip-making. So people can choose daily activity patterns with the updated speeds. People may travel less due to congestion or switch modes

  26. Cool Outputs • VMT for an individual person, or group of people living in a neighborhood • Number of Bike or Walk Trips Originating in a buffer around a bike path • The usual: Boardings by Route, Traffic Volumes by ten time periods • Can you think of something we can do now??? • We know about each person and where they go on a point level.

  27. Focus Model Flow: 28 Steps Outside The Speed Feedback Loop: Run Once- STAGE 1 GISDK called from C#: GISDK Preprocess Java: 3. Population Synthesizer C# 4. PopSyn Output Processor 5. Size Sum Variable Calculator STAGE 2 GISDK called from C#: For DIA, I-E, E-E and Commercial Trips 1. DRCOG Multi-Period Highway Preprocess 2. DRCOG Multi-Period Transit Preprocess 3. DRCOG Transit Preprocess 4. Trip Generation 5. Highway and Transit Skimming 6. Trip Distribution 7. Mode Choice STAGE 3 C# Regular Trips 8. Regular Work Location Choice 19 . Tour Main Mode Choice 9. Regular School Location Choice 20. Tour Time of Day Choice 10. Auto Availability 21. Intermediate Stop Generation 11. Aggregate Logsum Generation 22. Trip Time of Day Simulation 12.Daily Activity Pattern 23. Trip Time Copier 13. Exact Number of Tours 24. Intermediate Stop Location 14.Work Tour Destination Type 25. Trip Mode Choice 15.Work-Based Subtour Generation 26. Trip Time of Day Choice 16. Tour Time of Day Simulation 27. Write Trips to TransCAD 17. Tour Primary Destination Choice 18. Tour Priority Assignment STAGE 4 GISDK called from C#: 28. Highway and Transit Assignment FEEDBACK

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