May 9, 2007

Custom Applications for Calculating Transit Operating Statistics from Travel Demand Forecasting Output:

May 9, 2007

The Denver RTD OpStats 2.0Transit Operating Statistics Model

Herbert HigginbothamConnetics Transportation Group

PLANNING APPLICATIONS 2007

TRB Planning Applications 2007

Background• Pre-2001: RTD’s operating statistics for long-

range planning are calculated by manually entering route-by-route data into a spreadsheet

• 2001: First OpStats model produces bus statistics from MinUTP travel demand model output

• 2004: RTD initiates the FasTracks program, amplifying the need to quickly produce bus and rail statistics for alternatives analysis

• 2006: Model is redesigned as RTD OpStats 2.0; updated to read TransCAD travel demand model output and adding a rail statistics module

Route Headways,

Times & Distances


Typical Alternatives Analysis

TravelDemandModel

Capital andO&M Cost

Models

Systemwide Vehicles,

Hours, and Miles

Period Lengths, Recovery Factors, Annualization Factors, etc.

Operating Assumptions

Manually–Generated

Spreadsheet

Computations

Automation Gap

• Replicating calibrated calculations for several alternatives can take hours and days


The Automation Gap• Repeatable tasks like data preparation and

summation occupy precious time and introduce human error

• Statistics formulas tend to embed assumptions, leaving them less likely to be consistent or updated across routes or alternatives

• Results must be calculated by an experienced user every time, making tasks difficult to share or transfer

• Calibrating or testing various operating parameters is slow and cumbersome

Manually–Generated

Spreadsheet

Computations

Automation Gap

Route Headways,

Times & Distances


Analysis with an Automated Model

TravelDemandModel

Capital andO&M Cost

Models

Systemwide Vehicles,

Hours, and Miles

Period Lengths, Recovery Factors, Annualization Factors, etc.

Operating Assumptions

• Accurate operating statistics produced in seconds allow planners more time for data analysis

No Automation Gap

OperatingStatistics

Model

Benefits of the OpStats 2.0 Model


• Speed– Manual Run: 1-2 hours or longer– OpStats 2.0 Run: 5-8 seconds

• Accuracy– Computations are built-in – no errors from

miscopied formulas or unreferenced worksheets– Facilitates fast and accurate model calibration

across multiple modes and vehicle types

• User-Friendly– Familiar Excel interface and easy-to-use controls

allow even novice users to get results quickly


Benefits of the OpStats 2.0 Model

• Functionality– Quickly vary systemwide operating assumptions– Produces operating statistics with and without

passenger demand equilibration– Stores countless alternative runs and reruns –

simplifies comparison between multiple scenarios

• Adaptability– Small file sizes allow sharing among many users– Open architecture allows advanced users to

modify formulas and structures to meet shifting agency needs


Opening the Model

Application loads in standard Excel

window

Adds button to run model to the standard toolbar

Opens to main Model Assumptions page


Model Input AssumptionsAssumptions are stratified

by service type (local bus, express bus, light rail, etc) and vehicle

type (40’ bus, articulated bus, LRV, etc)

Assigns service hours for peak, offpeak, & early/late periods, and factors for recovery and deadhead

time

Annualization factors by service type

Additional tables allow user to set dwell times, peak hour factors, seats per vehicle, vehicle loading standards, rail

consist max/min, and headway adjustment rules for equilibration

Equilibration switch


Running the Model

The user is prompted to enter a project name for the new

run

Pressing the Run OpStats button

initiates a new model run

A dialog box allows the user to select the travel demand model (TDM) output file that contains

the route data for the run

The TDM output file is created during a post-assignment process in

TransCAD. This DBF file contains the ID, mode, service type, vehicle type,

headways, run times & distances, and passenger volumes for each

route


Running the Model

In less than 10 seconds, the run is completed and the user is prompted to save the results

file


Model Results: Summaries

The user can continue to adjust assumptions and toggle equilibration in the output file to observe the effects of different

parameters

Other worksheets summarize bus

data by time period

Daily and annual bus and rail statistics are reported by service

type and vehicle type in print-ready tables

Some rows have been hidden to show the most pertinent data


Model Results: Bus Routes

Some columns have been hidden to show the most pertinent data

Separate worksheets perform bus calculations for each time period

Built-in custom formulas calculate bus statistics by

route

With bus equilibration on, peak hour volumes are used to equilibrate headways according to

user-defined rules. In certain cases, the vehicle type will be upsized to accommodate

large loads

Data are imported by route and period from the TDM output

file


Model Results: Rail Routes

Built-in custom formulas calculate

train and car statistics by route

Data are imported by route from the TDM output file

With rail equilibration on, peak hour volumes are used to calculate rail cars according to user-defined

rules

Some columns have been hidden to show the most pertinent data


Model Run History

Records key summary statistics for each run to

facilitate alternative comparison

Assigns Run ID and stores run date & time, TDM output filename, and model output

filename so runs can be quickly identified or

recreated


Model Calibration

General procedure:1. Operating assumptions replicating base year conditions are

input into the model2. OpStats 2.0 is executed with travel demand model output

from the base year validation run3. Results are compared to actual service data for the base

year, adjusting period lengths and run time factors as needed

Denver RTD Calibration• Results from a base year 2005 travel demand model run were

processed in OpStats 2.0 and compared to 2005 actual data• Model-generated bus statistics were within 5% of actual

statistics and model-generated rail statistics were within 5% to 10% of actual statistics


Potential Applications• FTA New and Small Starts Process

– Requires detailed and accurate operating statistics and associated cost data

• Alternatives Analysis, MIS, EIS– Run and compare multiple scenarios quickly

• SRTP, LRTP, Operational or Financial Analyses– Generates the statistics needed to quickly cost out

constrained and unconstrained plans

• Transit Agency “What If” Scenario Analysis – Test the effects of potential service changes (e.g.,

increasing service spans, changing load standards, etc)


Potential Add-in Features• Stored assumptions sets

– Allows user to run with one of several pre- and user-defined operating parameter sets stored in the model

• Multi-operator data sets– Useful for regional or large urban studies that cover

multiple agencies and/or operating environments

• Alternatives comparison module– Allows user to select one model run as a baseline and

several others to compare to it

• Cost model integration– Model can be programmed to directly export data to a

separate cost model, or can be designed as part of an all-inclusive operating statistics and cost model


Model Specifications• Platform: MS Excel 2000

– Is also compatible with Excel 98 and Excel 2003

• Language: MS Visual Basic 6.3– Underlying programming language of MS Excel

• System Requirements:– Windows 98, 2000, ME, XP– Minimum 500 MHz processor speed– Minimum 250 MB RAM

• File Sizes:– Program file: 687 KB– Output files: 1.6 MB


AcknowledgementsThe Denver RTD OpStats 2.0 model was developed by Connetics Transportation Group in cooperation with:

•The Denver Regional Transportation District (project conception, funding, review, and management)

– Bill Van Meter– Dave Hollis– Lee Cryer– David Krutsinger

•AECOM (TransCAD code-writing)

– Manish Jain

Our deepest thanks for their guidance and support

May 9, 2007

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