Tour-Based Model for a Small Area

Presented at 11th Transportation Planning Applications ConferenceReno, NVMay 2011

William G. Allen, Jr., PEConsultantWindsor, SC

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The Modern Modeller’s Muddle

Where we are

Where we need to be

Further than Further than you thinkyou think

Trips Tours

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Glynn County, Georgia

Southeast Georgia coast, between Savannah and Jacksonville

County seat: Brunswick 2006: 67,600 people, 36,600 jobs Home to St. Simons Island, Jekyll Island,

Federal Law Enforcement Training Center Bisected by I-95

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Glynn County Location

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Why a New Travel Model?

Georgia DOT already has a travel model -- the official MPO model

County was growing rapidly GDOT not always able to respond quickly County wanted more detail, more focus on

local roads and small areas County wanted to control the process

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Where to Start?

Buy the software (Cube Voyager, the GDOT standard)

Software is a platform, not a model Using a model is easy, creating one requires

specialized expertise County hired a consultant to develop the

model and train staff

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Observed Travel Data

Home interview survey is best– Expensive ($200/household)– Difficult, time-consuming– Add-on to NHTS (next one: 2017)

2000 Census has some data on Work travel GDOT has traffic counts Validation year: 2006 (before gas price spike,

recession)

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Glynn County Approach

Very limited budget and schedule Subdivide the GDOT TAZes and add network

detail GDOT: 397 zones, County: 676 Transfer model from other cities, adjust to

reflect local conditions & counts Copy some information from GDOT model

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Conventional Travel Modelling

“Four step process”: generation, distribution, mode choice, assignment

Travel is zone-to-zone aggregate totals Trips are independent of each other Used for over 50 years

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The New Way

Model every individual trip Measure travel in round-trip tours More realistic representation of travel Faster computers make calculations feasible

– More accuracy and flexibility possible

Favored by academics and researchers– More theoretically correct

Slowly becoming adopted

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What Is a “Tour”?

Origini

Destinationj

Stopk

Trip

(Half)-(Half)-TourTour

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Challenges

Most tour models have been data intensive, costly, and time-consuming

A moving target: research is on-going Typical development: 2 - 3 years, $ millions Often custom-written software (black box) Model run times measured in days New York, Columbus, Sacramento, Atlanta

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Simplified Version

County staff expressed no preference Limited resources

– 6 months, $60K, no survey data– Not a research project, need real results

Not a true activity-based model No transit Doesn’t model personal interactions,

household relationships, or trip sequencing

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Some Things Are the Same

Still must represent the basic choices:– How many trips?– Where?– By what mode?– At what time?– By what route?

Sequence of steps is not much different Most components are familiar

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Some Things Are Different

Travel represented as round-trip tours Model discrete travel by HHs, not zonal

averages Use Monte Carlo simulation to model

individual travel choices Added simple time of day model (4 periods) New intermediate stop model

– How many stops?– Where?

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Model Synthesis

Use Baltimore 2001 NHTS add-on survey Port, manufacturing, tourism, I-95 – it’s

Brunswick on a larger scale Provided many parameters, relationships Adjust for geographic scale Borrowed some parameters from GDOT

model Validated to 2000 JTW & local counts

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Generation

Starts conventionally Purposes: HBW, SCH, HBS, HBO, COM,

TRK, ATW, VIS, 4 I/E’s, 4 E/I’s Prods: look-up table by size & income Attrs: regression by zone Rates from GDOT and Baltimore models Non-motorized share removed Output a record for each RT tour

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Distribution

Allocate productions to zone of tour attraction– HBW, SCH: work or school– Other: where you spent the most time

Discrete destination choice Probabilities calculated by gravity function F’s based on 2000 JTW; non-work by

analogy Process iterated to match attractions

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Intermediate Stops

Each journey is a round-trip tour Main tour purposes: work, school, shop,

other, at-work, visitor Stops are made on the way from home and

on the way back home 30% of tours involve at least 1 stop Stops are for shopping, personal business No Non-Home-Based trip purpose!

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Two Sub-Models

Two multinomial logit models Model 1: How many stops? (separately by

P-A and A-P)– Based on tour purpose, HH size, income, area

types, retail emp, P-A travel time– A-P stops also based on number of P-A stops

Model 2: Where are the stops?– Logit destination choice– Detour time, area type, employment

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Other Models

Time of Day: fixed percents by purpose used to allocate half-tours to 4 time periods

Mode Choice: standard logit auto occupancy model: 1, 2, 3, 4+ per auto

Trip Accumulator: splits RT tours into individual O/D trips by SOV / HOV / TRK and period

Conventional assignment by period, veh type One speed feedback loop

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Uses of New Model

Evaluate growth proposals Support impact fees Long-range plan analysis Provide data to site traffic studies Corridor studies

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So What?

Runs in 1 hour on any Windows computer No black box software; all in Cube Voyager Easy to run; requires few inputs Accuracy was improved (10% RMSE) Incorporated the key features of tour-based

models Proof that new approach can be applied to a

smaller area, on a budget (6 months, $60 K)

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Questions?

Presentation is available at www.williamgallen.com