Lexington Area TransCAD Travel Demand Model July 22, 2003 Kentucky Traffic Model Users Group Meeting Kyeil Kim, Ph.D. Bernardin, Lochmueller & Associates,

Slides:



Advertisements
Similar presentations
1 Update on Bicyclist & Pedestrian Data Collection and Modeling Efforts Transportation Research Board January 2010 Charlie Denney, Associate Michael Jones,
Advertisements

A PERSPECTIVE ON APPLICATION OF A PAIR OF PLANNING AND MICRO SIMULATION MODELS: EXPERIENCE FROM I-405 CORRIDOR STUDY PROGRAM Murli K. Adury Youssef Dehghani.
Speed-Flow & Flow-Delay Models Marwan AL-Azzawi Project Goals To develop mathematical functions to improve traffic assignment To simulate the effects.
THURSTON REGION MULTIMODAL TRAVEL DEMAND FORECASTING MODEL IMPLEMENTATION IN EMME/2 - Presentation at the 15th International EMME/2 Users Group Conference.
1 Innovative Tools October 27, 2011 Chi Mai. 2 Presentation Overview VISSIM Corridors VISSIM Protocol Hours of Congestion.
SE Florida FSUTMS Users Group Meeting FDOT Systems Planning Office
Parsons Brinckerhoff Chicago, Illinois GIS Estimation of Transit Access Parameters for Mode Choice Models GIS in Transit Conference October 16-17, 2013.
Feedback Loops Guy Rousseau Atlanta Regional Commission.
TRAVEL DEMAND FORECASTING FOR THE OLYMPIC GAMES ATHENS 2004 ATTIKO METRO S.A. Anna Anastasaki.
Traffic assignment.
VARIABLE SPEED LIMIT DEPLOYMENT EVALUATION I-270/I-255 Traffic and Safety Conference May 12, 2010 Missouri University of Science and Technology and HDR.
Madison County Travel Demand Model Challenges and Innovations Diane B. Zimmerman, PE.
Simpson County Travel Demand Model July 22, 2003.
Status of the SEMCOG E6 Travel Model SEMCOG TMIP Peer Review Panel Meeting December 12, 2011 presented by Liyang Feng, SEMCOG Thomas Rossi, Cambridge Systematics.
SCAG Region Heavy Duty Truck Model Southern California Region Heavy Duty Truck Model.
Development of a New Commercial Vehicle Travel Model for Triangle Region 14 th TRB Planning Applications Conference, Columbus, Ohio May 7, 2013 Bing Mei.
Implementing the FHWA Quick Response Freight Model in the Twin Cities Steve Wilson and Jonathan Ehrlich SRF Consulting Group, Inc. SRF Consulting Group,
Intercity Person, Passenger Car and Truck Travel Patterns Daily Highway Volumes on State Highways and Interstates Ability to Evaluate Major Changes in.
GEOG 111 & 211A Transportation Planning Traffic Assignment.
Junction Modelling in a Strategic Transport Model Wee Liang Lim Henry Le Land Transport Authority, Singapore.
Session 11: Model Calibration, Validation, and Reasonableness Checks
Sequential Demand Forecasting Models CTC-340. Travel Behavior 1. Decision to travel for a given purpose –People don’t travel without reason 2. The choice.
CE 2710 Transportation Engineering
Agenda Overview Why TransCAD Challenges/tips Initiatives Applications.
Design Speed and Design Traffic Concepts
GEOG 111/211A Transportation Planning Trip Distribution Additional suggested reading: Chapter 5 of Ortuzar & Willumsen, third edition November 2004.
Regional Travel Modeling Unit 6: Aggregate Modeling.
An Experimental Procedure for Mid Block-Based Traffic Assignment on Sub-area with Detailed Road Network Tao Ye M.A.Sc Candidate University of Toronto MCRI.
Milton-Madison Bi-State Travel Demand Model Rob Bostrom Planning Application Conference Houston, Texas May 19, 2009.
Source: NHI course on Travel Demand Forecasting (152054A) Session 10 Traffic (Trip) Assignment Trip Generation Trip Distribution Transit Estimation & Mode.
Travel Demand Modeling At NCTCOG Presentation For IOWA TMIP Peer Review March 30 – April 1, 2004.
Transportation leadership you can trust. presented to presented by Cambridge Systematics, Inc. Development of a Hybrid Freight Model from Truck Travel.
BALTIMORE METROPOLITAN COUNCIL MODEL ENHANCEMENTS FOR THE RED LINE PROJECT AMPO TRAVEL MODEL WORK GROUP March 20, 2006.
Trip Generation Review and Recommendations 1 presented to MTF Model Advancement Committee presented by Ken Kaltenbach The Corradino Group November 9, 2009.
June 15, 2010 For the Missoula Metropolitan Planning Organization Travel Modeling
Investigation of Speed-Flow Relations and Estimation of Volume Delay Functions for Travel Demand Models in Virginia TRB Planning Applications Conference.
Simpson County Travel Demand Model Mobility Analysis November 7, 2003.
Knoxville Regional Travel Demand Model Upgrade Program May 6, 2004 Knoxville Regional Travel Demand Model Upgrade Program May 6, 2004.
NTERFACING THE MORPC REGIONAL MODEL WITH DYNAMIC TRAFFIC SIMULATION INTERFACING THE MORPC REGIONAL MODEL WITH DYNAMIC TRAFFIC SIMULATION David Roden (AECOM)
SAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY San Francisco’s Dynamic Traffic Assignment Model Background SFCTA DTA Model Peer Review Panel Meeting July.
Transportation Planning, Transportation Demand Analysis Land Use-Transportation Interaction Transportation Planning Framework Transportation Demand Analysis.
Major Transportation Corridor Studies Using an EMME/2 Travel Demand Forecasting Model: The Trans-Lake Washington Study Carlos Espindola, Youssef Dehghani.
SAN FRANCISCO COUNTY TRANSPORTATION AUTHORITY San Francisco DTA Model: Working Model Calibration Part 1: Process Greg Erhardt Dan Tischler Neema Nassir.
February 8, 2008 SERPM65 vs. SERPM6-Corradino 1 SERPM-6.5 & SERPM-6: Differences & Future Directions Southeast Florida FSUTMS Users Group Meeting Ft. Lauderdale,
Incorporating Traffic Operations into Demand Forecasting Model Daniel Ghile, Stephen Gardner 22 nd international EMME Users’ Conference, Portland September.
ECIA A Regional Response to Local needs Travel Demand Forecasting Model for DMATS Area Chandra Ravada.
Transportation leadership you can trust. presented to TRB 11 th Conference on Transportation Planning Applications presented by Dan Goldfarb, P.E. Cambridge.
Calibrating Model Speeds, Capacities, and Volume Delay Functions Using Local Data SE Florida FSUTMS Users Group Meeting February 6, 2009 Dean Lawrence.
Transportation Engineering (CIVTREN) notes of AM Fillone, DLSU-Manila
How Does Your Model Measure Up Presented at TRB National Transportation Planning Applications Conference by Phil Shapiro Frank Spielberg VHB May, 2007.
CE 341 Transportation Planning
1 Fine Tuning Mathematical Models for Toll Applications Dr. A. Mekky, P.Eng., A. Tai, M. Khan Ministry of Transportation, Ontario, Canada.
Source: NHI course on Travel Demand Forecasting (152054A) Trip Generation CE 451/551 Grad students … need to discuss “projects” at end of class.
Source: NHI course on Travel Demand Forecasting (152054A) Session 11: Model Calibration, Validation, and Reasonableness Checks.
11th TRB National Transportation Planning Applications Conference CORRADINO May 9, Validation of Speeds and Volumes in a Large Regional Model Southeast.
1 Methods to Assess Land Use and Transportation Balance By Carlos A. Alba May 2007.
11 th National Planning Applications Conference Topic: Statewide Modeling Validation Measures and Issues Authors: Dave Powers, Anne Reyner, Tom Williams,
Hcm 2010: BASIC CONCEPTS praveen edara, ph.d., p.e., PTOE
INCORPORATING INCOME INTO TRAVEL DEMAND MODELING Brent Spence Bridge Case Study October 13, 2015.
Incorporating Time of Day Modeling into FSUTMS – Phase II Time of Day (Peak Spreading) Model Presentation to FDOT SPO 23 March 2011 Heinrich McBean.
CE Urban Transportation Planning and Management Iowa State University Calibration and Adjustment Techniques, Part 1 Source: Calibration and Adjustment.
Travel Demand Forecasting: Trip Generation CE331 Transportation Engineering.
Travel Demand Forecasting: Traffic Assignment CE331 Transportation Engineering.
Transportation Modeling – Opening the Black Box. Agenda 6:00 - 6:05Welcome by Brant Liebmann 6:05 - 6:10 Introductory Context by Mayor Will Toor and Tracy.
Network Attributes Calculator
16th TRB Transportation Planning Application Conference
Transportation Planning Applications Conference Sheldon Harrison
Johnson City MPO Travel Demand Model
Ventura County Traffic Model (VCTM) VCTC Update
Trip Distribution Review and Recommendations
Presentation transcript:

Lexington Area TransCAD Travel Demand Model July 22, 2003 Kentucky Traffic Model Users Group Meeting Kyeil Kim, Ph.D. Bernardin, Lochmueller & Associates, Inc.

Main Features Consists of separate time-of-day (TOD) models Realistic free-flow speed based on a speed survey and HCM-based signal delays Varying capacities by TOD for reversible lanes Model parameters are based on recent travel survey and KYTCs HIS database. 2-stage assignments: Initial and Feedback User-friendly model GUI

Model Area

Roadway Network Incorporation of KYTCs HIS and geometric/operations data All MINUTP network attributes FHWA functional class, posted speeds, etc. Number of lanes, reversible lanes & bike lanes Area type, shoulder widths, median type, etc. Traffic signals & multi-way stops (signal priority, multiple signals) Turn prohibitors

TAZ DB Total 489 zones Internal zones = 445 zones External zones = 44 zones 51 data attributes Date related to population and household Employment by SIC code Student population, group quarters & school enrollment Vehicle ownership Key data for estimating trip productions and attractions

Speed/Capacity Estimation Free-flow speed, peak-hour capacity & daily capacity A special GIS-dk program to estimate directional capacities by TOD & free-flow speed Consideration of changes in reversible lanes by TOD Free-flow speed = f (functional class, posted speed, number of lanes, facility type, delays on interrupted facilities) Daily capacity = f (functional class, number of lanes, facility type) Peak-hour capacity = max. service flow * adjustment factors where, Adjustment factors = f (geometric data, functional class, facility type, area type, delays on interrupted facilities)

Speed/Capacity Estimation (Contd) Delays on interrupted facilities HCM 2000 procedure delay/veh = uniform delay * PF + incremental delay + initial queue delay where, PF = progression factor = f (arrival type, g/C) uniform delay = Varying g/Cs and PFs by signal priority and multiple signals

Lexington Model GUI

Trip Generation Six internal trip purposes: - HBW, HBK12, HBU, HBO, NHBW & NHBO Trip production - Cross-classification technique - Data: The 2000 Knoxville Household Travel Behavior Study, The 1999 Indiana University Travel Demand Survey - Analysis of Variance (ANOVA) and non-parametric correlations techniques to identify the predictor variables for various trip purposes - Stratification curve: distribution of households in a zone over various levels of the predictor variables

Trip Generation (Contd) Trip production model Trip Purpose1 st Predictor2 nd PredictorOverall Trip Rate HBWWorkers/H.H.Vehicles/H.H.1.30 HBK12Students/H.H.None0.64 HBUUniversity Student/TAZ None0.48 HBOHousehold SizeVehicles/H.H.3.72 NHBWWorkers/H.H.Household Income 0.84 NHBOHousehold SizeVehicles/H.H.2.02 Total9.00

Trip Generation (Contd) Trip attraction model: the Atlanta regression model Trip PurposeIndependent VariableParameter HBWTotal Employment1 HBK12K-12 Enrollment1 HBUUniversity Enrollment1 HBO Population.1168 Retail Employment.8257 Commercial & Govt Employment.0408 Other Employment.0137 NHBW & NHBO Population.0575 Retail Employment.7593 Commercial & Govt Employment.0846 Other Employment.1053

Trip Distribution Doubly-constrained Gravity model for the 6 internal trip purposes & E-I trips Friction factors - Initial factors from the old MINUTP model - Fitting to Gamma function for smoothing the factors - Adjustment of Gamma parameters to arrive at correct trip lengths by trip purpose Socioeconomic (or K) factors

Vehicle Occupancy Vehicle occupancy rates by trip purpose HBW 1.09 persons/vehicle HBK persons/vehicle HBU 1.20 persons/vehicle HBO 1.83 persons/vehicle NHBW 1.17 persons/vehicle NHBO 1.75 persons/vehicle (Source: The 2000 Knoxville Household Travel Behavior Study)

Time-of-Day AM peak ( 06:30~09:00 ); Midday peak ( 12:00~13:30 ); PM peak ( 15:30~18:00 ) and Off-peak TOD factors - Split the 24-hr trip table into tables by TOD - by trip purpose Directional factors - Convert trip tables in a production-attraction format to origin- destination tables - by trip purpose and by TOD Data Source: the 2000 Knoxville Household Travel Behavior Study

External Trips 44 external stations E-E trips The 1994 O-D survey by Wilbur Smith Associates Most of E-E trip interchanges except for the interstate and US60 exchanges Kentucky Statewide Travel Model via critical link analysis E-E trip interchanges for the interstate and US60 external stations Modlin Equations A check of reasonableness E-I trips = ADTs - E-E trips at each external station 27 stations of the 44 stations carry through trips

Traffic Assignment Time-of-day user equilibrium assignments - separate AM-peak, Midday-peak, PM-peak & Off-peak assignments Improved free-flow speeds and varying capacities by TOD by reversible lanes Separate volume-delay functions (defaults) Unsignalized facilities = 0.20; = 10.0 Signalized facilities = 0.05; = 10.0 Feedback assignment

Feedback Loop 24-Hour Average Speed Gravity Model TOD Trip Table Factoring AM-peak Assignment Midday-peak Assignment PM-peak Assignment Off-peak Assignment 24-Hour Weighted Average Congested Link Speed

CAL_REP Assignment post-processor written in GIS-dk and incorporated in the GUI Various error statistics by functional classification, volume group, screenline, cutline and specific corridors Error statistics total counts, average counts, counts standard deviation total loadings, average loadings, loadings standard deviation % root mean square error mean error, % error total counts VMT, total loadings VMT, % VMT error

Assignment Results

CAL_REP Report Loading % error = -1 % Loading VMT error = 0.9% % RMSE = 25% Interstate = 0.03% (% error); -2.6% (VMT error) Urban Principal Arterial = -1.3%; -3.1% Urban Minor Arterial = -3.8%; 3.7%

In Progress Model runs for future years and post-processing 2030 with committed projects only 2010 with committed plus Plan projects scheduled for completion by with committed plus Plan projects scheduled for completion by with all projects in the current LRP Multinet feature in GUI for efficient network data handling

THANK YOU!