draft report DRAFT Model Documentation Dane County Travel Demand Model Wisconsin Department of Transportation Cambridge Systematics, Inc.

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1 Dane County Travel Demand Model draft report prepared for Wisconsin Department of Transportation prepared by Cambridge Systematics, Inc. January,

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3 report DRAFT Model Documentation Dane County Travel Demand Model prepared for Wisconsin Department of Transportation prepared by Cambridge Systematics, Inc. 100 CambridgePark Drive, Suite 400 Cambridge, MA date January, 2014

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5 Table of Contents 1.0 Introduction Model Updates Highway and Transit Networks Network Validation Transit Coding Feedback Loop Nested Logit Mode Choice Mode Choice Model Specification Time of Day Cube Catalog Model Application Overview Trip Generation Feedback Loop Trip Distribution Network Skimming Branch Initial Skims Congested Skims Run Once Branch K-Factors External-External Trip Distribution Gravity Model Convergence Check Mode Choice Calculate Mode Shares Mode Share Application Mode Share Application - Time Period Split Mode Share Application - Apply Mode Shares Combine Vehicle Ownership Classes Time Period PA-OD Split Assignment Convergence Assignment Final Assignment Cambridge Systematics, Inc. i

6 Table of Contents, continued Transit Assignment Post Processing Trip Length Summary Process Survey Data Network Statistics Public Transit Summary Model Validation Generation Distribution Mode Split Assignment Model Operation Scenario Inputs Socioeconomic Zonal Data Special Generator File Direct Special Generator File External-Internal Trip Data Network File Transit Line File Sub Area Extraction Forecast Scenario Include Committed Projects in Network Include Planned Projects in Network Delete TEMP Files Delete All Intermediate Files Scenario Model Lookup Files District Correspondence Super District Lookup Turn Penalty File Speed Lookup Table Capacity Lookup Table Alpha Beta Capacity Lookup Table Deficiency Target File Terminal Time Lookup Friction Factor File Auto Occupancy Lookup ii Cambridge Systematics, Inc.

7 Production Attraction Rates External-External Files External-External Station ADT Targets External-External Bluetooth External Hit Records Percent of Trucks on External-External ODS Forecast Year: Auto External-External FRATAR File Forecast Year: Truck EE FRATAR File Scenario Time of Day Factors Peak/Off-Peak Trip Shares PA Factors for Four Time Periods AP Factors for Four Time Periods Production Based Peak TOD Factors Production Based Off-Peak TOD Factors Attraction Based Peak TOD Factors Attraction Based Off-Peak TOD Factors EE Truck Time of Day Factors Scenario Mode Choice / Transit Factors Mode Choice Coefficients Mode Choice Constants Transit Path Factors Transit Wait Time Curve Transit Fare Table Premium Transit Factor File Bus Speed Factor & Bus Speed Constant Scenario Model Parameters Model Definition Base Year & Forecast Year Number of Districts Number of Zones First External Zone Maximum FRATAR iterations Auto Operating Cost Convergence Threshold Maximum Number of Iterations Cube Cluster Check Box Process Survey Data Check Box & Survey Database Trip Length Summary Table Check Box Cambridge Systematics, Inc. iii

8 Table of Contents, continued Intra-Zonal Distance Divisor Nearest Neighbor iv Cambridge Systematics, Inc.

9 List of Tables Table 1.1 Mode Choice Model Parameters Table 1.2 Feedback Iteration Time Period Definitions Table 1.3 Detailed Time Period Definitions for the Final Iteration Cambridge Systematics, Inc. v

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11 List of Figures Figure 1.1 Previous Model Highway Network Figure 1.2 New Geodatabase Highway Network with Local Roads Figure 1.3 New Highway Network with Only User Specified Links Figure 1.4: Mode Choice Model Structure for Home-based Purposes Figure 1.5: Mode Choice Model Structure for Non-home-based Purposes Figure 2.1 Main Screen of the Dane County Model Figure 2.2 Trip Generation Screen Figure 2.3 Feedback Loop Main Screen Figure 2.4 Distribution Main Screen Figure 2.5 Trip Distribution Network Skimming - Initial Skim Screen Figure 2.6 Trip Distribution Network Skimming - Congested Skim Screen Figure 2.7 Trip Distribution Network Skimming - Transit Skim Screen Figure 2.8 Trip Distribution Run Once Screen Figure 2.9 Trip Distribution Run Once K-Factor Screen Figure 2.10 Trip Distribution Run Once External to External Screen Figure 2.11 Trip Distribution Gravity Model Figure 2.12 Trip Distribution Convergence Check Screen Figure 2.13 Mode Choice Main Screen Figure 2.14 Mode Choice Default Mode Shares Figure 2.15 Mode Choice Mode Share Calculation Figure 2.16 Mode Choice Mode Share Application Figure 2.17 Mode Choice Combine Vehicle Ownership Classes Figure 2.18 Mode Choice Production/Attraction to Origin/Destination Figure 2.19 Trip Assignment Assignment Branch Figure 2.20 Trip Assignment Convergence Assignment Figure 2.21 Trip Assignment Final Assignment Figure 2.22 Trip Assignment Transit Assignment Cambridge Systematics, Inc. vii

12 List of Figures, continued Figure 4.1 Scenario Manger Inputs Figure 4.2 Scenario Manager - Lookups Figure 4.3 Scenario Manager Time of Day Factors Figure 4.4 Scenario Manager Mode Choice / Transit Factors Figure 4.5 Scenario Manager Model Parameters viii Cambridge Systematics, Inc.

13 1.0 Introduction This report documents the Dane County travel demand model updates, modeling procedures implemented, operating details and validation results. The Dane County model is a four-step travel demand model which represents highway, transit, non-motorized personal trips and truck trips within, into, outof and through Dane County. Major model updates from the previous model include the development of new highway and transit networks within the Cube geodatabase environment, replacing the FORTRAN based modemad.exe mode choice program with a Cube script mode choice model, implementing a congestion feedback loop for the distribution, mode choice and assignment steps, and converting the daily model to a time of day model with AM, Mid-Day (MD), PM, and Night Time (NT) periods. All of these updates have been implemented within a Cube Catalog configuration. Details of the modeling procedures are documented in Section 2 that describes the Cube Application modules within the overall Dane County Cube Catalog. This process includes a step by step walk though of each Application group within the model. Section 3 of this document and includes the validation of each of the four steps of the model. Many of the figures shown in Section 3 come directly from the validation worksheet provided with the model. The final section, Model Operation, describes how to run the model using the Cube Catalog Scenario Manager. This section also describes the data format and content of input files used in the operation of the model. Cambridge Systematics, Inc. 1-1

14 1.1 MODEL UPDATES The main model updates, changes and improvements have been made to the Dane County model in the following components: Highway and Transit Networks, Feedback Loop, Nested logit mode choice model, Time of Day, and Cube Catalog. These changes, along with updated 2010 base year socioeconomic data, effectively make this version of the Dane County model as a new model for the region rather than an update of the previous model. In Section 1 provides an overview of key changes made to each of the five model components. 1.2 HIGHWAY AND TRANSIT NETWORKS The network updates for the Dane County model were full replacements of the previous highway and transit networks (Figure 1.1). Both the new highway and new transit networks have been developed within Cube s geodatabase structure. The new Cube geodatabase was constructed using the Wisconsin Department of Transportation s Wisconsin Local Roads (WisLR) GIS line file (Figure 1.2). This line work includes all roadways within Dane County and all roads, including local roads, were built into the Cube geodatabase. The model is set up such that functionally classified roads and roads that are coded with a value of 1 in the include data field are built into a Cube.net network file from the geodatabase. Additional details on the specifics of the highway and transit networks can be found in Section 4, Model Operation. 1-2 Cambridge Systematics, Inc.

15 Figure 1.1 Previous Model Highway Network Figure 1.2 New Geodatabase Highway Network with Local Roads Cambridge Systematics, Inc. 1-3

16 Figure 1.3 New Highway Network with Only User Specified Links Network Validation As part of the validation of the new Dane County highway network, the new layer was compared to the previous network. These two layers were overlaid in Cube and checked to ensure the critical roadways from the previous model: (1) Are included in the new layer, (2) Are properly coded in the new layer, and (3) Data in several important fields are accurate and updated. Directionality of the newly added lane separated interstates and boulevard roads and fixed physical geometry like disconnects and other network connectivity and flow issues were also checked. Existing screenlines were checked against available count data and implemented where count data were available. Transit Coding The final network development step was to code the transit lines within the new network. The transit network operates on top of the highway network and therefore needed to be re-coded to match the new highway network. The General Transit Feed Specification (GTFS) data were overlaid on the highway network and the node sequence and stop locations were determined. Transit 1-4 Cambridge Systematics, Inc.

17 headways were calculated by dividing the frequency of scheduled trips within each time period. 1.3 FEEDBACK LOOP The model loops from congested highway assignment back to trip distribution and through mode choice and assignment again. After the first iteration, convergence is checked after the trip distribution stage. If the trip tables are not found to converge, the process continues up to a default maximum of ten iterations. Details of the implementation of the feedback loop can be found in Section 3, Model Application. 1.4 NESTED LOGIT MODE CHOICE Mode choice model parameters and the nest structure were transferred from the mode choice model estimated for Minneapolis-St. Paul. In addition to the geographic proximity, this model was selected because it has a nested structure and includes the same trip purposes as the Dane County model. In the mode choice model, home-based trips are subdivided into three classes based on vehicle ownership (zero vehicles, one vehicle, and two or more vehicles). Mode shares are calculated for all 16 sub-purposes (15 combinations of three vehicle ownership levels for the five Home Based Purposes and one Non-Home Based Purpose) and three times of day (TOD) that include the AM peak, Midday (MD) and PM peak. The night (NT) time of day does not use the mode choice model. The model nesting structures are shown in Figure 1.4 and Figure 1.5. Homebased purposes have three levels of nesting and the non-home-based purpose has two levels of nesting. The nesting parameters used for the first, second, and third nest levels are 0.8, 0.7 and 0.6 respectively. The third level is the lowest level of nesting used in the model. Cambridge Systematics, Inc. 1-5

18 Figure 1.4: Mode Choice Model Structure for Home-based Purposes Figure 1.5: Mode Choice Model Structure for Non-home-based Purposes Mode Choice Model Specification This section describes the variables that were included in the mode choice utility functions for different trip purposes. 1-6 Cambridge Systematics, Inc.

19 In-vehicle travel time for auto and transit (IVTT): In vehicle travel time for the auto modes is the congested travel time from the highway skimming process. In-vehicle travel time for transit modes is calculated from a pivoted value from the congested highway speed. The travel time unit is in minutes. Out of vehicle travel time (OVTT) for transit modes: The out of vehicle time is calculated by summing up the initial wait time, transfer wait time, walk/drive access time, transfer time and a transfer penalty expressed in minutes. The unit is in minutes. Cost of travel (Cost) for auto: For the auto modes, the cost is the operating cost plus parking costs. Parking cost is defined in the land-use file and varies by geography and for peak versus off-peak time periods. Auto operating cost per mile is assumed as 13 cents per mile 1. There is no cost associated with the non-motorized modes. The cost unit is in cents. Cost of travel (Cost) for transit. The transit cost differs depending on the mode used to access transit. The cost for the Walk to transit option is just the transit fare. The costs for the Drive to transit option include the transit fare as well as operating costs and parking costs for the automobile leg of the trip. The cost unit is in cents. Non-motorized (NM) attributes: The travel times for non-motorized modes (walk and bike) are calculated from the travel distance obtained from the highway skimming process and an assumption about walk and bike speeds. The walk speed is assumed to be 3 miles per hour and the bike speed is assumed to be 10 mile per hours. The unit is in minutes. There is no cost associated with the non-motorized modes. Vehicle Ownership dummy variable (boolean): The vehicle ownership variables are set according to the three vehicle ownership classes for each trip table market segment. CBD dummy variables (Boolean): These variables are true in cases where the attraction end or both ends of the trip are within the CBD area. The mode choice model parameters are shown in Table Auto operating cost is calculated based on the average fuel price for the Midwest during 2010 and assuming a 21 MPG fleet mileage. Cambridge Systematics, Inc. 1-7

20 Table 1.1 Mode Choice Model Parameters HBW HBU HBO HBSh HBSch NHB Variable 0 auto 1 auto 2+ auto 0 auto 1 auto 2+ auto 0 auto 1 auto 2+ auto 0 auto 1 auto 2+ auto 0 auto 1 auto 2+ auto All IVTT Cost OVTT PK OVTT OP NM time Auto Owner flag NM Auto Owner flag SR Auto Owner flag Transit CDB at end A for NM CDB at end A for SR CBD flag at both trip end for NM Cambridge Systematics, Inc.

21 1.5 TIME OF DAY Time of day factors by trip purpose segment the daily trip table into three time periods during the feedback loop iterations and a total of eight time periods in the final iteration. The time of day factors were developed based on the distribution of trips by purpose in the National Household Transportation Survey (NHTS) dataset. Truck and External to External trip time of day factors were based on ATR data provided by WisDOT; additional ATR data as processed by TADI; and TADI Wavetronix data. The time of day factors are fixed and do not vary in response to network conditions or other inputs to the model. The feedback time period definitions (prior to convergence) and the final iteration time period definitions (at convergence) are shown in Table 1.2 and Table 1.3 respectively. Table 1.2 Time Period Feedback Iteration Time Period Definitions Time AM Peak Midday PM Peak 6:00AM 9:00AM 9:00AM 3:00PM 3:00PM 6:00PM Table 1.3 Detailed Time Period Definitions for the Final Iteration Time Period Time Time Period Time AM Peak1 6:00AM 7:00AM PM Peak1 3:00PM 4:00PM AM Peak2 7:00AM 8:00AM PM Peak2 4:00PM 5:00PM AM Peak3 8:00AM 9:00AM PM Peak3 5:00PM 6:00PM Midday 9:00AM 3:00PM Night 6:00PM 6:00AM 1.6 CUBE CATALOG The model has been developed using a Cube Catalog setup to facilitate the operation of the model. The major components of a Cube Catalog are: Cambridge Systematics, Inc. 1-9

22 Scenario Manager, Data, Application Manager, and Keys. This setup allows for a much more simplified operation and maintenance of the model code and procedures. The model is primarily run using the Scenario Manager. This feature allows for easy setup up of different scenarios and testing of alternatives. Operation of the model using the scenario manager and the files referenced are described in the Section 4, Model Operation. The Application Manager, within the Cube Catalog provides a flow chart type setup of the model structure which is useful for understanding how all of the model components fit together. These individual model components are described in Section 3, Model Application. The Keys section of the Cube Catalog defines the model keys. Individual files are defined as Keys such that when they are called during the model operation, the Key is referenced in place of the actual file name. This is useful in cases where a file is called in multiple sections of the model operation. For example, the model highway network is used in the skimming process for trip distribution and used in the assignment process for trip assignment. The Key setup requires the user to change the reference of the network Key only instead of changing the model code in multiple places where the network file is called. The Data section of the Cube Catalog lists the input, output and report files that are created by the model Cambridge Systematics, Inc.

23 2.0 Model Application This section provides an overview of the model operation within the Cube Application Manager setup within the model catalog. Each of the four steps of the Dane County model are demonstrated within the Cube Application Manager component of the Cube Catalog. The actual operation of the model is best preformed using the Scenario Manager within the catalog file. The operation of the model through the scenario manager is documented at the end of this section. 2.1 OVERVIEW At the top level, the Dane County model is organized into application groups for each of the four steps in a transportation planning model and an additional group for post processing (Figure 2.1). A feedback loop repeats the Distribution, Mode Choice and Assignment groups until convergence. Trip Generation is run only once at the beginning of each model run. Figure 2.1 Main Screen of the Dane County Model Cambridge Systematics, Inc. 2-11

24 2.2 TRIP GENERATION Trip generation produces personal and commercial internal-to-internal (II), internal-to-external (IE), and external-to-internal (EI) productions and attractions by zone. The personal trips are segmented into three vehicle ownership categories including zero vehicles, one vehicle, and two or more vehicles. Special generator productions and attractions are added to the unbalanced Production- Attraction (PA) counts and are balanced and distributed similarly to the generated trips. The special generator inputs are not segmented by vehicle ownership. These trips are allocated to the three vehicle ownership categories according to the distribution of the generated trips in the zone. If there are no generated trips in the zone, the trips are allocated across the three vehicle ownership categories according to the overall distribution of trips. There are six personal trip purposes. Output files are generated with the purposes in the following order: Home Based Work trips (HBW), Home Based Shopping trips (HBSHOP), Home Based School trips (HBSCHOOL) Home Based Other trips (HBO), Non-home-based trips (NHB), and Home Based University trips (HBU). Commercial truck productions and attractions are segmented by Single-Unit and Combination trucks. Figure 2.2 Trip Generation Screen 2-12 Cambridge Systematics, Inc.

25 2.3 FEEDBACK LOOP The feedback loop is set to go through up to 10 successive iterations. The procedure increments the variable iter from 1 to a default value of 10 in steps of 1 for each loop (Figure 2.3). The default maximum number of iterations can be changed through the {max_iter} key in the catalog. Intermediate files include the iteration variable that is attached at the end of the file name *_@iter@.* Feedback loop convergence is checked after the completion of the trip distribution step. The convergence criteria are based on a comparison of changes in the trip table between the current iteration and the previous iteration of the trip distribution. Convergence is reached when at least 95 percent of the zone to zone interchanges have changes that are less than 5 percent change. The 95 percent criterion value is configurable though the {conv_threshold} key. When convergence is reached, the {DISTCHK.CONVERGE} key is set to 1. At this stage, the model setup begins the final iteration of the model loop. Figure 2.3 Feedback Loop Main Screen 2.4 TRIP DISTRIBUTION The trip distribution application consists of three main branches with two options within each branch. The first option on each branch is only performed on the first iteration. The three branches shown in Figure 2.4 are: NetSkim Branch, RunOnce Branch, and Converge Branch. The trip distribution is performed after the skim branch and prior to the convergence check. Cambridge Systematics, Inc. 2-13

26 Figure 2.4 Distribution Main Screen Network Skimming Branch Network skimming produces a single highway network for assignment as well as AM, MD and PM highway and transit skims for the morning peak, midday, and evening peak periods respectively. Initial Skims This component has a different operation depending on whether it is the first iteration of the feedback loop or a subsequent iteration. In the first iteration, the network is extracted from the Geodatabase and skims are created using free-flow speeds. The free-flow skims are then copied to the AM, MD and PM skims for input to trip distribution and mode choice (Figure 2.5). There is no transit assignment in the first iteration. generated in subsequent iterations. Transit skims are only 2-14 Cambridge Systematics, Inc.

27 Figure 2.5 Trip Distribution Network Skimming - Initial Skim Screen Congested Skims In subsequent iterations, the loaded networks, by time of day, from the previous iteration are skimmed for both highway and transit. This congested skim process loops through the AM, MD and PM time periods to create the congested skims for the three time of day periods (Figure 2.6). The NT time period is not skimmed as this is a relatively uncongested highway period and the majority of transit system in not in operation. Cambridge Systematics, Inc. 2-15

28 Figure 2.6 Trip Distribution Network Skimming - Congested Skim Screen The transit skimming process includes the generation of four different skims to reflect the different types of transit mode and access mode. The transit skims that are produced include the Walk to Bus, Walk to Premium Transit, Drive to Bus, and Drive to Premium Transit skims (Figure 2.7) Cambridge Systematics, Inc.

29 Figure 2.7 Trip Distribution Network Skimming - Transit Skim Screen Run Once Branch The Run Once branch within the trip distribution step performs two tasks which only need to be run once during a model run. These two tasks include the creation of the K-Factor files and the creation of the external to external trip table. The Run Once branch is only needed in the initial iteration (Figure 2.8). Figure 2.8 Trip Distribution Run Once Screen K-Factors This application group produces k-factor zonal matrices for each trip purpose (Figure 2.9). This application group is only run in the initial iteration. The k- factors are defined by vehicle ownership class, but due to calibration data limitations all vehicle ownership classes have the same k-factors. The k-factor inputs are defined by district and are expanded to the zonal level. Cambridge Systematics, Inc. 2-17

30 Figure 2.9 Trip Distribution Run Once K-Factor Screen External-External Trip Distribution This application group produces External-External EE vehicle trip matrices by auto and trucks. In the base year, the EE trips are fratared from survey inputs. In forecast years, the new targets are fratared from the base year distribution. This application group is only run in the initial iteration (Figure 2.10). Figure 2.10 Trip Distribution Run Once External to External Screen 2-18 Cambridge Systematics, Inc.

31 Gravity Model This group produces daily II/EI/IE person trips by purpose and vehicle ownership and truck trips by truck type. The weighted average by trip purpose of the AM, MD and PM skims is used as an input (Figure 2.11). Figure 2.11 Trip Distribution Gravity Model Cambridge Systematics, Inc. 2-19

32 Convergence Check This group compares the trip table from the Gravity Model to the previous iteration trip table. The convergence check is not done on the first iteration. The converge criteria are the same as discussed in the Feedback Loop Section 2.3. If the difference is less than the percentage set in the {conv_threshold} key, converge is achieved and the DISTCHK.CONVERGE key is set to 1. Figure 2.12 Trip Distribution Convergence Check Screen 2.5 MODE CHOICE The major components of mode choice are the following: Calculate mode shares, Split into PA AM, MD, PM, NT time periods, Apply mode choice probabilities, Combine Vehicle Ownership Classes, Convert from PA to OD trip tables, and Combine personal and commercial trips Cambridge Systematics, Inc.

33 Figure 2.13 Mode Choice Main Screen Cambridge Systematics, Inc. 2-21

34 Calculate Mode Shares This group produces mode shares for each combination of time period, vehicle ownership, and purpose segment. A total of 48 mode share matrices are generated. In the initial feedback iteration, the occupancy rates and non-motorized rates by purpose from the previous model are used to derive mode shares. The only modes with a non-zero share are drive alone (DA), shared ride (SR) and Walk. For the initial skim, the shares are the same for all time periods and vehicle ownership class trips. Figure 2.14 Mode Choice Default Mode Shares In subsequent iterations, mode shares are calculated using the loaded network skims and transit skims from the previous iteration. The share are estimated for the following modes: Drive Alone (DA), Shared Ride (SR), Walk to Bus (WBus), Drive to Bus (DBus), Walk to Premium Transit (WPrem), Drive to Premium Transit (DPrem), Walk, and Bike. First the parking cost and CBD flags are set and then the process loops through the trip purposes Cambridge Systematics, Inc.

35 The mode share loop consist of a total of 48 iterations, 45 of which are home based trip purpose/vehicle ownership/time of day market segments: 5 trip purposes Home Based Work, Home Based University, Home Based Other, Home Based Shopping, Home Based School. 3 vehicle ownership segments Zero Vehicles, One Vehicle, Two or more Vehicles, and 3 times of day AM Peak (6-9AM), Midday (9AM-3PM), PM Peak (3-6PM) The remaining 3 iterations are for the Non Home Based trip purpose for the three times of day by grouping together all vehicle ownership segments. Figure 2.15 Mode Choice Mode Share Calculation Cambridge Systematics, Inc. 2-23

36 Mode Share Application To apply the mode shares to the daily trip table, the trips are first factored into time of day trip tables and then the shares by mode are applied. Mode Share Application - Time Period Split This group splits the daily personal trip tables from the daily gravity model into AM, MD, PM and NT production-attraction (PA) trips. The vehicle ownership segments are assumed to have the same time period split for each trip purpose. Mode Share Application - Apply Mode Shares The mode share application produces purpose production/attraction trip tables by mode (Auto,WBus,DBus,WPrem,DPrem,Walk,Bike) for each time period. In each loop, the mode shares are applied to each time of day-person-purposevehicle ownership trip table (Figure 2.16). The DA and SR person trips are combined into a single Auto mode using as an input the shared ride occupancy. The process first splits the purpose-specific production-attraction daily trip table into each of the time periods. The mode choice shares are then applied to each trip purpose by time of day to determine the trips by each mode. As part of this procedure, the trips are multiplied by 100 to avoid rounding. This scale is taken out prior to assignment. Figure 2.16 Mode Choice Mode Share Application 2-24 Cambridge Systematics, Inc.

37 Combine Vehicle Ownership Classes This group combines the mode trip tables by vehicle class segment from Mode Choice into a production/attraction matrix of trips by mode for each time period. Figure 2.17 Mode Choice Combine Vehicle Ownership Classes Time Period PA-OD Split During the pre-convergence iterations, this group transforms the productionattraction time period trip tables into origin-destination trip tables for the AM, MD, and PM time periods. AM AM to 9AM, MD 9AM to 3PM, and PM 3PM-6PM. Note that since the NT time period is not used within the mode choice, it is not split out. These time period trip tables are combined with the truck trip tables and the external-external trip tables for assignment. After the trip table convergence is reached, this group splits the productionattraction time period trip tables into origin-destination trip tables for eight fine grained eight time periods that include (Figure 2.18): AM1 6AM to 7AM, AM2 7AM to 8AM, AM1 8AM to 9AM, MD 9AM-3PM, Cambridge Systematics, Inc. 2-25

38 PM1 3PM to 4PM, PM2 4PM to 5PM, PM1 5AM to 6PM, and NT 6PM to 6AM. The final time period trip tables are combined with the truck trip and the external-external trip tables for input to the assignment procedures. Figure 2.18 Mode Choice Production/Attraction to Origin/Destination 2.6 ASSIGNMENT The assignment group has two major branches: 1. Convergence Assignment 2. Final Assignment Within each branch is a time-of-day loop which performs an assignment for the time periods. The convergence assignment assigns the AM and PM peak periods as 3 hour time periods as well as the 6 hour Midday period (3 total assignments). The final assignment assigns the peak periods as 6 1-hour periods as well as Midday and Night time periods (8 total assignments). Figure 2.19 Trip Assignment Assignment Branch 2-26 Cambridge Systematics, Inc.

39 Convergence Assignment The convergence assignment group loops through the AM, MD, and PM time periods and implements the assignment routine. As this is only an intermediate step and not the final assignment the key output from this step is not the traffic volumes, but the congested highway travel times. Also within the time period loop, the convergence assignment re-calculates the bus travels times as a function of the congested highway travel times. These bus travel times and the highway travel times are fed back into the mode choice program on the subsequent loop. Figure 2.20 Trip Assignment Convergence Assignment Final Assignment The final assignment group assigns the auto and transit trip tables, by time of day to the networks and also has a subarea extraction option. The highway trip Cambridge Systematics, Inc. 2-27

40 tables are assigned for the 3 AM, 1 Mid-Day, 3 PM, and 1 NT time periods and the transit is assigned for the 1 three hour AM, 1 six hour Mid-Day and 1 three hour PM time periods. The subarea extraction for the highway assignment will be performed if the Sub Area Extraction? check box is marked and a valid subarea highway network is included in the Sub Area Network input box within the Scenario Manager. Running a subarea extraction is optional and model may be run with or without this procedure included Cambridge Systematics, Inc.

41 Figure 2.21 Trip Assignment Final Assignment Transit Assignment The transit assignment group is the last group run within the four-step model procedure. This group first combines the AM and PM peak hour trip tables into their respective three hour and merges these tables with the MD transit trips. Cambridge Systematics, Inc. 2-29

42 The mode choice model estimates a mode specific trip table in the production/attraction format. In production/attraction format, all trips flow from the production trip end to the attraction trip end. Some demand models assign transit trips in this P/A format by assigning the HBW trips during the AM peak period and the other purposes during the MD time period. This model converts the P/A table to O/D table and assigns all trip purposes to the specific time period in which they occur. The transit trips are assigned in origin/destination format for each of the time periods. This creates a slight disconnect from the production/attraction level of service data that was used to create the mode tables. This disconnect means that the P to A level of transit service skim is used to estimate trips which may originate at either the production end, which is consistent with the LOS skim, OR the attraction end, which is not consistent with the LOS skim. The walk to transit trips are not impacted by this as they have walk access and egress for each PA pair estimated. This means the when the PA pair is converted to an OD pair both directions of access and egress are available regardless of the direction of travel. The drive to transit trips represent a potential problem as they are estimated using drive access and walk egress skims, there is no guarantee that the corresponding walk access drive egress pair exists in the opposite direction. Prior to the assignment process drive to bus and drive to premium skims are created in the attraction to production direction. These skims are then compared to the similar skims in the production to attraction direction that were used to estimate the drive access trips. If a drive access skim that exists in the P/A direction does not existed in the A/P direction, the transit trips for this zonal pair are zeroed out. This is done to ensure that drive access trips can make the return drive egress trip later in the day. Cube will not successfully run if transit trips are assigned to a zonal pair that does not have a valid level of service. For the base year transit network, no trips are zeroed out. The transit assignment procedure performs the following assignments: Drive to Premium in the P/A direction, Drive to Premium in the A/P direction, Walk to Premium, Drive to Bus in the P/A direction, Drive to Bus in the A/P direction, and Walk to Bus. Unlike the drive to transit trips which has drive on one trip end and walk on the other, walk to transit trips have walk on both trip ends so no directional distinction needs to be made Cambridge Systematics, Inc.

43 Figure 2.22 Trip Assignment Transit Assignment 2.7 POST PROCESSING The major groups of Post Processing are the following: Trip Length Summary Process Survey Data Network Statistics Trip Length Summary This group produces the average trip length, trip length distribution, and intrazonal statistics from the model run. Process Survey Data This group produces the average trip length, trip length distribution, and intrazonal statistics from the survey data using the model run skims. Cambridge Systematics, Inc. 2-31

44 Network Statistics This group calculates link deficiencies (obsolete) and prepares link database files for reporting. Public Transit Summary This group calculates link deficiencies (obsolete) and prepares link database files for reporting Cambridge Systematics, Inc.

45 3.0 Model Validation 3.1 GENERATION As a validation check, the trip generation procedure was first confirmed to reproduce the trips from the Transport2020Model using the previous model SE data. The updated SE data produces the following trip values: Transport 2020 New Model POPULATION 426, ,018 HOUSEHOLDS 176, ,727 PERSONS PER HOUSEHOLD RETAIL EMPLOYMENT 41,926 35,354 SERVICE EMPLOYMENT 167, ,547 MANUFACTURING EMPLOYMENT 31,067 N/A TOTAL EMPLOYMENT 278, ,573 EMPLOYEES PER PERSON EMPLOYEES PER HOUSEHOLD SCHOOL ENROLLMENT 70,554 74,284 TRIP GENERATION OUTPUTS HOME-BASED WORK TRIPS 304, ,781 HOME-BASED SHOP TRIPS 273, ,111 HOME-BASED SCHOOL TRIPS 111, ,356 HOME-BASED OTHER TRIPS 551, ,840 NON-HOME BASED TRIPS 584, ,838 HOME-BASED UNIVERSITY TRIPS 94, ,270 TRUCK GENERATION OUTPUTS SINGLE-UNIT TRUCK TRIPS 61,838 73,986* COMBINATION TRUCK TRIPS 22,416 27,314* 3.2 DISTRIBUTION Friction factors are calibrated so that average trip lengths are within 5% of the survey average trip lengths, the coincidence ratio of the trip length distributions is greater than 0.65, and intrazonal rates are within 3 percentage points of the survey intrazonal rates. As shown in Table XX, with the exception of HBU trips, these criteria are met. Cambridge Systematics, Inc. 3-33

46 The mismatch on HBU is likely due to limitations in the HBU generation method. HBU trips are generated according to number of households in each zone, without regard for distance to university attractions. Therefore, HBU trips are produced across the region and the trip lengths are longer on average than the survey observations. Insert distribution tables 3.3 MODE SPLIT Target mode shares are developed from the NHTS survey. The mode choice constants are calibrated to fit the target shares as close as possible. To avoid overfitting, the constants are capped at a maximum absolute value of 5.0. The calibrated mode choice constants are shown in Table ZZ. Table XX shows that the model is fitting across most purposes very well with the exception of HBU non-motorized trips. Again, this is likely due to the limitation of HBU trip generation causing HBU trips to be longer than observed. Insert mode choice constants Insert mode shares 3.4 ASSIGNMENT Model assignment is calibrated using daily traffic counts associated with the network links. The counts are compared by link class, area type, and count magnitude. Table ZZ shows that these counts are within the FHWA targets by each of these segments. Futhermore, counts located on screenlines are also within an acceptable difference. Insert assignment tables 3-34 Cambridge Systematics, Inc.

47 Cambridge Systematics, Inc. 3-35

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49 4.0 Model Operation Within the Cube Catalog structure, the Application Manager provides a useful interface to visualize how the model components all fit and work together. For operation of the model, the Scenario Manager, provide a more direct method of model operation. The Dane County travel demand model is setup to run using the Scenario Manager. The setup includes five user input/operation screens: Input Screen Lookup Files Screen Time of Day Factor Screen Mode Choice / Transit Factors Screen Model Parameters Screen Cambridge Systematics, Inc. 4-37

50 4.1 SCENARIO INPUTS The Inputs Screen is where the model user can change or update the model input data, define the model year, and control other model operational procedures. Figure 4.1 Scenario Manger Inputs Socioeconomic Zonal Data The socioeconomic (SE data) file contains the data used within the trip generation process as well as the parking cost and CBD flags used in the model choice model. This file is for a given model year and or scenario. The Dane County Catalog file setup includes a 2010 base year (Dane_TAZ_SE2010.dbf) and 2050 forecast year (Dane_TAZ_SE2010.dbf) SE data files. The data included within the SE data file is as follows: Zone This is the traffic analysis zone number. The zone is used as an index for the zonal data for any program that uses the SE data. For Dane County the numbers begin with 1 and continue to 1,200. The TAZ number 1,110 to 1,200 are currently not used within the model. HH Total zone household field. Retail Total zone retail employment field Service Total zone service employment field Total Total zone employment. Note that this number may be larger than the sum of Retail and Service as it includes all other employment Cambridge Systematics, Inc.

51 SCHENR Zone school enrollment field which contains the number of students enrolled in a school within the TAZ. Only TAZ which contain a school should have values. SVXY Percentage household size and vehicle cross classification field. The data in these fields are percentage of households by household size (X=1-4) and vehicle ownership (Y=0-2). These fields are multiplied by the HH field to create the number of households in each cross classification field. The 12 data fields are: SV10, SV20, SV30, SV40, SV11, SV21, SV31, SV41, SV12, SV22, SV32, SV42. Example: the SV21field contains the number of zone household that have 2 persons and 1 vehicle. WVXY Percentage household workers and vehicle cross classification field. The data in these fields are percentage of households by number of workers (X=1-4) and vehicle ownership (Y=0-2). These fields are multiplied by the HH field to create the number of households in each cross classification field. The 12 data fields are: WV10, WV20, WV30, WV40, WV11, WV21, WV31, WV41, WV12, WV22, WV32, WV42. Example: the WV21field contains the number of zone household that have 2 workers and 1 vehicle. PERX Percentage of vehicle ownership households from 0 to 3 vehicles. These fields are multiplied by the HH field to create the number of households with 0 to 3 vehicles. PARKPK Peak period parking cost in dollars. PARKOP Off-Peak period parking cost in dollars. CDBFL Central Business Area flag. This Boolean value is 1 or 0, with values of 1 indicating the zone is within the CBD. AT_1 Area Type Field. The values for this field are: 10-Rural, 20-Suburban, 30- Urban, and 40-CBD. District District ID field. This field group the TAZ into the districts at which the gravity model K-Factors are applied. Special Generator File The special generator file, allows the user to add in productions and attraction by trip purpose in addition to those estimated by the trip generation process. In the current setup, this file is used to add in the Home Based University trips made by group quarters. Home Based University trip attractions are also added in using this file. Production and attractions added using this file are included in the production and attractions totals prior to trip balancing. Direct Special Generator File The direct special generator file, allows the user to add production and attractions by purpose. The productions and attractions added using this file are added to the production and attraction totals after trip generation balancing. This Cambridge Systematics, Inc. 4-39

52 means that productions and attractions added using this file will not be adjusted in the trip balancing procedure. Note that for each trip purpose the same number of productions and attractions must be added to the zones in order to maintain the trip balance. Cube will not successfully run if a trip imbalance exists going into the trip distribution step. External-Internal Trip Data This file contains the external to internal trips by purpose. Each file is specific to a year of the model and must be consistent with the SE data file. These trip ends are estimated using traffic count data at the external zone. The productions and attractions are converted from vehicles trips to person production and attractions by removing the external to external trips based on the bluetooth OD data, allocating the vehicle trips to a trip purpose, and converting the vehicle trips by purpose to person trips by purpose. Network File The network file is a geodatabase file which contains the Dane County model network for both the base and existing and committed highway networks. For all conditions the highway network exported from the geodatabase if the Highway network within the geodatabase. This.net network contains all of the links in the geodatabase and subsequent steps build either the base, E+C or planned networks depending on the value in the forecast year parameter check boxes. Transit Line File The transit line file has the extension.lin and is an export from the geodatabase. The catalog was initially setup to read the transit line directly from the geodatabase. Citilabs, the makers of the Cube software, advised against reading the transit line file directly from the geodatabase file and recommended exporting it prior to using it in the Public Transport program. Sub Area Extraction The Sub Area extraction check box and network file are optional features that have been included to allow the user to perform a sub area extraction from the network. The sub area extraction check box only impacts the final highway assignment routine, all other model procedures will run in exactly the same with the box checked or unchecked. If the check box is checked, the model will look for a sub area network and will create subarea matrix files names SubArea_@tod@.met is the time period time of day. These matrices are useful to determine the number of trips that flow into and out of the given subarea. Note that the subarea network used in this process must be created from the full highway network that is being used in the model Cambridge Systematics, Inc.

53 For more information on subarea network creation, consult the Cube help files. Forecast Scenario The forecast scenario check box informs the model if the run to be performed is for the forecast or base year. This check box changes the manner in which the external to external trip table is created. For the base year, this trip table is read in directly from observed data. In the forecast year, the model forecasts the future year external to external trip table by using the based year observed table and forecasted count data to grow the trip table to the future year using a FRATAR process. The files used this process are described in the Scenario Lookups section of this report. Note that the forecast scenario check box does NOT update any of the model input files, such as the socioeconomic input data or lookup files. These must be changed, as needed, using the appropriate input or lookup file definitions in the scenario manager. Include Committed Projects in Network This check box indicates if the existing and committed highway projects are to be included in the highway network. Checking this box will build the E+C highway network. Include Planned Projects in Network This check box indicates if the planned highway projects are to be included in the highway network. Checking this box will build the planned highway network. Note that if the E+C check box and Planned Project check boxes are both checked, both sets of projects will be included in the highway network. If only the Planned Project box is checked, only the planned projects will be included. Delete TEMP Files This check box, when checked will delete all files created during the model run that have the extension.temp. For most model runs, this box should be checked in order to limit the number of files created. The.temp files created during the model run are all temporary files which are created during the process of generating the final files. Unchecking the box allows the user to view these files, which may be helpful for diagnostic purposes. Delete All Intermediate Files The Delete All Intermediate Files check box, when checked will delete all of the.temp files as well as all of the final files from each of the model iterations except for the final iteration. Each feedback loop iteration (distribution, mode choice, and assignment) of the model produces results and it is typically not necessary to keep these files. Cambridge Systematics, Inc. 4-41

54 Having this box unchecked allows the user to compare results of the model from each of the model iterations of the feedback loop Cambridge Systematics, Inc.

55 4.2 SCENARIO MODEL LOOKUP FILES The Model Lookup Files page in the Scenario Manager is the location of the model lookups and the external to external input files. Figure 4.2 Scenario Manager - Lookups District Correspondence The District Correspondence file is a lookup file that groups the TAZ into districts. This lookup file is a space separated text file with four columns. The first column contains the TAZ number (1-1,242), and the second contains the district number (1-29). The third and fourth columns control the allocation of the TAZ to districts. All values in the third and fourth columns are 100. Cube Defines the four columns as: 1. IPZONE Input Zone Number 2. OPZONE Output Zone Number 3. ROWPCT Percentage of IPZONE s values to be assigned to the OPZONE when renumbering the IPZONE rows 4. COLPCT Percentage of IPZONE s values to be assigned to the OPZONE when renumbering the IPZONE columns Super District Lookup The Super District lookup file is similar to the District Correspondence file, but where the District Correspondence file allocated TAZ to districts, the Super District file splits the district into TAZ. Cambridge Systematics, Inc. 4-43

56 Turn Penalty File The turn penalty file is a space separated text file that contains the turn penalties to be used with the network file. The turn penalties are defined using three nodes; a from node, a through node, and a to node. The forth value in the turn penalty defines the turn penalty set that the penalties belong to and the fifth is the actual penalty to be applied to the turn movement. A value of -1 will prohibit turning movements, and a positive real number value will apply a time penalty in minutes equivalent to the value entered. 1. From Node 2. Through Node 3. To Node 4. Turn Penalty Set 5. Turn Penalty Value Speed Lookup Table The speed lookup table is a space separated text cross classification lookup table. The highway speeds are defined by the linkclass and area values coded on each of the highway links. The linkclass and area variables defined in the network section of this documents. The file consists of five columns containing: 1. Linkclass 2. Rural Speed 3. Suburban Speed 4. Urban Speed 5. CBD Speed The speeds are defined as miles per hour. Capacity Lookup Table As with the speed lookup table the capacity lookup table is also a space separated text cross classification lookup table 1. Linkclass 2. Rural Capacity 3. Suburban Capacity 4. Urban Capacity 5. CBD Capacity The capacities are defined as vehicle per lane, per hour Cambridge Systematics, Inc.

57 Alpha Beta Capacity Lookup Table The AB lookup defined the Alpha and Beta values, by linkclass, for use in the standard BPR volume delay function. Additionally, this file contains the hourly to period capacity conversion factors. The capacity conversion factors expand the hourly capacity to a time period specific capacity. Deficiency Target File The deficiency target lookup file is a space separated text file used in the deficiency analysis process. Terminal Time Lookup The terminal time look up file is a space separated text file use to define the origin and destination terminal times for each zone. 1. Zone Number 2. Origin Terminal Time in Minutes 3. Destination Terminal Time in Minutes Friction Factor File The friction factor look up file is a space separated text file setup with the time in minutes in the first column and the friction values for the trip purposes in the other columns. 1. Time in minutes 2. Home Based Work (HBW) Friction Factor 3. Home Based Shopping (HBSH) Friction Factor 4. Home Based School (HBScl) Friction Factor 5. Home Based Other (HBO) Friction Factor 6. Non Home Based (NHB) Friction Factor 7. Home Based University (HBU) Friction Factor Auto Occupancy Lookup The auto occupancy look up file is a space separated text file containing the occupancy factors used to convert person trip to vehicle trips. Trip Purpose (HBW, HBSH, HBScl, HBO, NHB, HBU) 1. Combined Drive Alone and Shared Ride Occupancy 2. Shared Ride Occupancy Cambridge Systematics, Inc. 4-45

58 Production Attraction Rates The production and attraction rate lookup file defines the trip generation rates used in the model. Each row of the file is for a specific trip purpose with the columns containing either production or attraction rates for that purpose. The text file contains label which identify the values. External-External Files The next set of lookup file on the second scenario manager page are the external to external trip files. These files control the handling of the external to external traffic for the model. External-External Station ADT Targets The external to external target file sets the target number of trips that are to be external to external for each of the external zones. 1. External Zone Number 2. Number of Origin External to External Trips 3. Number of Destination External to External Trips External-External Bluetooth External Hit Records The Bluetooth hits record file is the processed Bluetooth data in database format. These data are used to create the base year external to external trip table. 1. Origin External Zone 2. Destination External Zone 3. Number of trips Percent of Trucks on External-External ODS This input database file sets the truck percentage of external to external trip table. Each OD pair with external to external trips is specified. 1. Origin External Zone 2. Destination External Zone 3. Number of trips Forecast Year: Auto External-External FRATAR File The Auto EE FRATAR file is a space separated text file that sets the target value of the forecast year auto EE trips. The base year model uses a total EE target then splits them into Autos and Trucks. For the forecast year the process sets targets for both the autos and truck separately Cambridge Systematics, Inc.

59 Forecast Year: Truck EE FRATAR File The Truck EE FRATAR file is a space separated text file that sets the target value of the forecast year auto EE trips. The base year model uses a total EE target then splits them into Autos and Trucks. For the forecast year the process sets targets for both the autos and truck separately. Cambridge Systematics, Inc. 4-47

60 4.3 SCENARIO TIME OF DAY FACTORS The scenario time of day factors page controls the time of day factors and production and attraction factors used in the model. Figure 4.3 Scenario Manager Time of Day Factors Peak/Off-Peak Trip Shares The peak/off-peak shares file contains the time of shares for the for auto the trip purposes, the truck trips and the external to external trips. The peak/off-peak shares file is used in the gravity model to create a weighted daily highway skim for each trip purpose for use in the daily trip distribution process. Each trip purpose uses a daily highway skim that is weighted by the number of trips of that purpose during each of the time periods. For example if the 25% of the HBW trips occur during the AM peak, 50% during the off peak and 25% during the PM peak the weighted skim would be 25% of the AM skim plus 50% of the off peak skim plus 25% of the PM skim. This process is used by both the auto and truck distribution procedures. The peak/off-peak shares file also contains the time of day shares for the external to external trips. These factors split the daily external to external trip table into time period specific trip tables. PA Factors for Four Time Periods This file contain the factors used to define the production based time of day factors for four time periods 6-9AM, 9AM-3PM, 3-6PM, and 6PM-6AM Cambridge Systematics, Inc.

61 This file is used in the intermediate iterations of the model during which the peak periods are not split out into individual hours. AP Factors for Four Time Periods This file contain the factors used to define the attraction based time of day factors for four time periods 6-9AM, 9AM-3PM, 3-6PM, and 6PM-6AM. This file is used in the intermediate iterations of the model during which the peak periods are not split out into individual hours. Production Based Peak TOD Factors This file contains the production based peak period time of day factors for each trip purpose at the following time periods 6-7AM, 7-8AM, 8-9AM,3-4PM, 4-5PM and 5-6PM. Production Based Off-Peak TOD Factors This file contains the production based off peak period time of day factors for each trip purpose at the following time periods 9AM-3PM and 6PM-6AM. Attraction Based Peak TOD Factors This file contains the attraction based peak period time of day factors for each trip purpose at the following time periods 6-7AM, 7-8AM, 8-9AM,3-4PM, 4-5PM and 5-6PM. Attraction Based Off-Peak TOD Factors This file contains the attraction based off peak period time of day factors for each trip purpose at the following time periods 9AM-3PM and 6PM-6AM. EE Truck Time of Day Factors The EE truck time of day file contains the truck time of day for Single and Multi- Unit trucks for the AM1, AM2, AM3, MD, PM1, PM2, PM3 and NT times of day. Time of day external to external trip factors for both autos and truck are also included in this file. Cambridge Systematics, Inc. 4-49

62 4.4 SCENARIO MODE CHOICE / TRANSIT FACTORS The fourth page of the scenario manager contains the mode choice and transit factor files used in the transit skimming, mode choice and transit assignment routines. Figure 4.4 Scenario Manager Mode Choice / Transit Factors Mode Choice Coefficients The mode choice coefficients file is a space separated text file that is a crossclassification lookup of the trip purposes and vehicle ownership groups by the mode choice level of service utility equation components. The columns in the file contain the following trip purpose and vehicle ownership groups. Home Base Work, 0 vehicle HHs Home Base Work, 1 vehicle HHs Home Base Work, 2+ vehicle HHs Home Base University, 0 vehicle HHs Home Base University, 1 vehicle HHs Home Base University, 2+ vehicle HHs Home Base Other, 0 vehicle HHs Home Base Other, 1 vehicle HHs 4-50 Cambridge Systematics, Inc.

63 Home Base Other, 2+ vehicle HHs Home Base Shopping, 0 vehicle HHs Home Base Shopping, 1 vehicle HHs Home Base Shopping, 2+ vehicle HHs Home Base School, 0 vehicle HHs Home Base School, 1 vehicle HHs Home Base School, 2+ vehicle HHs Non Home Based, all vehicle group HHs The rows contain the individual level of service components. IVTT In-vehicle travel time in minutes Cost Cost of travel in cents OVTTPK Out of vehicle travel time for the peak periods OVTTOP Out of vehicle travel time for the off peak period NM Nonmotorized travel time for walk and bike in minutes NM_Binary This is an adjustment factor to the constant for each vehicle ownership segment within each purpose for nonmotorized trips SR_Binary This is an adjustment factor to the constant for each vehicle ownership segment within each purpose for shared ride trips TRN_Binary This is an adjustment factor to the constant for each vehicle ownership segment within each purpose for tranist trips NM_ATTCBD This is a nonmotorized coefficient for trips with the attraction end located in the CDB TRN_ATTCBD This is a transit coefficient for trips with the attraction end located in the CDB NM_BOTHCBD This is a nonmotorized coefficient for trips with the both production and attraction ends located in the CDB Mode Choice Constants The mode choice constants file is a space separated text file that is a crossclassification lookup of the trip purposes and vehicle ownership groups by the available modes. The columns in the file contain the same trip purpose and vehicle ownership groups as listed for the mode choice coefficients. The rows contain each of the available modes. Cambridge Systematics, Inc. 4-51

64 Drive Alone Shared Ride Walk to Bus Drive to Bus Walk to Premium Drive to Premium Bike Walk Transit Path Factors The transit path factors file defines the factors used in the transit path building procedures. This file sets the minimum and maximum wait times, the path building functions, the fare systems, value of time, transfer penalties and other transit path building values. More information on these values can be found in the Cube help section. Transit Wait Time Curve This file define the initial transit wait curve to be used in the wait time estimation in the transit path building. The values included in this file effectively set the initial wait time to be half of the transit headway. Transit Fare Table The transit fare file defines the fares used for each of the modes in the model. More information on these values can be found in the Cube help section. Premium Transit Factor File This file is the same as the Transit Path Factors files, but for use in the premium mode. Bus Speed Factor & Bus Speed Constant The Bus Speed Factor and Bus Speed Constant files are both space separated text files that are a cross-classification lookups of the area type and linkclass. These two files provide the speed factors and constants used in the bus travel time function. The bus travel time function is defined as: Bus Speed = Congested Speed * Bus Speed Factor + Bus Speed Constant 4-52 Cambridge Systematics, Inc.

65 4.5 SCENARIO MODEL PARAMETERS The data contained in model parameters tab of the scenario manager includes basic model setup information that should not need to be changed often. Figure 4.5 Scenario Manager Model Parameters Model Definition The Model Definition is an identifier for the model. This is a descriptive field only and is not used in any calculations during the operation of the model. Base Year & Forecast Year The Base and Forecast Years inputs are where the model years are defined. Specifically these two input years inform the model of how many years there are between the base and forecast model years. This information is used in the post processing of the model to calculate the growth rates between the base and forecast years. Number of Districts The number of districts values sets the number of districts used in the model. The districts are used during the trip distribution K-Factor expansion process. Cambridge Systematics, Inc. 4-53

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