Mxd Trip Generation Model

8/11/2019 Mxd Trip Generation Model

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MIXED USE TRIP GENERATION MODEL v 4.0

MODEL UPDATES

As is the case with all scientific and engineering methods, this MXD tool will continueIt is the user's responsibility to verify that the version in use is suitably up to date for

For updates to the MXD tool spreadsheet, including versions that account for tr

USAGE STATEMENT AND DISCLAIMER

The MXD spreadsheet tool is a functional implementation of the research and mathematical equaitons

as a public service, for use by professional transportation planners and traffic engineers, experienced in

We make no representation or warranty concerning the tool's use by inexperienced individuals, nor co

no responsibility for the conclusions or opinions inexperienced users may draw from the results produc

While the research underlying the spreadsheet has been reviewed for general usefulness, it is the respIt is also the user's responsibility to exercise professional judgment on appropriateness to the specific d

with respect to local data and to test the method's sensitivities to the particular combination of factors u

In cases that vary significantly from those used to develop and validate the method (as described in the

as to the method's relevance and performance.

Although the method has been validated with respect to its ability to predict daily traffic generation for a

1. The accuracies of the model's predictions of travel by transit, walking, and bicycle modes have not b

2. The accuracy of prediction of proportions of daily travel occurring during specific times of day has not

3. The method was developed primarily to address the effects of mixed-use development and, though it

to transit-oriented developments (particularly adjacent to premium bus or rail service) and to developme

4. The method does not account for the effects of changing the spatial separation among uses within th

5. The spreadsheet has not been tested for all possible project descriptions, and the user assumes res

results expected based on the documented equations and against the professional judgment of an exp

To ensure fully-informed use of the results produced by this method, the user is advised to present the

and Trip Generation Handbook) and to explain the professional judgment that leads to a conclusion tha

As is the case with all scientific and engineering methods, MXD will continue to undergo enhancement

the version in use is suitably up to date for his/her purposes. For updates to the MXD spreadsheet, i

1. "Traffic Generation by Mixed-Use Developments - A Six-Region Study Using Consistent Built Environ

2. Ibid.

INSTRUCTIONS

This spreadsheet allows one to input data from a project site and estimate vehicle trip reduction
http://www.fehrandpeers.com/


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by determining:

1. The percent of trips internally captured

2. The percent of external trips which are made by walking

3. The percent of external trips which are made by transit

All user inputs are on the "Input" tab and the results are on the "Results" tab

The spreadsheet uses regression model cofficients to calculate trip reduction percentages by trip purpo

The results are combined to produce "adjusted" external vehicle trips.

Most Input cells are shaded this color of yellow. All other cells are protected and should not be change

Always check your results for reasonability and compare them to sites of similar nature with actual coun

Off-site variables

The spreadsheet takes some off-site variables into account. So the results may be different for differen

could change. Please keep this in mind if doing an analysis that involves "existing plus project" and "cu

AM and PM peak hour modelsThe AM and PM peak hour results are not based on a validated peak hour model. The site trip reductio

the "predicted probabilities" (internal capture, walk, and transit) are the same in the peak hours as for d

The overall trip reduction percentages will differ in the peak hours only to the extent that the trip purpos

use NCHRP factors to account for this or to input trip purpose splits manually.

Site-Specific Internalization

In some cases one may wish to manually define site specific internalization due to unique situations. Th

or contain schools that mostly serve local residents. An experienced traffic engineer or planner will nee

Project Site Size Limitations

Please be aware that the site ought to fall within the range of the data used to develop the model, name

1. The site should be between 5 and 2000 acres

2. There should be less than 5000 dwelling units and less than 3 million square feet of com

If the site does not meet the above criteria, please use an alternate method, as described in the ITE Ha

Employment within a 30 minute transit trip input variable

Note: the 30 minutes is door-to-door, so should include estimations for home-to-transit and transit-to-w

as well as average waiting time for the transit vehicle.

If local data is unavailable:

1. Estimate the geographic area accessible by a 30-minute transit trip.

2. Compare that geographic area to the Census' Longitudinal Employer-Household Dynami

The Census LEHD program's "On the Map" allows users draw a geographic area within whi

calculate employment. See http://onthemap.ces.census.gov/


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to undergo enhancement and updates in the future, and the current version may becis/her purposes.

ansit and peak hour validation please visit: www.coolconnecti

or the MXD method described in the accompanying documentation [1]. Fehr & Peers offers the spread

the use of the Institute of Transportation Engineers Trip Generation report and Trip Generation Handb

cerning the tool's functionality or accuracy beyond the scope of the underlying research. We also bear

d.

nsibility of the user to assess whether the research is relevant to and credible for his/her intended applietails of their subject case. In cases where this is in doubt, the user is advised to either apply alternate

der study.

accompanying documentation) [2], the user is advised to consult with an expert in the transportation pla

variety of mixed-use development projects, the following qualifiers apply:

en mathematically validated, and the model does not predict the amount of automobile travel occurring

been fully validated.

does account for some effects of transit availability and regional accessibility, special care should be u

nt within the regional core (downtown).

e development site, nor with changing the mix of specific types of retail and services uses such as ente

onsibility for checking and judging the reasonableness of the spreadsheet results for the specific case

rt in the transportation planning or engineering.

alongside the results produced by the conventional methods (such as those in the Institute of Transpo

t the MXD results as reasonable. Ideally, traffic counts at sites comparable to the proposed project sho

nd updates in the future, and the current version may become out-of-date or superseded. It is the user'

cluding versions that account for transit and peak hour validation please visit:

ment Measures", Ewing et al.,ASCE Journal of Urban Planning and Development, September 2011.
http://www.coolconnections.org/http://www.fehrandpeers.com/http://www.coolconnections.org/


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se. ITE Trip Generation and NCHRP 365 factors are used to calculate "Baseline" project site trips by pu

.

ts available

t planning years, because the surrounding area

mulative plus project" scenarios.

n data was only captured on a daily basis, and thus

ily for a given trip purpose.

distribution differs. The user is given the option to

ese include project sites that are isolated from surrounding communities

to be consulted to determine the appropriate assumptions and calculations.

ly:

ercial use

ndbook write-up

rk travel times,

s data.

h the map will then


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me out-of-date or superseded.

ns.org

heet

ook.

cation.ethods or to validate the MXD method

nning/engineering field

entirely within the MXD site.

ed when applying the method

tainment, restaurant, and hotel.

nder study both against the

rtaiton Engineers Trip Generation report

ld be performed.

s responsibility to verify that

www.coolconnections.org
http://www.coolconnections.org/http://www.coolconnections.org/


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rpose.


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Acronym Definition

ACS American Community Survey

ASCE American Society of Civil Engineers

DU dwelling unit

HBO home-based other trips

HBW home-based work trips

HH household

ITE Institute of Transportation Engineers

ksf thousand square feet

MXD mixed use development

MXD tool EPA's Mixed-Use Development Trip Generation Tool

NCHRP National Cooperative Highway Research Program

NHB non-home-based trips

ROW right-of-way

TOD transit-oriented development

VMT vehicle-miles traveled


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MIXED USE TRIP GENERATION MODEL V4 - INPUT

All shaded cells are inputsProject / Scenario Specific Inputs

Default National Factors - Can be changed for project based on site specific data, or regional values fro

Section 1 - General Site Information

Site Name Example Project

Geographic Notes / Instructions

Developed Area (in acres) 0 Include streets, ROW, parking lots, poc

Number of Intersections Count intersections either within or on th

Is Transit (bus or rail) present within the site or across the

street? Yes Note: This is only used as a way to zero

Land Use - Surrounding Area

Is the site in a Central Business District or TOD? Yes

Employment within one mile of the MXD 0 Do not include employment within the M

Employment within a 30 minute Transit Trip (Door-to-door) 0 Include employment within the MXD itse

This can be a difficult number to get - so

Site Demographics

Enter Population Directly? If "No", will apply average HH size factor

Population You do not need to enter population her

Average Vehicles Owned per Dwelling Unit 1.85

Conversion Factors

Source:

Average Household Size

Single Family 3.2

Multi-Family 2.5

High Rise Condo 2.5

Jobs per ksf

Retail 2.0 ITE Trip Gener

Office 3.0 ITE Trip Gener

Light Industrial 1.0 ITE Trip Gener

Manufacturing 0.5 ITE Trip Gener

Warehousing 2.0 ITE Trip Gener

Misc. Uses 2.0 ITE Trip Gener

Jobs from ITE rates per other unit

Answering "Yes" will reduce the HBO anstores (large vs. small) should be the pri

Section 2 - Variable Modeling Parameters

The U.S. Census American Community

right, and search "Community Facts" for

is within the housing statistics of the AC


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Source

Jobs per Hotel Room 0.50 ITE Trip Gener

Jobs per Movie Screen 4.00 ITE Trip Gener

Grade School Jobs per student 0.10 ITE Trip Gener

High School / Middle School Jobs per Student 0.10 ITE Trip Gener

College Jobs per student 0.25 ITE Trip Gener

Trip Purpose Splits by Land Use Type

This will affect the final results significantly. Keep "Use NCHRP" on "Yes" unless you have reliable split

For each land use type, choose whether to use NCHRP 365 splits as outlined on the Mode Parameters tab.

If "Yes" is chosen, the percentages will not affect the results. If "No," then enter the splits.

NOTE: For residences, the NHB Attractions are automatically calculated as the remainder to ensure the total is 1

NOTE: For all other purposes, the NHB attractions are automatically set equal to the NHB productions, and the H

total is 100%

NOTE: There is no NCHRP split defined for schools, so the split has to be entered below.

DAILY Use NCHRP? HBW HBO

Residences Yes 15% 50%

Retail Yes 0% 0%

Office Yes 0% 0%

Other non-residential (excluding schools) Yes 0% 0%

Schools No 0% 0%

AM PEAK HOUR


Retail Yes 0% 0%

Office Yes 0% 0%


Schools No 0% 0%

PM PEAK HOUR


Retail Yes 0% 0%

Office Yes 0% 0%


Schools No 0% 0%

NON-HOME BASED TRIPS GENERATED BY PROJECT HOUSEHOLDS

Enter the percent of these that occur Source for this information:

Completely Within the Project Site 25%With one trip end external to the Project Site 15%

Completely outside the Project Site 60% Calculated from other two percentages

SITE-SPECIFIC INTERNALIZATION

This should only be used in unique situations such as if the project is isolated from surrounding communities or c

This section of input is for when you have specific trips you want to EXCLUDE from the MXD process. These tri

Productions


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from the "baseline" trips before applying the model. The overall trip reduction percentage will still take these trips

if you were just letting the model work on all the "baseline" trips. An experienced transportation engineer or plann

assumptions and calculations.

Section 3 - Land Use Inputs

Quantity Units Daily

Number of Dwelling Units

Single Family 0 DU Log Equation

Multi-Family 0 DU Linear Equatio

High Rise Condo 0 DU Linear Equatio

General Retail other than those listed below 0 ksf Log Equation

Supermarket 0 ksf Average Rate

Bank 0 ksf Average Rate

Health Club 0 ksf Average Rate

Restaurant (non-fast food) 0 ksf Average Rate

Fast-Food Restaurant 0 ksf Average Rate

Gas Station 0 ksf Average Rate

Auto Repair 0 ksf Average Rate

Office

Non-Medical 0 jobs Log Equation

Medical 0 jobs Average Rate

IndustrialLight Industrial 0 jobs Average Rate

Manufacturing 0 ksf Average Rate

Warehousing / Self-Storage 0 ksf Average Rate

Hotel (including restaurant, facilities, etc) 0 Rooms Average Rate

Motel 0 Rooms Average Rate

Movie Theater 0 Screens Average Rate

School

University 0 Students Average Rate

High School 0 Students Average Rate

Middle School 0 Students Average Rate

Elementary 0 Students Average Rate

Daily

AM Peak

Hour

PM Peak

Hour

Trips from Land uses not covered above ==> 0 0 0

Jobs in those Land Uses 0

Daily

AM Peak

Hour

PM Peak

Hour

Retail (note: if you use job units for retail, the spreadsheet will convert

before applying trip rates, using the rate in section 2 which you can change)

Trip Equation


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Total "Baseline" ITE Trips 0 0 0

Section 4 - VMT InputsHBW HBO NHB

Average Trip Length in the Region 0 0 0Average Trip Length in the Traffic Analysis Zone 0 0 0


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census data, travel demand model, etc

et parks. Do not include open space, vacant lots.

e perimeter of the MXD. Do not count most unsignalized driveways or alleys, but DO count major entrances to

out the probability of external trips if no transit is present.

D itself

lf

me suggestions are in the instructions tab in "Instructions."

s (in section 2) to dwelling units below

. It will be calculated based on dwelling units below and average HH sizes in section 2.

What does this input affect?

tion Manual

tion Manual

tion Manual

tion Manual

tion Manual

tion Manual

d NHB purpose splits for retail use to those found in smaller stores. The nature of themary factor in the selection here.

Survey is likely a good source. Go to the link at

your community. The vehicles per household data

. http://factfinder2.census.gov/faces/nav/jsf/pages/index.xht

Directly affects trip internalization and mode

splits. Also used to compute site population if

population isn't entered directly.

Used to compute site employment for any land

uses which are entered in ksf rather than jobs.

For retail, if land uses are entered in jobs, it's

used to convert back to ksf for trip generation

calculations.
http://factfinder2.census.gov/faces/nav/jsf/pages/index.xhtmlhttp://www.fehrandpeers.com/http://factfinder2.census.gov/faces/nav/jsf/pages/index.xhtml


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tion Manual

tion Manual

tion Manual

tion Manual

tion Manual

which have been QA/QCd

00%

BO attractions are automatically calculated as the remainder to ensure the

NHB HBW HBO NHB Source (if not using NCHRP):

10% 7% 8% 10%

15% 10% 60% 15%

15% 35% 35% 15%

10% 60% 20% 10%

2.5% 35% 60% 3%

10% 7% 8% 10%

15% 10% 60% 15%

15% 35% 35% 15%

10% 60% 20% 10%

2.5% 35% 60% 3%

10% 7% 8% 10%

15% 10% 60% 15%

15% 35% 35% 15%

10% 60% 20% 10%

2.5% 35% 60% 3%

ontains a school that primarily serves local residents

s will be counted as internal, and subtracted

Attractions

This only affects VMT

calculations

Used to compute site employment for these

land uses which are typically expressed in other

units


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into account, and thus be a higher reduction than

er should be consulted to determine the appropriate

Trips ITE Daily Parameters

AM Peak Hour

PM Peak

Hour Daily

AM Peak

Hour

PM Peak

Hour Code

Average

Rate

Linear

Multiplier

Linear Equatio Log Equation 0 0 0 210 9.57

Linear Equatio Linear Equati 0 0 0 220 6.65 6.06

Linear Equatio Linear Equati 0 0 0 232 4.18 3.77

Log Equation Log Equation 0 0 0 820 42.94

Average Rate Average Rate 0 0 0 850 102.24 66.95

Average Rate Average Rate 0 0 0 912 148.15






Log Equation Linear Equati 0 0 0 710 3.32












Note the

formulas

are

slightly

different in

this

section


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Source:

region's Metropolitan Planning Organization


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hopping areas or residential developments.

l


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AM PEAK HOUR TRIP RATES

Linear

Constant

Log

Multipler

Log

Constant

Average

Rate

Linear

Multiplier

Linear

Constant

Log

Multipler

Log

Constant

0.92 2.71 0.75 0.7 9.74

123.56 0.51 0.49 3.73

223.66 0.34 0.29 28.86

0.65 5.83 1 0.59 2.32

1391.56 3.59

12.35

1.38

11.52

49.35

79.3

2.94

0.84 2.23 0.48 0.86 0.24

0.67 3.76 0.53

30.57 0.44 0.27 70.47

-20.7 0.73 0.83 -29.52

1.01 0.82 0.15

-373.16 0.56 1.24 -2

0.92 2.11 0.45 0.92 -0.46

0

440 0.21 0.21 -69.14

0.81 1.86 0.42

0.54

0.45 1.14 -1.86


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PM PEAK HOUR TRIP RATES Valid Trip

Average

Rate

Linear

Multiplier

Linear

Constant

Log

Multipler

Log

Constant

Jobs Per

Input Unit

(if

Applicable) Daily

1.01 0.9 0.51 Yes

0.62 0.55 17.65 Yes

0.38 0.34 15.47 Yes

3.73 0.67 3.37 2.0 Yes

10.5 0.61 3.95 2.0 Yes

25.82 2.0 Yes

3.53 0.95 1.43 2.0 Yes

11.15 2.0 Yes

33.84 2.0 Yes

97.08 2.0 Yes

3.38 0.94 1.33 2.0 Yes

0.46 0.37 60.08 1.0 Yes

1.06 1.06 -0.32 1.0 Yes

0.42 0.29 58.03 1.0 Yes

0.73 0.78 -15.97 0.5 Yes

0.26 1.02 1.49 2.0 Yes

0.59 0.50 Yes

0.47 0.94 -0.51 0.50 Yes

13.64 4.00 Yes

0.21 0.19 118.58 0.25 Yes

0.13 0.10 Yes

0.16 0.10 Yes

0.15 0.10 Yes


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en Calc Choice?

AM Peak

Hour

PM Peak

Hour

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes


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MIXED USE TRIP GENERATION MODEL V4 - RESULTS

HBW HBO NHB Total HBWBaseline # of External Trips (ITE Model) 0 0 0 0 0% External Trip Reduction

(predicted by MXD Model)

Internal Capture #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0!

Walking External #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0!

Transit External #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0!

# of Trips Reduced (predicted by MXD Model)




MXD Model # of Vehicle Trips #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0!

Results

Baseline Adjusted Reduction %

Daily 0 #DIV/0! #DIV/0!

AM Peak Hour 0 #DIV/0! #DIV/0!

PM Peak Hour 0 #DIV/0! #DIV/0!

HBW HBO NHB Total HBW

Baseline # of External Trips (ITE Model) 0 0 0 0 0% External Trip Reduction

(predicted by MXD Model)




# of Trips Reduced (predicted by MXD Model)

Internal Capture #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0!Walking External #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0!


Adjusted # (MXD Model) of Vehicle Trips

generated by Project Residences #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0!

Results Baseline Adjusted Reduction %

Daily

MODEL APPLICATION - ALL TRIPS

External Vehicle Trips

External Vehicle Trips

Daily

MODEL APPLICATION - TRIP ENDS ASSOCIATEDWITH HOUSES IN THE PROJECT ONLY


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Daily 0 #DIV/0! #DIV/0!

AM Peak Hour 0 #DIV/0! #DIV/0!

PM Peak Hour 0 #DIV/0! #DIV/0!


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HBO NHB Total HBW HBO NHB Total0 0 0 0 0 0 0

#DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0!



#DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! Total Daily




HBW HBO NHB Total

#DIV/0! #DIV/0! #DIV/0! #DIV/0!

#DIV/0! #DIV/0! #DIV/0! #DIV/0!

#DIV/0! #DIV/0! #DIV/0! #DIV/0!

HBO NHB Total HBW HBO NHB Total

0 0 0 0 0 0 0




#DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0!#DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0!



AM Peak Hour PM Peak Hour

PM Peak Hour

Daily

AM Peak Hour

AM Peak Hour

PM Peak Hour

Total Trips Reduced

VMT Redu

VMT Redu

Daily

ITE DailyMXD Daily

MXD Redu

(VMT Red

as a perce


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HBW HBO NHB Total

0 0 0 0#DIV/0! #DIV/0! #DIV/0! #DIV/0!

#DIV/0!

#DIV/0!

HBW HBO NHB Total

#DIV/0! #DIV/0! #DIV/0! #DIV/0!

#DIV/0! #DIV/0! #DIV/0! #DIV/0!

VMT Avoided #DIV/0!

ction from Trip Capture

ction from Shorter Trips

MT Reduced

MT Adjusted VMT

ction in Daily VMT

ction from Trip Capture)

ntage


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Comparison of MXD forecasted daily trips to ITE forecasted daily trips

0

0

0

0

0

1

1

1

1

1

1

Daily AM Peak Hour PM Peak Hour

ITE Trips

MXD Trips

0

0.10.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

ITE Daily VMT MXD Daily Adjusted

VMT

MXD Reduction in

Daily VMT

(VMT Reduction from

Trip Capture)

Mxd Trip Generation Model

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