Appendix 3 CUUATS Transportation Model Report

TRANSPORTATION MODEL

LONG RANGE TRANSPORTATION PLAN 2025

Champaign-Urbana Urbanized Area Transportation Study (CUUATS)

TABLE OF CONTENTS

I. INTRODUCTION ...... 1

II. DATA DEVELOPMENT...... 2 1. TRAFFIC ANALYSIS ZONE (TAZ), CENTROIDS, AND EXTERNAL STATIONS...... 2 2. NETWORK CODING...... 2 1) Highway Network...... 7 2) Transit Network ...... 8 3. SOCIOECONOMIC DATA ...... 13

III. DEFINITIONS FOR TRIPS ...... 14 1. TYPES OF TRIPS ...... 14 2. TRIP PURPOSES ...... 14

IV. TRIP GENERATION...... 16 1. OVERVIEW...... 16 2. TRIP PRODUCTION AND ATTRACTION ANALYSIS ...... 17 1. Trip Production...... 17 2. Trip Attraction ...... 17 3. EXTERNAL TRIPS ANALYSIS ...... 17 1) Roadside origin-destination survey...... 18 2) External Trips ...... 18 4. BALANCING ...... 21

V. TRIP DISTRIBUTION ...... 22 1. OVERVIEW...... 22 2. ESTIMATION OF IMPEDANCES: TRAVEL TIMES...... 23 3. ESTIMATION OF FRICTION FACTOR...... 23 4. USE OF GRAVITY MODEL ...... 24

VI. MODE CHOICE...... 26 1. MODE SPLIT PROCEDURES...... 26 2. CREATION OF AN ORIGIN-DESTINATION TRIP TABLE ...... 27

VII. TRIP ASSIGNMENT...... 28 1. HIGHWAY TRIP ASSIGNMENT...... 28 1) Methodology ...... 28

i 2) Parameters...... 28 2. TRANSIT TRIP ASSIGNMENT...... 29

VIII. TIME-OF-DAY ANALYSIS ...... 30

IX. MODEL VALIDATION...... 31 1. PLOT CHECK ...... 31 2. VOLUME CHECK...... 31 1) % Root Mean Square Error...... 31 2) Average Volume Ratio...... 31 3. VEHICLE MILES TRAVELED CHECK...... 33

X. REFERENCE ...... 34

XI. APPENDICES...... 35 APPENDIX A: HOUSEHOLD SIZE BY TAZ ...... 36 APPENDIX B: EMPLOYMENT BY TAZ...... 40 APPENDIX C: UNBALANCED TRIP PRODUCTIONS AND ATTRACTIONS .... 44 APPENDIX D: BALANCED TRIP PRODUCTIONS AND ATTRACTIONS...... 47

ii LIST OF FIGURES

Figure 1. The Structure of the Four-Step Travel Demand Model ...... 1 Figure 2. Procedures to build transit network...... 9 Figure 3. Procedures for building transit skim file ...... 12 Figure 4. Trip Purposes ...... 14 Figure 5. Trip Generation Process ...... 16 Figure 6. Trip Distribution Process...... 22 Figure 7. Process to Estimate Friction Factors from the Survey...... 24

List of Tables

Table 1. Node Attributes ...... 7 Table 2. Link Attributes ...... 7 Table 3. Link Speed/Capacity by functional classification and area type ...... 8 Table 4. Link data (Type 1 Data Card) ...... 9 Table 5. Speed Curve Use Data (Type 2 Data Card) ...... 10 Table 6. Speed Curve Data (Type 3 Data Card)...... 10 Table 7. Speed curve data used by Champaign-Urbana Urbanized Area ...... 11 Table 8. Line numbers used in TROUTE.TEM ...... 11 Table 9. Employment Category...... 13 Table 10. Summary of the Roadside Origin-Destination Survey...... 18 Table 11. Percent Residency and Trip Purposes for CUUATS...... 20 Table 12. External Trip Productions and Attractions (Person Trips) ...... 20 Table 13. Trip Generation Summary ...... 21 Table 13. Typical Terminal Times for Different Area Types ...... 23 Table 14. Calibrated Friction Factors...... 25 Table 15. Production/Attraction code and Area types used in mode choice model...... 26 Table 16. Volumes by Split Curves ...... 26 Table 17. BPR curve coefficients for Link Group3...... 29 Table 18. Percentage of peak periods by actual traffic counts done in 2002 (1/09/04).... 30 Table 19. Peak hour traffic volumes for Champaign-Urbana Urbanized Area ...... 30 Table 20. VMT per household and per capita...... 33 Table 21. VMT by Road Classification ...... 33

LIST OF MAPS

Map 1. Study Area Boundary for LRTP 2025...... 3 Map 2. Traffic Analysis Zones for LRTP 2025...... 4 Map 3. Highway Network for LRTP 2025...... 5 Map 4. Transit Network for LRTP 2025...... 6 Map 5. Cordon Count Locations...... 19 Map 6. Highway Network...... 32

iii I. Introduction

The purpose of this document is to outline the main processes of creating a transportation model (or “travel demand model”). The model will be used as an analysis tool to evaluate existing and future network conditions as part of the Long Range Transportation Plan 2025. This document is divided into four chapters describing data requirements, definitions that CUUATS staff has developed for model inputs, trip generation process and the trip distribution process.

The model uses a four-step travel demand model to estimate the traffic volumes, which is shown in Figure 1. Currently, the CUUATS travel demand model utilizes TRANPLAN version 9.0 and VIPER version 3.0 by CITILAB.

The four-step travel demand model: § Trip Generation: estimate how many trips are made by each household for each of the trip purposes (work, shopping, etc.) and how many trips are attracted to each location (work places, shopping centers, etc.). § Trip Distribution: estimate how many trips go from one location to all other locations. § Mode Choice: given that someone will travel from one location to another, compare the mode options and choose which mode the traveler would likely use. § Trip Assignment: route the travel between zones onto public transportation services and roadways.

Socioeconomic Data Trip Generation Trip Rates

Highway Network Trip Distribution Friction Factor

Transit Network Mode Choice Utility Coefficient

Trip Assignment BPR Coefficients

Time-Of-Day Analysis Peak-time Percentage

Traffic Volume

Figure 1. The Structure of the Four-Step Travel Demand Model

1 II. Data Development

1. Traffic Analysis Zone (TAZ), Centroids, and External Stations

The study area for the travel demand model encompasses the existing Champaign-Urbana Urbanized Area (not including Bondville). Traffic analysis zones (TAZs), centroids, and external stations were defined based on the study area. Map 1 shows the study area, and Map 2 shows traffic analysis zones, centroids, and external stations. The study area has 147 TAZs, 147 centroids, and 20 external stations.

Traffic analysis zones are the geographical units for the travel demand model. Major land uses are defined for each TAZ. It is assumed that all travel activities and characteristics are homogeneous within each TAZ. When defining TAZs, several factors should be considered1:

§ Geometric shape of zones § Geographic, physical, and political boundaries § Census boundaries § Arterial roadways should not bisect a TAZ § Relatively similar land use in a zone

Centroids are the center of activities within a traffic analysis zone; the centroid is not necessarily physically centered in the TAZ. Centroids represent the origins and destinations of travel activity within each zone2. These are determined based on aerial photos and knowledge of the local situations.

Centroid connectors connect centroids to the nearby road network. These connectors represent all local residential streets that are not included in the highway network. Ideally, a centroid should be connected by at least four centroid connectors.

External stations are the points that represent outside traffic entering, exiting, or passing through the study area. The study area has 20 external stations on the edge of the urbanized area. Roadside interview surveys were done at the stations in April 2003 to collect data about trip behaviors.

2. Network Coding

The most important aspect of the transportation model is to build an accurate network for each mode representing the transportation system for the Champaign-Urbana urbanized area. CUUATS has developed a highway network for automobile users and a transit network for transit users. All the street characteristics were coded in geographic information system (GIS) format and StreetMap USA was used as a base map. Then, the base map was updated based on the survey file and aerial photos taken in 2001. Map 3 and Map 4 show each of output for the highway network and the transit network displayed in VIPER

1 Alvin Whyte (2000). Travel Demand Forecasting Manual 2: Highway Network Coding Procedures. Ohio DOT. 2 Martin, A. William, and Nancy A. Mcguckin (1998). Report 365: Travel Estimation Techniques for Urban Planning. National Academy Press. Washington D.C.

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Map 1. Study Area Boundary for LRTP 2025

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Map 2. Traffic Analysis Zones for LRTP 2025

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Map 3. Highway Network For LRTP 2025

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0 0.5 1 2Miles

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Map 4. Transit Network 0 0.5 1 2 Miles For LRTP 2025

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Legend

Transit Route Link Centroid Connector Interstate Highway 0 0.5 1 2Miles Highway Ramp

6 1) Highway Network

Highway network consists of nodes and links. Following sections describe each of highway network component. Once database were prepared, highway network can be built by the Tranplan function “Build Highway Network.” For highway network impedance coding, refer the first section of Trip Distribution.

Highway node

Nodes are the representation of street intersections and any changes in the transportation system. For example, if the street reduces from two lanes to one lane, the point where the number of lanes changes is the location of a node. The Champaign-Urbana Urbanized Area Highway Network has total 1,009 nodes uses State Plane Coordinate System (Illinois East). Node data is made in ASCII format and attributes for the node database are shown at Table 1.

Table 1. Node Attributes Field Columns Field Name Description Type C 1 ID Record Identifier, always as “N” Node Number, 1-147 Centroids, N 2-6 (5) N 148-167 External Stations, 1000-1999 Highway nodes, 2000-2999 Node only for transit - 7-8 (2) - Not Used N 9-17 (9) X X-Coordinate, two digit decimal places - 18-19 (2) - N 20-28 (9) Y Y-Coordinate, two digit decimal places C 29-80 Comments Comments

Highway link

Highway links are connections between any two nodes in the transportation system. Links contain the important characteristics of a roadway such as functional classifications, distances, capacities, area types, and speed. Champaign-Urbana Urbanized Area has 2,886 links, 7 functional classifications, and 3 link group data. Data format for link is shown at Table 2 and detailed information for coding capacity is followed in Table 3. In Table 3 the capacity for the connector is assumed to be a 999999, this is because the connector is a representation of the local streets inside the TAZ and may not represent an actual roadway. As a result, the model will not show any congestion in the connectors.

Table 2. Link Attributes Field Columns Field Name Description Type N 1-5 (5) ANODE A node number which identifies the “from” node of the link N 6-10 (5) BNODE B node number which identifies the “to” node of the link ASSIGNMENT Functional Classification of roadways N 11 (1) GROUP 1 = Major Arterial, 2 = Minor Arterial, 3 = Collector

7 4 = Local, 5 = Connector, 6 = Interstate Highway, 7 = Ramp N 12-15 (4) DIST Actual node to node distance (Hundredths of miles) C 16 (1) OPTCODE Time or speed, always as “S” Operation speed N 17-20 (4) SPEED1 (Miles per hour, decimal point between columns 18 and 19) Posted speed N 21-24 (4) SPEED2 (Miles per hour, decimal point between columns 18 and 19) N 25-26 (2) DIRCODE Direction Code, here coded as “1” 1 = CBD, 2 = Fringe, 3 = Residential, N 27-28 (2) AREATYPE 4 = OBD (Other Business Area such as Market Place Mall, North Prospect, U of I, and Parkland College), 5 = Rural N 29-30 (2) LANES Number of lanes (1 to 3) 1-17 by functional classification for BPR parameters. N 31-32 (2) Facility Type Refer the BPR parameters section of the trip assignment. N 33-38 (6) CAPACITY 24-hour capacity. Refer the Table 3. N 39-44 (6) VOLUME Average Annual Daily Traffic from traffic count N 45 (1) OPTION “1” = ignore all data in columns 46-80

Table 3. Link Speed/Capacity by functional classification and area type Area Type Facility Type 1 2 3 4 5 (ASSIGN. GROUP) CBD Fringe Residential OBD Rural Major Divided 8200 8300 8500 8500 7500 1 Arterial* Undivided 6300 7500 7500 7500 6500 6500 (25 mph) 2 Minor Arterial* 6300 7500 7500 6500 7500 (30-40 mph) 3 Collector* 5300 6500 6500 6500 5700 4 Local* 4800 6000 6000 6000 5200 5 Connector 999999 999999 999999 999999 999999 6 Interstate Highway 19000 19000 19000 19000 19000 7 Ramp 9000 9000 9000 9000 9000 * Per lane capacity for 24hours

2) Transit Network

Transit network uses a highway network as a base. Nodes and links of highway system are shared with a transit network and speed for transit is computed as a function of auto travel speed on highway network. The databases that represent transit network were made in the INET program. The coding procedures using INET program are shown on the Figure 2. First step is to generate input file into Tranplan function and then build the transit network using Tranplan. INET requires three input databases: TSYSIN.TEM, TROUTE.TEM, and HNET.TEM and Tranplan needs two inputs: HUDNET.TEM and additional nodes if needed. Following sections explain about transit travel impedance.

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TSYSIN.TEM TROUTE.TEM HNET.TEM

INET

HUDNET.TEM

Build Transit Network Additional

Nodes

MTD.NET

Figure 2. Procedures to build transit network

Database

o TSYSIN .TEM

TSYSIN consists of header in the first record, control file, and three data cards. Data card 1 contains links not in the highway network, Data card 2 includes speed curve use data and Data card 3 gives the speed curve to be used for each mode and roadway combinations. Nodes in transit network share the same node system in the highway network. Additional nodes needed for the transit routes are added as a separate database in the process of running Tranplan. Following tables show the format of each data card. All the data were made with two-digit format.

Table 4. Link data (Type 1 Data Card) Field Data Column Field name Description Length Type CARD 1 1 I1 Card Type = 1 TYPE 5 2-6 ANODE I5 ANODE 5 7-11 BNODE I5 BNODE 1 12 Unused - - 2 13-14 MODE I2 Walk = 1, MTD = 4 8 15-22 Add. Mode 4I2 Leave the columns blank

9 Distance From A to B in miles 5 23-27 DIST F5.0 Eg.0.5 mile => 0.5, 0.02 mile => coded as 0.1 Speed from A to B in miles per hour, coded 5 mile/hr 5 28-32 SPEED F5.0 less than highway speeds 5 33-37 TIME F5.0 Time from A to B in minutes 5 38-42 Unused - - 2 43-44 Unused - - Type 2 since speed, distance, and time are identical 1 45 OPTION I1 between Node A and Node B 20 46-65 - - Blank 1 66 Fare Code I1 Blank (1 –7) 4 67-70 Unused - - 1 71 Area Type I1 1-5 Facility 1 72 I1 1-7 Type

Table 5. Speed Curve Use Data (Type 2 Data Card) Field Data Column Field name Description Length Type 1 1 Card Type I1 Card Type = 2 2 2-3 Low Mode I2 Low Mode 2 4-5 High Mode I2 High Mode 1 6 Unused - - 1 7 Low Area Type I1 Low area type from 1-5 1 8 High Area Type I1 High area type from 1-5 1 9 Unused - - 1 10 Low Facility Type I1 Low facility type from 1-9 1 11 High Facility Type I1 High facility type from 1-9 1 12 Unused - - Curve number from speed curve data 2 13-14 Curve Number I2 (1-15) 2 15-16 Unused - - - 17-31 Repeat 2-16 - Repeat 2-16 - 32-46 Repeat 2-16 - Repeat 2-16 1 47-61 Repeat 2-16 - Repeat 2-16 Note: For Mode 4, curve number 11 was assigned for facility type 8-9.

Table 6. Speed Curve Data (Type 3 Data Card) Field Column Field name Data Type Description Length 1 1 Card Type I1 Card Type = 1 1 2 Unused - - 2 3-4 Curve Number I2 Curve Number from 1 to 15 1 5 Unused - - 5 5-10 Low Hwy F5.0 Low auto speed value (X1) 1 11 Unused - - 5 12-16 Low Transit F5.0 Low transit speed value (Y1) 1 17 Unused - - 5 18-22 High Hwy F5.0 High auto speed value (X2)

10 1 23 Unused - - 5 24-28 High Transit F5.0 High transit speed value (Y2)

Champaign-Urbana Urbanized Area has three different area types and 7 facility types and grouped these by similar speed range. Table 7 shows the 15 speed curve data by area type and facility type. Transit speed is fewer by 5 miles per hour than that of highway speeds.

Table 7. Speed curve data used by Champaign-Urbana Urbanized Area CBD Fringe OBD Residential Rural Major Curve No 1 Curve No 4 Curve No 7 Curve No 10 Curve No 13 Arterial (20, 15) (20, 15) (15, 13) (20, 18) (25, 23) (30, 20) (45, 40) (45, 40) (45, 40) (45, 40) Minor Curve No 2 Curve No 5 Curve No 8 Curve No 11 Curve No 14* Arterial (15, 10) (15, 10) (15, 11) (15, 10) (20, 16) (25, 20) (30, 25) (35, 30) (40, 35) (45, 40) Collector Curve No 3 Curve No 6 Curve No 9 Curve No 12 Curve No 15** Local (15, 10) (15, 13) (15, 10) (20, 15) (45, 40) Connector (20, 15) (35, 30) (35, 30) (35, 30) (55, 50) *Curve number 14 is for minor arterial, collector, local, and ramp. ** Curve number 15 is for highway.

o TROUTE.TEM

TROUTE contains route records in INET format and includes mode, line number, specific line name, headway, and stops of each transit route. One line with different directions was considered as separate lines and had two separate line numbers. Here are the samples of route file and the following table indicates the line numbers used in this TROUTE.TEM.

&ROUTE M=4, L=1, ID='1YELLOW NB', RG=1, H=30.0, N=-1468,-1771,-2000,-1467,-2001, -17,-1016, 16,-1017,-1415,-1798, -1414, 2002,-2003,-2004,-1789,-1747,-1404,-1768,-1405,-1767,-1371, -1375,-2005,-1863,-1369,-1372,-1838,-1351,-1839,-1333,-2006, C=1 &END

Table 8. Line numbers used in TROUTE.TEM Line Line Line Name Line ID Line Name Line ID Number Number North Bound 1 9A BROWN 9A BROWN 9 1 YELLOW South Bound 19 9B BROWN 9B BROWN 99 North Bound 2 West Bound 10 2 RED 10 GOLD South Bound 29 East Bound 109 3 North Bound 3 North Bound 13 13 SILVER LAVENDER South Bound 39 South Bound 139 West Bound 4 West Bound 24 4 BLUE 24 SCAMP East Bound 49 East Bound 124 West Bound 5 East Bound 25 5 GREEN 25 LOOP East Bound 59 West Bound 125 6 ORANGE West Bound 6 21 QUAD 21 QUAD 21

11 East Bound 69 22 ILLINI 22 ILLINI FARTOISR 22 West Bound 7 22 ILLINI ISRTOFAR 122 7 GREY East Bound 79 23 SHUTTLE WEST 23 SHUTTLE WEST 23 8 OCHARD West Bound 8 23 SHUTTLE EAST 23 SHUTTLE EAST 123 DOWN East Bound 89 26 PACK 26 PACK 26

o HUDNET.TEM

This file is an output file generated from the INET Program and one of the inputs for building transit network. This contains link, line, and node data.

Transit Travel Impedances

In Tranplan, procedures to generate zone-to-zone travel impedances have two steps. First step is to create a minimum path file of transit travel that builds shortest paths from one zone to all other zones. Then the next step is to build a transit skim file that contains travel impedances from a minimum path file. Input to these functions are a transit network and several parameters and the output is a matrix with zone-to-zone travel impedances. The figure 3 shows the process of creating transit skim file.

Transit Network

Build Transit Paths

Transit Paths

Transit Selected Summation

Transit Skims

Figure 3. Procedures for building transit skim file

Regarding the first step, minimum path is the summation of transit travel time on the links and wait times such as waiting time and transferring time penalties between non-transit modes and transit modes or between different transit modes. Transfer time penalties were one-half of headways and set as a default by the Tranplan. However, minimum and maximum of transfer time penalties can replace the calculated time when the last is more than maximum time set in the parameter section of control file or less than the minimum transfer time. From non-transit to

12 transit, maximum wait penalty is set as 10 minutes and minimum is 2 minutes. For the transfer between transit modes, maximum wait penalty is 20 minutes and minimum is 2 minutes.

A transit skim file can be built using a minimum path file created in the transit path building function. Final output is a zone-to-zone matrices with 5 tables selected in the data section in the control file: walk access, total wait time, transfers, mode 4 time, and total time.

3. Socioeconomic Data

The socioeconomic data is one of the major inputs for the travel demand model. The data include household and employment information aggregated by each traffic analysis zone. Census block data is a source for household data. After identifying the household data by each TAZ, the data is disaggregated by household size in groups of one person, two persons, three persons, and four or more persons. See Appendix A and B for household and employment data by each TAZ.

Employment data is one of the most difficult inputs to collect and modify since each employer in the study area must be identified by their location, number of employees, and industrial classification. The Champaign County Chamber of Commerce, Illinois Department of Employment Security (IDES), the University of Illinois, and Urbana School District provided the data. CUUATS staff geocoded all employer locations in GIS. The data were then aggregated by TAZ and employment category (See Table 9).

Table 9. Employment Category Category Description Industrial Two digit Standard Industry Classification Code 00-51 Retail Two digit Standard Industry Classification Code 52-59 Service Two digit Standard Industry Classification Code 60-81, 83-89 Education Two digit Standard Industry Classification Code 82 Government Two digit Standard Industry Classification Code 91

13 III. Definitions for Trips

1. Types Of Trips

Trips may be defined as a non-stop itinerary that starts in one place and ends in another place3. There is a single origin and a single destination. Trips can be further divided by trip makers and origin locations.

§ Person trip: a movement from one address to another by one person by any mode § Vehicle trip: a movement by a private vehicle from one address to another for a purpose regardless of the number of the people in the vehicle § Internal-internal Trips: trips within the study area § Internal-External / External-Internal Trips: trips entering or exiting the study area. These trips are referred to as Internal-External Trips § External-External Trips: trips passing through the study area

2. Trip Purposes

A trip purpose is the main reason that motivates a trip4. CUUATS defined five different trip purposes for the travel demand model: Home-based Work, Home-based School, Home-based Shopping, Home-based Other, and Non-home-based. Figure 4 shows the simplified trip definitions.

Non-home trips Other

Work

Home to Work Non-home trips

Home to Work Home Work

Home to Shopping Non-home trips Figure 4. Shopping Trip Purposes

3 Thurston County Regional Planning Commission. 4 Martin, A. William, and Nancy A. Mcguckin (1998). Report 365: Travel Estimation Techniques for Urban Planning. National Academy Press. Washington D.C.

14 § Home-Based Work (HBW): This category includes To/From Work or Work-Related Business trips. § Home-Based School (HBShc) - This category includes trips to school, college or university for classes, or to school-related meetings. § Home-Based Shopping (HBSho) – One end of trip is shopping activities. § Home-Based Other (HBO): This category includes family and personal business trips such as banking, haircuts, visiting friends and relatives, other Social or Recreational trips taken for entertainment and recreation, and for trips that do not fit any of the other categories. § Non-home Based trips – This category includes trips that do not start or end at home.

15 IV. Trip Generation

1. Overview

Trip generation is a process that estimates the amount of trips made to and from each TAZ on a daily basis. CUUATS’ trip generation model is based on the cross-classification method because this is currently considered to be better than regression model in its ability to handle non-linear trip variables. This method was also used because it can integrate local trip rates from the household travel survey conducted in 2002-2003. This model makes use of disaggregate socio- economic data such as the household by family size classification to determine the amount of travel generated in the region5.

Figure 5 shows the input and output of this process. The final output through this process would be a set of balanced trip production and attraction rates for each TAZ and external station. Major input data sources are Census 2000, Champaign County Chamber of Commerce, and the 2002 CUUATS Household Travel Survey. As a result, the Champaign-Urbana urbanized area generated 566,700 person trips per day.

Household Data Trip Production Production Rate

Employment Data Trip Attraction Attraction Rate

ADT External Trip Through trip Rate

Balancing Balancing Factor

Balanced Trip P & A

Figure 5. Trip Generation Process

5 Martin, A. William, and Nancy A. Mcguckin (1998). Report 365: Travel Estimation Techniques for Urban Planning. National Academy Press. Washington D.C.

16 2. Trip Production and Attraction Analysis

Trip production analysis is used to estimate the amount of trips produced by each TAZ. It is assumed that households in each TAZ produce the trips. Trip production equations by trip purposes were developed from the CUUATS household survey as shown below.

1. Trip Production6

HBWork = 0.16*6.1(X1) + 0.14*9.8(X2) + 0.18*11.4(X3) + 0.14*12.7(X4) HBSchool = 0.15*6.1(X1) + 0.04*9.8(X2) + 0.03*11.4(X3) + 0.04*12.7(X4) HBShopping = 0.08*6.1(X1) + 0.14*9.8(X2) + 0.13*11.4(X3) + 0.12*12.7(X4) HBOther = 0.27*6.1(X1) + 0.35*9.8(X2) + 0.31*11.4(X3) + 0.41*12.7(X4) NHB = 0.34*6.1(X1) + 0.33*9.8(X2) + 0.35*11.4(X3) + 0.29*12.7(X4)

X1 = Total number of 1-person households X2 = Total number of 2-person households X3 = Total number of 3-person households X4 = Total number of 4+person households

Inversely, trip attraction analysis determines the trips attracted to each TAZ. Employers are the major source of attracting trips. The trip attraction rates for the model were borrowed and modified from the NCHRP Report 3657. The recommended NCHRP trip attraction rates are reasonable to use since the trip generation model is highly dependent on trip production analysis.

2. Trip Attraction 8

HBWork = 1.45 * (X1) OTHER = 9.0 * (X3) + 1.7 * (X4) + 0.5 * (X5) + 0.9 * (X6) HBSchool = 0.14 * [OTHER] HBShopping = 0.23 * [OTHER] HBOther = 0.64 * [OTHER] NHB = 4.1 * (X3) + 1.2 * (X4) + 0.5 * (X5) + 0.5 * (X6)

X1 = Total employees in Total EMP for a TAZ X2 = Total employees in BASIC for a TAZ X3 = Total employees in RETAIL for a TAZ X4 = Total employees in SERVICE for a TAZ X5 = Total employees in OTHEREMP for a TAZ X6 = Total household for a TAZ

3. External Trips Analysis

The purpose of external trip analysis is to find the number of external trip productions and attractions at external stations, which are the allocation of the observed traffic volumes crossing

6 Trip production rates are drawn from CUUATS Household Travel Survey 2002-2003. 7 Establishment Survey needs to be conducted to draw the trip attraction rates since Household Travel Survey is too small to provide them. 8 Trip attraction rates are based on the NCHRP 365 “Travel Estimation Techniques for Urban Planning.”

17 the regional study area using the estimated percentage of through trips, percentage of trip purposes and residency, and vehicle occupancy rates by each trip purpose. Two major data sources are the 24-hour average daily traffic (ADT) volume and the information on trip characteristics such as percent through trips, trip purpose, and residency. The total number of external stations in Champaign-Urbana-Savoy Area is 20 and the total ADT was 64,295. Cordon counts were done in 2001. Refer to the Map 5 to see the location and its ADT.

1) Roadside origin-destination survey

CUUATS staff conducted a roadside origin-destination survey in April 2003. Five questions on the person’s trip origin and purpose, destination and purpose, and place of residency were asked. Since a small sample of locations was surveyed among the 20 external stations, average numbers for percent through, percent trip purposes, and percent residency were used. The following table summarizes the roadside interview surveys.

Table 10. Summary of the Roadside Origin-Destination Survey Item Percent Percent Through 9 % External trips (I-E or E-I) 91 % Percent Truck 4 % Percent Vans and Pickups 35 % Percent Residency 30 % Percent Non-Residency 70 % Percent Home-based work trips 57 % Percent Home-based school trips 6 % Percent Home-based shopping trips 9 % Percent Home-based other trips 21 % Percent Non-home-based trips 7 % Source: CUUATS Roadside Origin-Destination Survey, April 2003

2) External Trips

Trips at external stations consist of through trips and external trips. Through trips are defined as those trips that begin and end outside the study area. External trips are those trips that either start or end outside the study area. External trips are calculated by subtracting through trips from the ADT. The percentage of through trips differs between areas depending on the functional classification of the roadway and population. The average percentage of through trips from the CUUATS roadside survey is 9%.

Through trip = Percentage of through trips * ADT. External trip = ADT – Through trips

Application of trip purposes into external trips

After finding the volume of external trips, these trips are allocated by trip purpose, based on the percentages of trip purposes.

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Map 5. Cordon Count Locations

19 Table 11. Percent Residency and Trip Purposes from CUUATS Roadside Survey Trip Purpose Resident Non-resident9 Total Home-based work 13 % 44 % 57 % Home-based school 4 % 2 % 6 % Home-based shopping 2 % 7 % 9 % Home-based other 7 % 14 % 21 % Non-home-based 4 % 3 % 7 % Total 30 % 70 % 100 % Source: CUUATS Roadside Origin-Destination Survey, 2003.

Estimation of trip production and attraction

In case of home based trips, trip production and trip attraction are estimated by residency. Persons who live outside of the study area produce the trip at the external station and persons who live inside the study area attract the trips at the external stations. 30% residency and 70% non- residency percentages were applied to the allocated trip purposes based on the survey results.

Estimated external trips are vehicle trips, whereas internal trips are person trips. Consistency must be achieved between the two in order to accurately illustrate production and attraction. A person trip was converted into vehicle trips by dividing the number of vehicle occupants by the number of vehicle trips. The average vehicle occupancy rate was 1.3 persons per vehicle. The table below shows the final results. A total of 67,844 trips were produced and 28,955 were attracted.

Table 12. External Trip Productions and Attractions (Person Trips) Station Production Attraction Number HBW HBSch HBSho HBO NHB Total HBW HBSch HBSho HBO NHB Total 148 693 35 146 324 90 1,288 209 47 32 172 90 550 149 300 15 63 141 39 558 91 20 14 74 39 238 150 300 15 63 141 39 558 91 20 14 74 39 238 151 2,009 102 424 941 260 3,736 607 136 94 498 260 1,594 152 416 21 88 195 54 773 126 28 19 103 54 330 153 416 21 88 195 54 773 126 28 19 103 54 330 154 2,910 147 614 1,362 376 5,410 879 197 136 721 376 2,309 155 2,864 145 604 1,341 370 5,324 865 193 134 710 370 2,272 156 2,494 126 526 1,168 322 4,637 753 168 117 618 322 1,979 157 2,356 119 497 1,103 305 4,380 711 159 110 584 305 1,869 158 5,451 276 1,150 2,552 705 10,134 1,646 368 256 1,351 705 4,325 159 44 2 9 21 6 82 13 3 2 11 6 35 160 46 2 10 22 6 86 14 3 2 11 6 37 161 2,679 136 565 1,254 346 4,981 809 181 126 664 346 2,126 162 970 49 205 454 125 1,803 293 66 45 240 125 770 163 577 29 122 270 75 1,073 174 39 27 143 75 458 164 254 13 54 119 33 472 77 17 12 63 33 202 165 416 21 88 195 54 773 126 28 19 103 54 330 166 3,926 199 828 1,838 508 7,300 1,185 265 184 973 508 3,115 167 577 29 122 270 75 1,073 174 39 27 143 75 458 Total 29,700 1,505 6,267 13,904 3,840 55,216 8,966 2,006 1,393 7,361 3,840 23,566

9 Non-resident are the persons who live outside of the study area meaning the trip production at the external station.

20 4. Balancing

Trip productions and attractions should be equal since each trip must have two trip ends: a production and an attraction. However, they are often different since trip productions and attractions are estimated separately. Through this last step in trip generation analysis, the productions and attractions can be balanced. As trip production is more reliable than the trip attraction, it was used to estimate the regional control total of trips, which totaled 566,700.

External trips are a function of observed traffic volume so they cannot be changed. Trip production is the control total, which cannot be changed to balance production and attraction. Thus the only factor that can be used to make the total production and attraction the same is trip attraction in TAZs. The balancing factor is calculated from the equation below. The factor is then applied into the internal trip attractions by trip purposes in study area.

Production Attraction Production = Attraction TAZs Pz Az {Pz + Pe} = {(Az * x) + Ae}

External Pe Ae Balancing factor x = (Pz+Pe–Ae) / Az Total P A

The calculated balancing factors are listed below for each trip purpose. Based on the balancing factors, the Champaign-Urbana urbanized area generates a total of 566,700 trips per weekday as shown in Table 13.

§ Home-based work trips = 0.96 § Home-based school trips = 1.13 § Home-based shopping trips = 1.29 § Home-based other trips = 1.26 § Non-home-based trips = 1.16 § Total trips = 1.15

Table 13. Trip Generation Summary External Purpose Trips Generation Internal TAZs Stations Production 87,502 29,700 Home-based Work 117,202 Attraction 108,236 8,966 Production 36,476 1,505 Home-based School 37,981 Attraction 35,975 2,006 Production 62,404 6,267 Home-based Shopping 68,670 Attraction 67,278 1,393 Production 174,453 13,904 Home-based Other 188,357 Attraction 180,996 7,361 Production 150,650 3,840 Non-home-based 154,489 Attraction 150,650 3,840 Production 511,484 55,216 Total 566,700 Attraction 543,134 23,566

21 V. Trip Distribution

1. Overview

Trip distribution is the estimation of how many trips go from one TAZ to all other TAZs. This process uses trip generation output data as an input and converts it into matrices of person trip tables that represent the movement between TAZs. The most common methodology for trip distribution is the gravity model, where the number of trip exchanges between two zones is directly related to land use patterns or activities and inversely related to separation between two locations.

The trip distribution process has two major steps: 1) Estimation of friction factors based on travel times, and 2) Distribution of trip generation using gravity model. These processes can be implemented using a transportation planning software package such as TRANPLAN, EMME2, or TRANSCAD. The basic model structure is standard but the parameters and measures for separation such as time, cost, or combination of time and cost are different between regions. The next part of this documentation follows the procedural order that CUUATS underwent while implementing trip distribution.

Highway Network

Step 1 Build Travel Time

Step 2 Estimate Friction Factors

Production Step 3 Use of Gravity Model Attraction

Person Trip Table

Figure 6. Trip Distribution Process

22 2. Estimation of Impedances: Travel Times

Travel impedance may be defined by the path of least resistance between each pair of zones10. Travel time, distance, etc. are summed for the links between each zone pair and the results are stored in a zone-to-zone travel impedance matrix. TRANPLAN calculates travel impedance. The steps to estimate impedance are as follows:

§ Estimation of free-flow interzonal travel times: Free-flow travel times are calculated by using link lengths and speeds. Link length is identified as a part of network data and link speed is estimated by a posted speed for each link. Once the length and speed were defined, shortest time path and travel impedance between zones can be calculated.

§ Estimation of intrazonal travel times: Many of intrazonal travel take place on the local street network that is not coded; intrazonal travel times was estimated by the nearest neighborhood technique:

Nearest neighborhood technique: Average interzonal travel times to the nearest adjacent zones Intrazonal travel time = 2

§ Terminal times: Terminal times is a representation of impedances at both ends of a trip required to walk to and from a transit mode, to park or access a parked car, and so forth. Terminal times are different for area types. Modified NCHRP terminal times were used in CUUATS model.

Table 13. Typical Terminal Times for Different Area Types Area Type Terminal Time (minutes) CBD 3 CBD Fringe 2 Other Business District 2 Residential 1 Rural 1

3. Estimation of Friction Factor

Friction factors or f-factors are inputs into the gravity model along with trip productions and attractions. The friction factor quantifies the impedance and is inversely related to the impedance (as the travel time increases, the friction factor decreases). There are several methods to calculate friction factors: 1) generated from survey data, 2) borrowed from another study, 3) generated from a power function, 4) generated from exponential functions, or 5) generated from a gamma function. Since survey data are available, it is possible to generate friction factors from the local data for the CUUATS model. The process to estimate friction factor is shown in Figure 7. Refer to Table 14 for the results.

10 Martin, A. William, and Nancy A. Mcguckin (1998). Report 365: Travel Estimation Techniques for Urban Planning. National Academy Press. Washington D.C.

23

Survey Data

Build Trip Table

Survey Network Skim File (Production/ GMHFIL.IN File Attraction Format)

Build Gravity Model History File

Gravity Model History File

Calibrate Gravity Model

Friction Factor

Figure 7. Process to Estimate Friction Factors from the Survey

4. Use of Gravity Model

Once the friction factor is prepared from the survey data, the trips are distributed using Gravity Model. This model can be simply described in that all trips produced in a zone are attracted to other zones depending on the distance and activity. The gravity model assumes that all trip attractions are directly proportional to the relative activity level, and inversely proportional to the distance between the zones. The following equation explains the gravity model:

24

Pi ´ A j ´ F ij ´ K ij T ij = zones å A k ´ F ik ´ K ik k = 1

Where: T ij = the number of trips from zone i to zone j Pi = the number of trip productions in zone i A j = the number of trip attractions in zone j F ij = the friction factor relating the spatial separation between zone i and zone j K ij = an optional trip-distribution adjustment factor for interchanges between zone i and zone j

Input data for this process include: Trip Production Table, Trip Attraction Table, Friction Factor, and Highway Network Skim File. As a result, the final trip person distribution matrix is produced.

The Output of trip distribution was five person-trip tables. Although the control totals of each trip purpose were the same as the trip generation results, the output from this process was two- dimensional person-trip matrices showing the movement of trips between zones.

Table 14. Calibrated Friction Factors Minutes HBWork HBSchool HBShopping HBOther NHB 1 150,680 54,779 392,618 322,764 52,547 2 145,724 77,908 274,368 241,647 282,951 3 136,836 98,504 198,203 183,789 175,438 4 125,339 111,824 147,674 141,922 118,747 5 112,513 115,111 113,218 111,205 86,978 6 99,442 18,516 89,115 88,368 68,342 7 86,938 94,615 71,847 71,174 57,105 8 75,534 77,057 59,196 58,070 50,300 9 65,522 59,203 49,729 47,966 46,299 10 57,011 43,337 42,496 40,089 44,146 11 49,990 30,524 36,858 33,884 43,225 12 44,378 20,892 32,371 28,944 43,083 13 40,073 14,034 28,722 24,975 43,332 14 36,977 9,344 25,687 21,756 43,597 15 35,031 6,228 23,103 19,121 43,497 16 34,230 4,197 20,848 16,946 42,658 17 34,660 2,888 18,832 15,136 40,766 18 36,538 2,049 16,991 13,618 37,633 19 40,287 1,514 15,274 12,333 33,266

25 VI. Mode Choice

1. Mode Split Procedures

Mode choice is the third step among the four major steps in travel demand model. It is a process to split all person trips into auto travelers and transit passengers according to the relationships between the two different modes: private automobile and public transit.

Split is performed using diversion curves that are provided by the Tranplan program. The curves specify the percentages of transit travel as a function of the ratio or differences between one of the trip purpose, origin zone code, destination zone code, and trip impedance range. The model is using 5 trip purposes and 4 different area types (See the Table 15 below). Among 5 trip purposes, home-based shopping trips and home-based other trips share the same split curve since the percentages of transit users for those trips are similar. Thus, 4 split curves were used in this model.

Table 15. Production/Attraction code and Area types used in mode choice model Production or Attraction Code Area Type Traffic Analysis Zone 1 CBD, Fringe 1-43 Other Business Area 2 44-66, 140-141, 145 U of I, Parkland College 3 Residential Area 67-121, 136-139 4 Rural Area 122-135, 142-144, 146-167

Input in this step is total person trip, a transit skim file, and a highway skim file. Output is the transit passenger trip tables and the auto trip tables. As results, volumes by 4 split curves were shown in the Table 16.

Table 16. Volumes by Split Curves Scurves Trip Purposes Transit Highway Total 15,632 101,564 117,196 1 Home-Based Work (13%) (87%) (100%) 9,468 28,514 37,982 2 Home-Based School (25%) (75%) (100%) Home-Based Shopping & 7,342 249,687 257,029 3 Home-Based Other (3%) (97%) (100%) 9,787 144,701 154,490 4 Non-Home-Based (6%) (94%) (100%) 42,231 524,466 566,697 Total (7%) (93%) (100%)

The number of auto drivers can be determined through the auto occupancy curve, which specifies and splits the auto person trips into auto drivers and auto passengers. Auto occupancy curves were used to convert person trips to vehicle trips. Resulting volumes by those curves are 409,973 for auto drivers and 115,093 for auto passengers. The auto occupancy ratio was 1.3 persons per vehicle.

26

2. Creation of an origin-destination trip table

After a mode choice and before a trip assignment, production-attraction format of trip table should be converted into origin-destination format to get actual directions of trips. Production- attraction format of trips expresses the directions going from home-end of the trip (production) to non-home end of the trip (attraction). That doesn’t reflect the real directions from origin to destination. The method to convert production-attraction trip tables into origin-destination trip tables is to add one-half of the trip table to one-half of the transposed trip table. In Tranplan, this conversion is performed by a “matrix transpose” function and applied to home-based trips ranging from trip purpose 1 to trip purpose 4. Non-home-based trips have origin-destination direction by definition. These home-based and non-home-based trips in OD format were combined into one table by using the function of “Matrix Manipulate.”

27 VII. Trip Assignment

Trip assignment loads the highway and transit person trips on networks. Theses traffic loadings are done on the 24-hour time period. Final output of this process is assigned highway and transit trips on each of networks. Inputs for trip assignments are coded networks and trip tables generated from the mode choice process. Following sections describe the highway and transit trip assignment, respectively.

1. Highway Trip Assignment

1) Methodology

There are several methods for loading trips on the network: All-or-nothing assignment, capacity restraint assignment, incremental assignments, stochastic assignments, and equilibrium assignment. Equilibrium assignment is used with all newly developed models and mostly recommended. This technique is used in this model.

By definition, equilibrium is reached when “no travelers can reduce his or her travel time from origin to destination by switching to another path11.” This method is performed in the Tranplan function “Equilibrium Highway Load.” Modified Bureau of Public Roads (BPR) curves given in Highway Capacity Manual 2000 were used in this model. Free flow speeds and LOS E capacities are additional requirements.

2) Parameters

The Bureau of Public Roads (BPR) Curves has been used to estimate link travel times as a function of the volume-to-capacity ratio. Basic formula is shown in the box below. Highway Capacity Manual 2000 provides recommended coefficients for BPR curves according to the various road classifications. Modified BPR curves12 were used in this model. For 17 road classifications resulting from the combinations of functional class, speed, and area types, the BPR curve coefficients are shown in the Table 17 below and coded on Link Group 3 of Tranplan link database.

Tc = congested link travel time b æ v ö Tf = link free-flow travel time é ù v = assigned link traffic volume (vehicles) Tc =Tf ´ç1+a ´ê ú÷ è ë c û ø c = link capacity a, b = volume/delay coefficients

11 ODOT, Traffic Assignment Procedures, 2001

12 The modified BPR curves and coefficients were based on the “Traffic Assignment Procedures” from Ohio Department of Transportation, which is originated from Highway Capacity Manual 2000.

28 Table 17. BPR curve coefficients for Link Group3 Free Flow Roadway Link Functional Area Speed Lanes a b Classification Group3 Class Type* (mph) 1 6 65 Any Any 0.25 9.0 Highway and 2 6 55 Any Any 0.10 10.0 Ramps 17 7 30-25 Any Any 0.34 4.0 3 1-5 55 5 2 0.08 6.0 Multi-lane or 4 1-5 50-45 5 2 0.07 6.0 Rural Roadway 17 1-5 55-45 5 1 0.34 4.0 17 1-5 40-25 5 Any 0.34 4.0 5 1-5 55-50 3 Any 0.34 4.0 6 1-5 55-50 2, 4 Any 0.74 5.0 7 1-5 55-50 1 Any 1.16 6.0 8 1-5 45-40 3 Any 0.38 5.0 9 1-5 45-40 2,4 Any 0.70 5.0 10 1-5 45-40 1 Any 1.00 5.0 Urban Street 11 1-5 35 3 Any 0.96 5.0 12 1-5 35 2, 4 Any 1.00 5.0 13 1-5 35 1 Any 1.40 5.0 14 1-5 30-25 3 Any 1.11 5.0 15 1-5 30-25 2, 4 Any 1.20 5.0 16 1-5 30-25 1 Any 1.50 5.0 · Area type is the same coded on link file of the highway network. · Original source: Exhibits C30-1 and C30-2 on page 30-39, HCM 2000. · a and b are the BRP parameters for the equation.

2. Transit Trip Assignment

Transit trip assignment is to load transit passengers on the transit network. Input in this function is transit volume, transit network, and a minimum transit path. Output is a loaded transit “legs” file sorted by lines. In case that more than one line operate on one link, the method of “Frequency Split” will be applied, which is a way of dividing transit volume by the relative frequencies of the transit lines.

29 VIII. Time-Of-Day Analysis

Time of day analysis in this model is performed after trip assignment. The area transportation situation needs to figure out the specific time of day traffic volumes rather than 24-hour daily traffic volumes. Daily time period and percentages of traffic volume are split into three-time period shown at Table 18. PM-peak time which is from 4:40 PM to 5:30 PM has the most traffic volume reaching 12% of daily traffic volume.

Table 18. Percentage of peak periods by actual traffic counts done in 2002 (1/09/04) Period Time Percentage Traffic Volume* AM Peak 7:30 – 8:30 AM 10.23% Off-Peak 12:00 – 1:00 PM 11.16% PM Peak 4:30 – 5:30 PM 11.73% * Source: ADT and turning movement traffic counts 2002, CUUATS.

Method selected for doing time of day analysis after trip assignment may be sufficient for smaller MPOs where the duration and intensity of congestions are limited. This is mostly commonly used and simplest method. Data required are peak hour factors that reflect peak period link-level travel demand. Limitations are that this method does not consider peak travel times in assignment and does not account for localized effects of changes in demand. 24-hour assigned traffic volume is factored using the traffic percentages of each time period. The Table 19 is the traffic volume for Champaign-Urbana urbanized area resulting from the time-of-day analysis.

Table 19. Peak hour traffic volumes for Champaign-Urbana Urbanized Area Period Estimated Volume Percentage AM Peak 929,086 10% Off-Peak 842,976 11% PM Peak 886,031 12% 24-hour 7,553,549 100%

30 IX. Model Validation

Once transportation model was set up, model validation should be done to verify the estimated model results comparing with the actual traffic count data. The root mean square error check, volume check, plot check and vehicle miles traveled (VMT) check are commonly performed for a base year trip assignment.

1. Plot Check

This is the comprehensive check for the trip assignment. Plot shows the assigned traffic volumes on each link of the network. These volumes are compared with actual traffic count data considering whether the trip assignment results seem reasonable in general and whether there are links with overestimated or underestimated volumes when compared in detail. The map 6 shows the overall display of traffic volumes for year 2000.

2. Volume Check

1) % Root Mean Square Error

The percent root mean square error (%RMSE) is “a measure of the relative error of the assignment compared to ground counts.” The equation for this is given in the box below. The %RMSE is often used to compare the accuracy between estimated and measured traffic volumes. It is considered that acceptable range for the %RMSE is about 40% or less. The base year model for Champaign-Urbana Urbanized Area has 39% of %RMSE.

Equation

2 å (Model j - Count j ) å Count j %RMSE =100* j ( j ) (NumberofCounts -1) NumberofCounts

2) Average Volume Ratio

Another method for model validating using traffic volume is comparing the estimated model results with traffic count data results according to the road classifications. Average volume ratio by road classification is shown on the Table 20.

Table 20. Average Volume Ratio by Road Classification Road Classification Observations (Number of links) Ratio (Model Estimation / Count) Major Arterials 157 0.88 Minor Arterials 373 0.95 Collectors 331 0.82 Total 898 0.90

31

Map 6. Highway Assignment with Multi-band Width

32

3. Vehicle Miles Traveled Check

Vehicle miles traveled (VMT) is obtained by multiplying the assigned volume and the distance of the link. The total VHT estimated was 1,581,367 miles and the study area has 125,264 population and 50,254 household. VMT per household/ capita and VMT by road classification are considered for checking the reasonableness of the model. Regarding VMT per household, acceptable range for this is 30 to 40 VMT per household and model result is 31.5 VMT per household as shown in the Table 21. Estimated VMT per capita is 12.6 while the acceptable range for this is 10 to 16 VMT per capita is acceptable.

Table 20. VMT per household and per capita.

ITEM Acceptable range* Model Results

VMT per household 30-40 VMT/HH 31.5 VMT/HH

VMT per capita 10-16 VMT/capita 12.6 VMT/Capita

* Source: Model calibration and validation seminar by TMIP, FHWA

Regarding VMT by road classification, arterials and collectors were considered for checking. Difference between actual VMT and estimated VMT were calculated and compared. VMT difference for arterials and collectors were 7.3% and 17.7%, respectively. If VMT difference for arterials is 10% or less and collectors is 20% or less, then they are acceptable.

Table 21. VMT by Road Classification Roadway Type Acceptable range* Model Results Arterials Under 10% 7.3 % Collectors Under 20% 17.7 % * Source: Model calibration and validation seminar by TMIP, FHWA

33 X. Reference

1. Alvin Whyte (2000). Travel Demand Forecasting Manual 2: Highway Network Coding Procedures. Ohio DOT.

2. FHWA (2001). Model Validation and Reasonableness Checking Manual.

3. Gregory Giamo (2001). Travel Demand Forecasting Manual 1: Traffic Assignment Procedures. Ohio DOT.

4. Martin, A. William, and Nancy A. Mcguckin (1998). Report 365: Travel Estimation Techniques for Urban Planning. National Academy Press. Washington D.C.

5. Thurston Regional Planning Commission (2002). Transportation Modeling for policy makers: Explaining the Mystery of the Black Box.

6. FHWA (2003). Model Validation Seminar. Travel Model Improvement Program.

7. US DOT and FHWA (1990). Calibration and Adjustment of System Planning Models.

34 XI. Appendices

§ APPENDIX A: HOUSEHOLD SIZE BY TAZ § APPENDIX B: EMPLOYMENT BY TAZ § APPENDIX C: UNBALANCED TRIP PRODUCTIONS AND ATTRACTIONS § APPENDIX D: BALANCED TRIP PRODUCTIONS AND ATTRACTIONS

35 APPENDIX A: Household Size By TAZ

Household Size ID TAZ2003 Population Households 1-person 2-person 3-person 4+person Total 125264 50254 17600 16881 7128 8645 1 CHP092_B 132 0 0 0 0 0 2 CHP124_B 134 76 49 16 5 6 3 CHP123 82 53 35 11 4 3 4 CHP092_C 26 16 7 8 1 0 5 CHP124_A 65 57 53 2 1 1 6 URB006 119 6 2 2 1 1 7 URB003 432 251 143 67 25 16 8 CHP092_A 17 9 4 3 1 1 9 CHP093 1085 649 420 153 38 38 10 CHP164 437 267 173 67 11 16 11 CHP179 1227 662 345 177 74 66 12 CHP180 866 500 280 142 31 47 13 CHP122 698 326 120 110 53 43 14 CHP116 642 322 146 100 37 39 15 CHP081 1516 676 199 261 109 107 16 CHP044 533 311 154 110 37 10 17 CHP043 1707 816 373 270 79 94 18 CHP035_A 2 1 0 1 0 0 19 CHP035_B 1149 639 369 181 53 36 20 CHP035_C 5 4 3 1 0 0 21 CHP031_B 0 0 0 0 0 0 22 CHP071 1232 684 322 240 74 48 23 CHP141 409 192 83 56 24 29 24 CHP146 1701 776 268 288 100 120 25 CHP098 767 314 88 118 40 68 26 CHP062 227 130 63 52 8 7 27 CHP067 1218 565 240 168 75 82 28 CHP095 1172 553 236 158 73 86 29 CHP025 1258 446 132 103 80 131 30 CHP169 461 200 51 85 28 36 31 URB040 1109 642 360 181 53 48 32 URB039 1193 527 147 223 53 104 33 URB037 2372 1050 409 310 130 201 34 URB001 1361 686 291 228 89 78 35 URB008 230 100 38 34 15 13 36 URB022 513 239 102 60 38 39 37 URB097 1374 745 399 236 63 47 38 URB021 856 349 95 131 52 71 39 URB020_B 923 314 104 101 46 63 40 URB010 481 230 91 78 35 26

36 Household Size ID TAZ2003 Population Households 1-person 2-person 3-person 4+person 41 URB030 1116 553 221 202 61 69 42 URB075_C 768 364 168 99 52 45 43 URB054 812 310 83 99 52 76 44 CHP053_B 22 14 9 3 1 1 45 CHP053_A 1026 603 374 122 59 48 46 CHP020 1937 1101 599 283 138 81 47 URB056 237 153 81 64 5 3 48 URB052 1085 537 164 244 95 34 49 URB058 773 318 111 167 12 28 50 URB057 0 0 0 0 0 0 51 CHP019 951 365 86 64 142 73 52 CHP052_A 717 306 110 110 65 21 53 CHP052_B 209 134 84 38 5 7 54 CHP086_A 1872 760 265 271 85 139 55 CHP051 8302 1301 464 315 180 342 56 CHP018 2449 511 249 30 30 202 57 URB060 5025 338 209 83 36 10 58 CHP049 0 0 0 0 0 0 59 URB064_A 5 2 0 1 1 0 60 CHP086_B 0 0 0 0 0 0 61 CHP010_A 292 154 53 75 20 6 62 CHP031_A 24 10 3 3 2 2 63 CHP065 0 0 0 0 0 0 64 CHP026_A 1096 497 214 149 76 58 65 CHP026_B 149 55 12 16 10 17 66 CHP026_C 93 30 6 11 3 10 67 CHP068 2970 1316 417 459 211 229 68 CHP036 1464 519 104 150 111 154 69 CHP072 2412 910 187 313 186 224 70 CHP144 1590 659 191 218 123 127 71 CHP038_A 889 344 46 173 45 80 72 CHP038_B 1064 473 134 209 52 78 73 CHP074 816 336 79 133 54 70 74 CHP110 606 251 66 95 38 52 75 CHP076 1272 414 32 127 99 156 76 CHP077 2308 877 203 309 150 215 77 CHP041 2313 811 115 265 168 263 78 CHP028 763 293 74 98 47 74 79 CHP063 1555 656 178 251 100 127 80 CHP066 1010 333 58 87 78 110

37 Household Size ID TAZ2003 Population Households 1-person 2-person 3-person 4+person 81 CHP139 586 275 92 107 43 33 82 CHP137 1011 437 130 170 62 75 83 CHP136 646 312 134 100 27 51 84 CHP140 689 317 97 128 47 45 85 CHP168 497 234 72 99 34 29 86 CHP143 1027 496 194 185 48 69 87 CHP147 889 391 100 174 50 67 88 CHP148 890 369 91 140 56 82 89 CHP114 665 289 80 122 36 51 90 CHP078 960 422 133 156 56 77 91 CHP079 971 395 78 184 46 87 92 CHP042 1095 417 84 160 61 112 93 CHP134 786 311 96 91 57 67 94 CHP135 898 457 225 127 45 60 95 CHP058 263 94 21 25 22 26 96 CHP117 1737 802 288 276 119 119 97 CHP010_B 1262 520 135 182 95 108 98 CHP022 563 194 43 57 33 61 99 CHP021 790 264 79 63 42 80 100 URB045_C 396 149 39 49 20 41 101 URB045_B 660 248 35 82 64 67 102 URB053 625 282 86 116 39 41 103 URB045_A 478 222 70 94 31 27 104 URB020_A 311 92 8 14 16 54 105 URB036 1951 640 172 242 93 133 106 URB013 295 160 82 42 18 18 107 URB065 1563 648 162 214 145 127 108 URB069 1065 423 80 174 79 90 109 URB064_B 287 155 73 52 17 13 110 URB090 1539 615 153 215 118 129 111 URB091 997 541 248 202 46 45 112 URB086 701 297 82 101 62 52 113 URB023 966 389 79 167 54 89 114 URB083 488 44 8 15 7 14 115 URB082 1501 613 174 205 105 129 116 URB012 2290 1153 439 460 147 107 117 URB028 3111 1348 443 434 208 263 118 URB074 1591 869 409 300 100 60 119 URB073 1459 631 157 274 83 117 120 URB075_A 82 28 3 8 9 8

38 Household Size ID TAZ2003 Population Households 1-person 2-person 3-person 4+person 121 URB078 746 278 49 92 58 79 122 NWF005_A 176 66 12 27 9 18 123 CHP005 22 7 2 1 0 4 124 CHP008 477 165 14 66 35 50 125 SWAIR1_C 44 18 2 9 4 3 126 SWAIR1_B 50 20 3 12 2 3 127 SWAIR1_A 1947 884 267 359 118 140 128 URB064_C 184 71 12 31 10 18 129 NEF005_A 132 44 5 15 9 15 130 URB046 818 344 105 113 51 75 131 NEF005_B 56 25 6 12 3 4 132 NEF005_C 224 87 15 38 14 20 133 NEF005_D 26 11 4 3 2 2 134 CHP003 158 62 12 24 12 14 135 CHP009 309 133 39 43 29 22 136 CHP002 36 13 1 5 4 3 137 CHP006 764 219 7 50 47 115 138 CHP007 10 4 1 1 1 1 139 CHP004 777 268 27 106 52 83 140 CHP026_D 4 1 0 0 0 1 141 CHP026_E 0 0 0 0 0 0

39 APPENDIX B: EMPLOYMENT BY TAZ

ID TAZ2003 TOTAL BASIC RETAIL SERVICE OTHER Total 70957 14531 11625 22224 37108 1 CHP092_B 560 25 24 458 78 2 CHP124_B 1097 16 46 1035 16 3 CHP123 788 159 137 490 161 4 CHP092_C 1060 378 164 18 878 5 CHP124_A 308 21 56 178 74 6 URB006 465 60 30 375 60 7 URB003 286 10 98 165 23 8 CHP092_A 1064 719 35 206 823 9 CHP093 301 0 142 151 8 10 CHP164 486 0 0 218 268 11 CHP179 573 1 0 499 74 12 CHP180 212 0 17 55 140 13 CHP122 489 103 257 124 108 14 CHP116 219 0 77 142 0 15 CHP081 2537 190 440 1798 299 16 CHP044 1365 543 182 518 665 17 CHP043 949 18 430 463 56 18 CHP035_A 498 384 0 114 384 19 CHP035_B 412 125 36 191 185 20 CHP035_C 322 57 83 182 57 21 CHP031_B 801 136 396 251 154 22 CHP071 864 35 464 292 108 23 CHP141 394 0 78 7 309 24 CHP146 405 12 114 152 139 25 CHP098 1624 1600 5 14 1605 26 CHP062 109 12 57 40 12 27 CHP067 76 16 60 0 28 CHP095 1023 541 203 274 546 29 CHP025 312 262 6 34 272 30 CHP169 175 0 1 174 31 URB040 784 10 294 253 237 32 URB039 507 0 3 492 12 33 URB037 149 0 11 69 69 34 URB001 511 12 50 112 349 35 URB008 664 164 254 139 271 36 URB022 1084 1048 18 18 1048 37 URB097 229 39 133 57 39 38 URB021 372 0 148 47 177 39 URB020_B 4162 0 15 4142 5 40 URB010 703 606 27 70 606

40 ID TAZ2003 TOTAL BASIC RETAIL SERVICE OTHER 41 URB030 262 43 123 84 55 42 URB075_C 420 0 316 77 27 43 URB054 1340 2 20 1289 31 44 CHP053_B 301 56 121 52 128 45 CHP053_A 135 14 61 60 14 46 CHP020 54 0 17 7 30 47 URB056 489 0 0 0 489 48 URB052 288 95 15 3 270 49 URB058 304 1 0 31 273 50 URB057 165 0 0 0 165 51 CHP019 652 0 194 113 345 52 CHP052_A 422 10 232 180 10 53 CHP052_B 52 0 24 28 0 54 CHP086_A 474 46 110 48 316 55 CHP051 969 5 27 170 772 56 CHP018 2176 110 309 246 1621 57 URB060 7455 10 123 205 7127 58 CHP049 86 0 3 0 83 59 URB064_A 867 5 2 13 852 60 CHP086_B 373 125 6 143 224 61 CHP010_A 1320 10 22 55 1243 62 CHP031_A 1775 608 31 336 1408 63 CHP065 129 31 28 70 31 64 CHP026_A 979 327 431 216 332 65 CHP026_B 1505 12 1447 46 12 66 CHP026_C 1703 1180 5 118 1580 67 CHP068 328 86 6 83 239 68 CHP036 31 17 0 4 27 69 CHP072 113 5 2 19 92 70 CHP144 268 26 19 21 228 71 CHP038_A 71 8 1 42 28 72 CHP038_B 112 15 0 97 15 73 CHP074 247 62 49 127 71 74 CHP110 90 13 26 51 75 CHP076 239 5 0 149 90 76 CHP077 139 6 0 133 6 77 CHP041 107 15 7 25 75 78 CHP028 18 0 2 11 5 79 CHP063 104 1 0 22 82 80 CHP066 184 0 21 157 6

41 ID TAZ2003 TOTAL BASIC RETAIL SERVICE OTHER 81 CHP139 208 200 2 6 200 82 CHP137 181 70 8 33 140 83 CHP136 49 0 6 26 17 84 CHP140 289 0 9 4 276 85 CHP168 194 0 0 13 181 86 CHP143 52 27 6 19 27 87 CHP147 602 1 11 79 512 88 CHP148 14 0 0 14 0 89 CHP114 204 9 22 92 90 90 CHP078 10 0 0 10 0 91 CHP079 18 0 0 18 0 92 CHP042 280 0 1 249 30 93 CHP134 331 8 0 33 298 94 CHP135 37 6 0 31 6 95 CHP058 601 500 3 98 500 96 CHP117 118 7 1 15 102 97 CHP010_B 15 0 0 15 0 98 CHP022 74 0 30 39 5 99 CHP021 327 10 7 40 280 100 URB045_C 28 10 0 18 10 101 URB045_B 701 310 3 388 310 102 URB053 247 37 25 98 124 103 URB045_A 662 234 141 277 244 104 URB020_A 8 0 0 8 0 105 URB036 51 0 0 27 24 106 URB013 292 0 2 10 280 107 URB065 70 0 0 2 68 108 URB069 19 0 0 19 0 109 URB064_B 211 0 0 211 0 110 URB090 148 4 2 142 4 111 URB091 207 37 23 147 37 112 URB086 39 4 20 12 7 113 URB023 105 2 9 94 2 114 URB083 927 0 17 910 115 URB082 265 203 28 34 203 116 URB012 407 80 7 21 379 117 URB028 166 5 38 55 73 118 URB074 78 0 2 61 15 119 URB073 83 0 0 24 59 120 URB075_A 74 0 48 16 10

42 ID TAZ2003 TOTAL BASIC RETAIL SERVICE OTHER 121 URB078 6 0 0 6 0 122 NWF005_A 157 108 3 21 133 123 CHP005 0 0 0 0 0 124 CHP008 39 12 2 25 12 125 SWAIR1_C 13 11 0 2 11 126 SWAIR1_B 171 55 3 4 164 127 SWAIR1_A 727 24 458 191 78 128 URB064_C 12 3 0 9 3 129 NEF005_A 96 24 16 56 24 130 URB046 1326 384 702 235 389 131 NEF005_B 534 438 19 77 438 132 NEF005_C 776 726 0 50 726 133 NEF005_D 0 0 0 0 0 134 CHP003 86 45 10 31 45 135 CHP009 0 0 0 0 0 136 CHP002 927 613 3 311 613 137 CHP006 83 0 0 83 0 138 CHP007 2 0 0 2 0 139 CHP004 146 101 1 39 106 140 CHP026_D 930 1 792 137 1 141 CHP026_E 849 829 20 0

43 APPENDIX C: UNBALANCED TRIP PRODUCTIONS AND ATTRACTIONS Trip Production Trip Attraction ID TAZ 2003 HBW HBSch HBSho HBO NHB TOTAL HBW HBSch HBSho HBO NHB TOTAL 1 CHP092_B 0 0 0 0 0 0 893 159 262 716 756 2,786 2 CHP124_B 110 67 69 204 197 648 1,750 346 569 1,559 1,624 5,849 3 CHP123 76 47 47 138 137 446 1,257 338 555 1,521 1,382 5,053 4 CHP092_C 24 12 17 47 45 146 1,691 302 496 1,358 1,255 5,102 5 CHP124_A 69 59 35 113 128 404 491 138 226 620 560 2,035 6 URB006 11 4 8 21 18 61 742 145 239 653 667 2,445 7 URB003 380 211 248 703 677 2,219 456 216 354 970 810 2,807 8 CHP092_A 15 7 10 28 26 86 1,697 167 274 752 887 3,778 9 CHP093 928 574 587 1,709 1,677 5,475 480 327 537 1,471 1,201 4,016 10 CHP164 378 236 241 703 687 2,245 775 115 188 516 582 2,177 11 CHP179 1,041 540 693 1,968 1,831 6,073 914 228 375 1,026 1,063 3,607 12 CHP180 751 419 501 1,439 1,345 4,455 338 118 194 531 501 1,683 13 CHP122 562 239 395 1,091 970 3,256 780 442 726 1,990 1,561 5,500 14 CHP116 524 251 360 1,014 917 3,066 349 189 310 848 712 2,408 15 CHP081 1,203 469 873 2,397 2,069 7,011 4,047 1,197 1,967 5,388 4,894 17,492 16 CHP044 485 249 327 897 865 2,823 2,177 482 792 2,170 2,041 7,663 17 CHP043 1,309 638 907 2,553 2,309 7,717 1,514 835 1,371 3,756 3,030 10,505 18 CHP035_A 2 1 2 4 3 11 794 60 98 268 362 1,582 19 CHP035_B 953 540 623 1,769 1,709 5,595 657 203 333 912 868 2,973 20 CHP035_C 5 4 3 9 10 31 514 168 275 754 648 2,359 21 CHP031_B 0 0 0 0 0 0 1,278 626 1,029 2,819 2,202 7,954 22 CHP071 1,083 539 743 2,058 1,923 6,346 1,378 823 1,352 3,702 2,914 10,168 23 CHP141 319 148 221 625 554 1,867 628 160 263 722 637 2,410 24 CHP146 1,334 560 959 2,665 2,315 7,833 646 316 519 1,422 1,218 4,122 25 CHP098 561 216 414 1,159 964 3,314 2,590 178 292 800 1,096 4,956 26 CHP062 198 104 138 383 359 1,181 174 108 178 488 388 1,336 27 CHP067 944 432 654 1,841 1,637 5,507 121 116 191 523 462 1,413 28 CHP095 926 423 640 1,812 1,602 5,404 1,632 472 775 2,123 1,882 6,883 29 CHP025 832 311 595 1,707 1,385 4,829 498 100 164 450 467 1,679 30 CHP169 359 135 267 733 619 2,113 279 41 68 186 207 782 31 URB040 970 537 640 1,823 1,732 5,702 1,250 581 954 2,614 2,143 7,543 32 URB039 924 363 691 1,924 1,606 5,508 809 207 340 931 959 3,246 33 URB037 1,793 784 1,264 3,595 3,088 10,524 238 184 303 829 756 2,309 34 URB001 1,134 524 787 2,191 1,981 6,616 815 221 362 993 943 3,333 35 URB008 171 74 120 332 295 991 1,059 423 695 1,904 1,533 5,615 36 URB022 407 183 278 788 697 2,353 1,729 143 236 646 813 3,567 37 URB097 1,133 613 758 2,134 2,029 6,668 365 306 502 1,375 1,106 3,654 38 URB021 630 238 462 1,285 1,078 3,694 593 279 459 1,257 1,019 3,608 39 URB020_B 555 224 398 1,118 949 3,244 6,638 1,149 1,888 5,171 5,711 20,557 40 URB010 389 172 271 748 675 2,254 1,121 134 221 604 674 2,754 41 URB030 915 415 648 1,805 1,606 5,389 418 273 449 1,230 1,000 3,370 42 URB075_C 600 285 406 1,144 1,040 3,475 670 511 839 2,298 1,742 6,059 43 URB054 572 211 417 1,172 966 3,338 2,137 411 674 1,847 1,979 7,049 44 CHP053_B 20 12 13 37 36 119 480 193 317 869 692 2,552 45 CHP053_A 900 524 568 1,649 1,595 5,235 215 185 304 832 694 2,230 46 CHP020 1,716 910 1,121 3,165 3,021 9,932 86 180 296 811 708 2,082 47 URB056 223 126 154 425 411 1,338 780 59 97 265 353 1,553 48 URB052 934 374 673 1,787 1,629 5,397 459 117 192 526 515 1,809 49 URB058 509 231 382 1,042 923 3,087 485 73 120 329 366 1,374 50 URB057 0 0 0 0 0 0 263 13 21 57 91 445 51 CHP019 746 239 507 1,378 1,199 4,067 1,040 376 617 1,690 1,415 5,138 52 CHP052_A 533 222 369 990 918 3,032 673 412 677 1,853 1,458 5,073 53 CHP052_B 190 117 123 356 347 1,134 83 59 97 266 219 724 54 CHP086_A 1,304 551 942 2,649 2,261 7,707 756 295 484 1,326 1,151 4,012 55 CHP051 2,311 949 1,639 4,736 3,909 13,544 1,546 322 528 1,448 1,486 5,330 56 CHP018 866 411 595 1,866 1,454 5,192 3,471 688 1,131 3,097 2,891 11,278 57 URB060 499 293 314 890 892 2,888 11,891 820 1,347 3,689 4,931 22,677 58 CHP049 0 0 0 0 0 0 137 11 17 47 59 272 59 URB064_A 4 1 3 8 7 23 1,383 72 118 324 496 2,393 60 CHP086_B 0 0 0 0 0 0 595 63 104 284 339 1,384

44

Trip Production Trip Attraction ID TAZ 2003 HBW HBSch HBSho HBO NHB TOTAL HBW HBSch HBSho HBO NHB TOTAL 61 CHP010_A 256 111 185 492 455 1,499 2,105 162 266 729 940 4,202 62 CHP031_A 18 7 13 36 31 105 2,831 241 395 1,083 1,363 5,914 63 CHP065 0 0 0 0 0 0 206 60 98 268 236 867 64 CHP026_A 831 381 569 1,586 1,439 4,805 1,562 748 1,229 3,368 2,685 9,592 65 CHP026_B 106 36 78 221 176 616 2,400 2,026 3,329 9,118 6,624 23,496 66 CHP026_C 56 19 43 123 95 336 2,716 164 269 736 1,064 4,949 67 CHP068 2,335 929 1,676 4,651 4,000 13,591 523 231 379 1,039 992 3,164 68 CHP036 1,014 334 743 2,089 1,678 5,858 49 75 123 338 306 891 69 CHP072 1,744 588 1,283 3,557 2,919 10,091 180 141 232 634 585 1,772 70 CHP144 1,202 455 863 2,392 2,037 6,948 427 141 231 633 601 2,034 71 CHP038_A 648 210 504 1,380 1,113 3,856 113 62 102 280 265 822 72 CHP038_B 825 326 614 1,691 1,438 4,894 179 92 151 414 396 1,233 73 CHP074 618 223 458 1,266 1,054 3,619 394 153 252 689 612 2,101 74 CHP110 455 170 335 931 778 2,670 144 64 104 286 259 856 75 CHP076 865 240 654 1,837 1,409 5,005 381 103 170 465 474 1,593 76 CHP077 1,640 580 1,210 3,378 2,769 9,578 222 157 258 706 661 2,003 77 CHP041 1,619 498 1,213 3,404 2,676 9,409 171 134 221 605 552 1,683 78 CHP028 543 197 399 1,121 917 3,176 29 47 77 210 187 549 79 CHP063 1,183 448 868 2,403 2,026 6,928 166 103 169 463 435 1,337 80 CHP066 667 210 489 1,382 1,093 3,842 293 117 192 526 488 1,616 81 CHP139 476 196 341 931 826 2,771 332 58 95 260 278 1,023 82 CHP137 772 304 564 1,558 1,332 4,530 289 91 150 410 397 1,336 83 CHP136 510 240 359 1,024 894 3,028 78 60 98 269 242 747 84 CHP140 556 222 404 1,105 962 3,249 461 79 129 354 372 1,395 85 CHP168 407 164 296 806 708 2,382 309 50 82 224 245 910 86 CHP143 821 371 587 1,641 1,442 4,862 83 84 138 379 340 1,024 87 CHP147 696 264 519 1,425 1,206 4,110 960 130 213 583 651 2,536 88 CHP148 676 247 500 1,392 1,152 3,968 22 55 90 247 221 635 89 CHP114 510 198 378 1,044 884 3,016 325 102 167 457 429 1,480 90 CHP078 740 298 538 1,499 1,277 4,352 16 61 100 275 245 698 91 CHP079 722 255 553 1,525 1,245 4,299 29 59 98 268 241 694 92 CHP042 783 270 589 1,650 1,326 4,618 447 127 208 570 579 1,931 93 CHP134 566 218 403 1,132 956 3,276 528 75 123 336 379 1,440 94 CHP135 728 366 495 1,414 1,278 4,281 59 72 118 324 296 868 95 CHP058 183 62 132 370 302 1,050 959 81 134 366 470 2,009 96 CHP117 1,384 584 981 2,724 2,389 8,062 188 124 204 559 522 1,598 97 CHP010_B 959 351 698 1,934 1,625 5,568 24 76 125 342 306 873 98 CHP022 371 128 274 779 618 2,169 118 79 130 356 296 979 99 CHP021 488 185 351 1,013 816 2,854 522 78 129 352 384 1,465 100 URB045_C 273 101 202 574 463 1,613 45 26 43 118 111 343 101 URB045_B 500 151 369 1,015 823 2,857 1,118 164 269 738 833 3,122 102 URB053 493 197 359 986 855 2,889 394 109 179 490 465 1,638 103 URB045_A 384 156 279 760 669 2,249 1,056 318 522 1,429 1,258 4,582 104 URB020_A 196 54 150 446 313 1,160 13 15 24 67 61 180 105 URB036 1,156 436 851 2,367 1,978 6,787 81 98 160 439 401 1,179 106 URB013 254 130 169 483 445 1,480 466 49 81 221 264 1,081 107 URB065 1,220 433 877 2,410 2,047 6,986 112 96 157 430 396 1,191 108 URB069 801 270 598 1,637 1,356 4,660 30 64 104 286 258 742 109 URB064_B 247 122 169 471 436 1,445 337 77 126 345 364 1,248 110 URB090 1,144 411 833 2,304 1,933 6,626 236 125 206 565 537 1,669 111 URB091 853 423 595 1,654 1,522 5,047 330 148 243 667 616 2,004 112 URB086 547 203 392 1,076 925 3,143 62 73 119 327 273 854 113 URB023 719 252 544 1,505 1,230 4,251 167 91 150 410 380 1,198 114 URB083 85 28 64 180 142 499 1,479 81 132 363 547 2,602 115 URB082 1,117 422 808 2,254 1,895 6,496 423 148 244 667 620 2,102 116 URB012 1,920 853 1,364 3,730 3,375 11,243 649 204 335 919 902 3,010 117 URB028 2,389 961 1,710 4,792 4,082 13,933 265 260 426 1,168 1,026 3,144 118 URB074 1,381 684 944 2,614 2,447 8,071 124 140 231 632 576 1,703 119 URB073 1,132 423 846 2,327 1,955 6,683 132 98 161 442 411 1,246 120 URB075_A 59 17 43 118 95 331 118 75 124 339 259 915 121 URB078 544 175 403 1,125 904 3,152 10 40 66 180 161 457 122 NWF005_A 124 42 95 264 211 736 250 29 48 131 151 609 123 CHP005 13 5 10 31 21 80 0 1 2 4 4 11

45

Trip Production Trip Attraction ID TAZ 2003 HBW HBSch HBSho HBO NHB TOTAL HBW HBSch HBSho HBO NHB TOTAL 124 CHP008 334 96 255 704 554 1,943 62 33 54 149 139 438 125 SWAIR1_C 35 11 27 71 59 203 21 4 6 17 19 67 126 SWAIR1_B 36 12 28 76 64 216 273 21 34 93 120 540 127 SWAIR1_A 1,547 618 1,132 3,118 2,682 9,097 1,160 813 1,336 3,660 2,847 9,816 128 URB064_C 134 45 102 283 228 792 19 12 20 56 53 160 129 NEF005_A 89 26 67 189 147 518 153 45 74 202 183 656 130 URB046 617 241 446 1,255 1,051 3,610 2,115 1,112 1,827 5,005 3,879 13,938 131 NEF005_B 44 17 33 91 77 263 852 84 137 377 442 1,891 132 NEF005_C 164 55 125 342 279 965 1,238 81 133 365 513 2,330 133 NEF005_D 19 8 14 38 33 112 0 2 3 7 6 17 134 CHP003 118 40 88 241 199 685 137 34 56 153 145 525 135 CHP009 244 92 173 475 412 1,396 0 18 30 83 73 205 136 CHP002 27 7 20 54 44 153 1,479 135 221 606 768 3,208 137 CHP006 475 122 365 1,059 761 2,782 132 52 86 234 230 734 138 CHP007 8 3 5 15 13 44 3 1 2 5 5 16 139 CHP004 536 159 410 1,138 893 3,135 233 57 93 256 262 901 140 CHP026_D 2 1 2 6 3 14 1,483 1,134 1,863 5,102 3,754 13,336 141 CHP026_E 0 0 0 0 0 0 1,354 1,154 1,896 5,194 3,765 13,364 142 URB100 74 24 56 155 124 433 11 6 10 28 26 82 143 URB101 75 26 55 153 126 436 38 39 64 175 130 446 144 URB102 16 9 11 30 30 96 11 2 4 11 11 40 145 URB103 0 0 0 0 0 0 0 0 0 0 0 0 146 URB104 17 6 11 31 28 93 3 1 2 6 6 19 147 URB105 33 10 26 73 56 198 0 2 4 11 9 26 Internal total 87,502 36,476 62,404 174,453 150,650 511,484 113,240 31,804 52,250 143,119 129,997 470,410 148 Staley & Monticello 693 35 146 324 90 1,288 209 47 32 172 90 550 149 Rising & Windsor 300 15 63 141 39 558 91 20 14 74 39 238 150 Rising & Kirby 300 15 63 141 39 558 91 20 14 74 39 238 151 Rising & Springfield 2,009 102 424 941 260 3,736 607 136 94 498 260 1,594 152 Rising & Bradley 416 21 88 195 54 773 126 28 19 103 54 330 153 Rising & Cardinal 416 21 88 195 54 773 126 28 19 103 54 330 154 Rising & Bloomington 2,910 147 614 1,362 376 5,410 879 197 136 721 376 2,309 155 Mattis & Olympian 2,864 145 604 1,341 370 5,324 865 193 134 710 370 2,272 156 Prospect & Olympian 2,494 126 526 1,168 322 4,637 753 168 117 618 322 1,979 157 Market & Olympian 2,356 119 497 1,103 305 4,380 711 159 110 584 305 1,869 158 Cunningham & Olympian 5,451 276 1,150 2,552 705 10,134 1,646 368 256 1,351 705 4,325 159 High Cross & Ford Harris 44 2 9 21 6 82 13 3 2 11 6 35 160 Cottonwood & Airport 46 2 10 22 6 86 14 3 2 11 6 37 161 Cottonwood & Univerisity 2,679 136 565 1,254 346 4,981 809 181 126 664 346 2,126 162 Cottonwood & Windsor 970 49 205 454 125 1,803 293 66 45 240 125 770 163 High Cross & Curtis 577 29 122 270 75 1,073 174 39 27 143 75 458 164 Philo & Curtis 254 13 54 119 33 472 77 17 12 63 33 202 165 First & Old church 416 21 88 195 54 773 126 28 19 103 54 330 166 Neil & Monticello 3,926 199 828 1,838 508 7,300 1,185 265 184 973 508 3,115 167 Duncan & Monticello 577 29 122 270 75 1,073 174 39 27 143 75 458 External total 29,700 1,505 6,267 13,904 3,840 55,216 8,966 2,006 1,393 7,361 3,840 23,566 TOTAL 117,202 37,981 68,670 188,357 154,489 566,700 122,206 33,810 53,642 150,480 133,837 493,975

46 APPENDIX D: BALANCED TRIP PRODUCTIONS AND ATTRACTIONS Trip Production Trip Attraction ID TAZ 2003 HBW HBSch HBSho HBO NHB TOTAL HBW HBSch HBSho HBO NHB TOTAL 1 CHP092_B 0 0 0 0 0 0 854 180 337 906 876 3,152 2 CHP124_B 110 67 69 204 197 648 1,672 392 733 1,972 1,882 6,651 3 CHP123 76 47 47 138 137 446 1,201 382 715 1,923 1,602 5,823 4 CHP092_C 24 12 17 47 45 146 1,616 341 639 1,718 1,454 5,768 5 CHP124_A 69 59 35 113 128 404 470 156 292 784 648 2,350 6 URB006 11 4 8 21 18 61 709 164 307 826 773 2,779 7 URB003 380 211 248 703 677 2,219 436 244 456 1,227 939 3,302 8 CHP092_A 15 7 10 28 26 86 1,622 189 353 951 1,028 4,144 9 CHP093 928 574 587 1,709 1,677 5,475 459 370 692 1,860 1,392 4,773 10 CHP164 378 236 241 703 687 2,245 741 130 243 653 674 2,441 11 CHP179 1,041 540 693 1,968 1,831 6,073 874 258 482 1,298 1,232 4,145 12 CHP180 751 419 501 1,439 1,345 4,455 323 134 250 672 581 1,959 13 CHP122 562 239 395 1,091 970 3,256 745 500 935 2,516 1,810 6,507 14 CHP116 524 251 360 1,014 917 3,066 334 213 399 1,073 825 2,844 15 CHP081 1,203 469 873 2,397 2,069 7,011 3,868 1,354 2,533 6,814 5,672 20,240 16 CHP044 485 249 327 897 865 2,823 2,081 545 1,020 2,744 2,366 8,756 17 CHP043 1,309 638 907 2,553 2,309 7,717 1,447 944 1,765 4,750 3,511 12,417 18 CHP035_A 2 1 2 4 3 11 759 67 126 339 420 1,711 19 CHP035_B 953 540 623 1,769 1,709 5,595 628 229 429 1,154 1,006 3,445 20 CHP035_C 5 4 3 9 10 31 491 190 355 954 751 2,740 21 CHP031_B 0 0 0 0 0 0 1,221 709 1,325 3,565 2,552 9,372 22 CHP071 1,083 539 743 2,058 1,923 6,346 1,317 931 1,740 4,682 3,377 12,046 23 CHP141 319 148 221 625 554 1,867 601 181 339 913 738 2,771 24 CHP146 1,334 560 959 2,665 2,315 7,833 617 357 669 1,799 1,412 4,854 25 CHP098 561 216 414 1,159 964 3,314 2,476 201 376 1,011 1,271 5,335 26 CHP062 198 104 138 383 359 1,181 166 123 229 617 450 1,585 27 CHP067 944 432 654 1,841 1,637 5,507 116 131 246 661 536 1,690 28 CHP095 926 423 640 1,812 1,602 5,404 1,560 534 998 2,685 2,181 7,957 29 CHP025 832 311 595 1,707 1,385 4,829 476 113 211 569 541 1,910 30 CHP169 359 135 267 733 619 2,113 267 47 88 235 240 877 31 URB040 970 537 640 1,823 1,732 5,702 1,195 657 1,229 3,306 2,484 8,871 32 URB039 924 363 691 1,924 1,606 5,508 773 234 438 1,178 1,112 3,734 33 URB037 1,793 784 1,264 3,595 3,088 10,524 227 208 390 1,048 876 2,749 34 URB001 1,134 524 787 2,191 1,981 6,616 779 249 467 1,255 1,092 3,843 35 URB008 171 74 120 332 295 991 1,012 479 895 2,408 1,777 6,571 36 URB022 407 183 278 788 697 2,353 1,653 162 304 817 942 3,877 37 URB097 1,133 613 758 2,134 2,029 6,668 349 346 646 1,739 1,282 4,362 38 URB021 630 238 462 1,285 1,078 3,694 567 316 591 1,590 1,181 4,245 39 URB020_B 555 224 398 1,118 949 3,244 6,345 1,300 2,431 6,539 6,618 23,233 40 URB010 389 172 271 748 675 2,254 1,072 152 284 764 781 3,053 41 URB030 915 415 648 1,805 1,606 5,389 399 309 578 1,556 1,159 4,001 42 URB075_C 600 285 406 1,144 1,040 3,475 640 578 1,080 2,906 2,019 7,223 43 URB054 572 211 417 1,172 966 3,338 2,043 464 868 2,336 2,294 8,006 44 CHP053_B 20 12 13 37 36 119 459 218 409 1,099 802 2,987 45 CHP053_A 900 524 568 1,649 1,595 5,235 206 209 391 1,052 804 2,662 46 CHP020 1,716 910 1,121 3,165 3,021 9,932 82 204 381 1,026 820 2,514 47 URB056 223 126 154 425 411 1,338 745 67 125 335 409 1,681 48 URB052 934 374 673 1,787 1,629 5,397 439 132 247 665 597 2,080 49 URB058 509 231 382 1,042 923 3,087 463 83 155 417 424 1,542 50 URB057 0 0 0 0 0 0 252 14 27 72 105 470 51 CHP019 746 239 507 1,378 1,199 4,067 994 425 795 2,138 1,639 5,990 52 CHP052_A 533 222 369 990 918 3,032 643 466 871 2,344 1,689 6,014 53 CHP052_B 190 117 123 356 347 1,134 79 67 125 337 254 862 54 CHP086_A 1,304 551 942 2,649 2,261 7,707 723 333 623 1,677 1,334 4,691 55 CHP051 2,311 949 1,639 4,736 3,909 13,544 1,477 364 680 1,831 1,722 6,075 56 CHP018 866 411 595 1,866 1,454 5,192 3,317 779 1,456 3,917 3,350 12,819 57 URB060 499 293 314 890 892 2,888 11,365 927 1,734 4,665 5,714 24,406 58 CHP049 0 0 0 0 0 0 131 12 22 60 69 294 59 URB064_A 4 1 3 8 7 23 1,322 82 152 410 575 2,540 60 CHP086_B 0 0 0 0 0 0 569 71 133 359 393 1,525

47

Trip Production Trip Attraction ID TAZ 2003 HBW HBSch HBSho HBO NHB TOTAL HBW HBSch HBSho HBO NHB TOTAL 61 CHP010_A 256 111 185 492 455 1,499 2,012 183 343 922 1,090 4,549 62 CHP031_A 18 7 13 36 31 105 2,706 272 509 1,370 1,580 6,437 63 CHP065 0 0 0 0 0 0 197 67 126 339 273 1,002 64 CHP026_A 831 381 569 1,586 1,439 4,805 1,493 846 1,583 4,259 3,111 11,292 65 CHP026_B 106 36 78 221 176 616 2,294 2,292 4,286 11,531 7,676 28,079 66 CHP026_C 56 19 43 123 95 336 2,596 185 346 931 1,233 5,292 67 CHP068 2,335 929 1,676 4,651 4,000 13,591 500 261 488 1,314 1,149 3,713 68 CHP036 1,014 334 743 2,089 1,678 5,858 47 85 159 427 354 1,072 69 CHP072 1,744 588 1,283 3,557 2,919 10,091 172 159 298 802 678 2,110 70 CHP144 1,202 455 863 2,392 2,037 6,948 409 159 298 801 697 2,363 71 CHP038_A 648 210 504 1,380 1,113 3,856 108 70 132 354 307 971 72 CHP038_B 825 326 614 1,691 1,438 4,894 171 104 195 524 459 1,453 73 CHP074 618 223 458 1,266 1,054 3,619 377 173 324 872 710 2,456 74 CHP110 455 170 335 931 778 2,670 137 72 134 362 300 1,005 75 CHP076 865 240 654 1,837 1,409 5,005 364 117 219 588 549 1,837 76 CHP077 1,640 580 1,210 3,378 2,769 9,578 212 177 332 893 766 2,380 77 CHP041 1,619 498 1,213 3,404 2,676 9,409 163 152 284 765 640 2,004 78 CHP028 543 197 399 1,121 917 3,176 27 53 99 265 217 662 79 CHP063 1,183 448 868 2,403 2,026 6,928 159 117 218 586 504 1,583 80 CHP066 667 210 489 1,382 1,093 3,842 281 132 247 665 566 1,891 81 CHP139 476 196 341 931 826 2,771 317 65 122 329 322 1,157 82 CHP137 772 304 564 1,558 1,332 4,530 276 103 193 518 460 1,550 83 CHP136 510 240 359 1,024 894 3,028 75 68 126 340 281 889 84 CHP140 556 222 404 1,105 962 3,249 441 89 166 448 431 1,575 85 CHP168 407 164 296 806 708 2,382 296 56 105 283 284 1,025 86 CHP143 821 371 587 1,641 1,442 4,862 79 95 178 479 394 1,225 87 CHP147 696 264 519 1,425 1,206 4,110 918 147 274 737 754 2,829 88 CHP148 676 247 500 1,392 1,152 3,968 21 62 116 312 257 768 89 CHP114 510 198 378 1,044 884 3,016 311 115 215 578 497 1,716 90 CHP078 740 298 538 1,499 1,277 4,352 15 69 129 348 284 846 91 CHP079 722 255 553 1,525 1,245 4,299 27 67 126 338 279 838 92 CHP042 783 270 589 1,650 1,326 4,618 427 143 268 721 671 2,230 93 CHP134 566 218 403 1,132 956 3,276 505 84 158 425 439 1,611 94 CHP135 728 366 495 1,414 1,278 4,281 56 81 152 409 343 1,042 95 CHP058 183 62 132 370 302 1,050 916 92 172 463 544 2,187 96 CHP117 1,384 584 981 2,724 2,389 8,062 180 141 263 708 604 1,895 97 CHP010_B 959 351 698 1,934 1,625 5,568 23 86 161 433 354 1,056 98 CHP022 371 128 274 779 618 2,169 113 89 167 450 343 1,163 99 CHP021 488 185 351 1,013 816 2,854 499 89 166 446 445 1,643 100 URB045_C 273 101 202 574 463 1,613 43 30 55 149 129 405 101 URB045_B 500 151 369 1,015 823 2,857 1,069 185 347 933 965 3,499 102 URB053 493 197 359 986 855 2,889 377 123 230 620 539 1,890 103 URB045_A 384 156 279 760 669 2,249 1,009 359 672 1,807 1,458 5,305 104 URB020_A 196 54 150 446 313 1,160 12 17 31 84 71 216 105 URB036 1,156 436 851 2,367 1,978 6,787 78 110 207 556 465 1,415 106 URB013 254 130 169 483 445 1,480 445 56 104 280 306 1,190 107 URB065 1,220 433 877 2,410 2,047 6,986 107 108 202 544 459 1,420 108 URB069 801 270 598 1,637 1,356 4,660 29 72 135 362 299 896 109 URB064_B 247 122 169 471 436 1,445 322 87 162 437 422 1,429 110 URB090 1,144 411 833 2,304 1,933 6,626 226 142 265 714 622 1,969 111 URB091 853 423 595 1,654 1,522 5,047 316 168 313 843 713 2,354 112 URB086 547 203 392 1,076 925 3,143 59 82 154 413 317 1,025 113 URB023 719 252 544 1,505 1,230 4,251 160 103 193 519 440 1,415 114 URB083 85 28 64 180 142 499 1,413 91 171 459 634 2,768 115 URB082 1,117 422 808 2,254 1,895 6,496 404 168 314 844 718 2,448 116 URB012 1,920 853 1,364 3,730 3,375 11,243 620 231 432 1,162 1,045 3,491 117 URB028 2,389 961 1,710 4,792 4,082 13,933 253 294 549 1,477 1,188 3,761 118 URB074 1,381 684 944 2,614 2,447 8,071 119 159 297 799 667 2,040 119 URB073 1,132 423 846 2,327 1,955 6,683 127 111 208 559 477 1,481 120 URB075_A 59 17 43 118 95 331 113 85 159 429 300 1,086 121 URB078 544 175 403 1,125 904 3,152 9 45 85 228 186 554 122 NWF005_A 124 42 95 264 211 736 239 33 61 165 175 674 123 CHP005 13 5 10 31 21 80 0 1 2 6 4 13

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Trip Production Trip Attraction ID TAZ 2003 HBW HBSch HBSho HBO NHB TOTAL HBW HBSch HBSho HBO NHB TOTAL 124 CHP008 334 96 255 704 554 1,943 59 37 70 188 162 517 125 SWAIR1_C 35 11 27 71 59 203 20 4 8 22 22 76 126 SWAIR1_B 36 12 28 76 64 216 261 23 44 117 139 584 127 SWAIR1_A 1,547 618 1,132 3,118 2,682 9,097 1,108 920 1,720 4,629 3,299 11,676 128 URB064_C 134 45 102 283 228 792 18 14 26 71 61 190 129 NEF005_A 89 26 67 189 147 518 146 51 95 255 213 759 130 URB046 617 241 446 1,255 1,051 3,610 2,022 1,258 2,353 6,329 4,496 16,457 131 NEF005_B 44 17 33 91 77 263 814 95 177 476 512 2,074 132 NEF005_C 164 55 125 342 279 965 1,183 92 171 461 595 2,502 133 NEF005_D 19 8 14 38 33 112 0 2 3 9 7 21 134 CHP003 118 40 88 241 199 685 131 38 72 194 168 603 135 CHP009 244 92 173 475 412 1,396 0 21 39 105 85 250 136 CHP002 27 7 20 54 44 153 1,413 152 285 766 890 3,506 137 CHP006 475 122 365 1,059 761 2,782 127 59 110 296 267 859 138 CHP007 8 3 5 15 13 44 3 1 2 6 6 18 139 CHP004 536 159 410 1,138 893 3,135 223 64 120 324 303 1,034 140 CHP026_D 2 1 2 6 3 14 1,418 1,282 2,398 6,452 4,350 15,901 141 CHP026_E 0 0 0 0 0 0 1,294 1,306 2,442 6,569 4,363 15,974 142 URB100 74 24 56 155 124 433 11 7 13 35 30 96 143 URB101 75 26 55 153 126 436 37 44 82 221 151 534 144 URB102 16 9 11 30 30 96 11 3 5 14 13 46 145 URB103 0 0 0 0 0 0 0 0 0 0 0 0 146 URB104 17 6 11 31 28 93 3 2 3 8 7 23 147 URB105 33 10 26 73 56 198 0 3 5 13 11 32 Internal total 87,502 36,476 62,404 174,453 150,650 511,484 108,236 35,975 67,278 180,996 150,650 543,134 148 Staley & Monticello 693 35 146 324 90 1,288 209 47 32 172 90 550 149 Rising & Windsor 300 15 63 141 39 558 91 20 14 74 39 238 150 Rising & Kirby 300 15 63 141 39 558 91 20 14 74 39 238 151 Rising & Springfield 2,009 102 424 941 260 3,736 607 136 94 498 260 1,594 152 Rising & Bradley 416 21 88 195 54 773 126 28 19 103 54 330 153 Rising & Cardinal 416 21 88 195 54 773 126 28 19 103 54 330 154 Rising & Bloomington 2,910 147 614 1,362 376 5,410 879 197 136 721 376 2,309 155 Mattis & Olympian 2,864 145 604 1,341 370 5,324 865 193 134 710 370 2,272 156 Prospect & Olympian 2,494 126 526 1,168 322 4,637 753 168 117 618 322 1,979 157 Market & Olympian 2,356 119 497 1,103 305 4,380 711 159 110 584 305 1,869 158 Cunningham & Olympian 5,451 276 1,150 2,552 705 10,134 1,646 368 256 1,351 705 4,325 159 High Cross & Ford Harris 44 2 9 21 6 82 13 3 2 11 6 35 160 Cottonwood & Airport 46 2 10 22 6 86 14 3 2 11 6 37 161 Cottonwood & University 2,679 136 565 1,254 346 4,981 809 181 126 664 346 2,126 162 Cottonwood & Windsor 970 49 205 454 125 1,803 293 66 45 240 125 770 163 High Cross & Curtis 577 29 122 270 75 1,073 174 39 27 143 75 458 164 Philo & Curtis 254 13 54 119 33 472 77 17 12 63 33 202 165 First & Old church 416 21 88 195 54 773 126 28 19 103 54 330 166 Neil & Monticello 3,926 199 828 1,838 508 7,300 1,185 265 184 973 508 3,115 167 Duncan & Monticello 577 29 122 270 75 1,073 174 39 27 143 75 458 External total 29,700 1,505 6,267 13,904 3,840 55,216 8,966 2,006 1,393 7,361 3,840 23,566 TOTAL 117,202 37,981 68,670 188,357 154,489 566,700 117,202 37,981 68,670 188,357 154,489 566,700

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