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FOCUS MODEL OVERVIEW CLASS FIVE Denver Regional Council of Governments July27, 2011.

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Presentation on theme: "FOCUS MODEL OVERVIEW CLASS FIVE Denver Regional Council of Governments July27, 2011."— Presentation transcript:

1 FOCUS MODEL OVERVIEW CLASS FIVE Denver Regional Council of Governments July27, 2011

2 Tentative Schedule Model StepsJuly 28 Model Steps & More about Applicationto 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 FEEDBACK

5 Focus Model Flow STAGE 1: Make Population And Network STAGE 2: Run GISDK to Mode Choice STAGE 3: C# Logit Models to Create Trips STAGE 4: GISDK Assignment 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 monte carlo.  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 Tour Mode DTWTSBSR3+SR2DABW Trip mode DT X WT XX SB XXX SR3+ XXXX SR2 XXXXX DA XXXXXX B XXXXXXX W XXXXXXXX

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 STAGE 1: Make Population And Network STAGE 2: Run GISDK to Mode Choice STAGE 3: C# Logit Models to Create Trips STAGE 4: GISDK Assignment 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 PMPM  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 FEEDBACK


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