5 th Bi-Annual Border to Border Conference Development of an Origin-Destination Matrix for the Paso Del Norte Region (Regional Master Network Phase IV)

Slides:

Advertisements

Similar presentations

THURSTON REGION MULTIMODAL TRAVEL DEMAND FORECASTING MODEL IMPLEMENTATION IN EMME/2 - Presentation at the 15th International EMME/2 Users Group Conference.

Advertisements

International Telecommunication Union No 1 The Executive Round Tables High-level perspectives and strategies regarding the present and future use of ICT.

GIS and Transportation Planning

NCHRP Renaissance Planning Group Rich Kuzmyak Chris Sinclair Alex Bell TRB National Transportation Planning Applications Conference May 6, 2013 Columbus,

Simpson County Travel Demand Model July 22, 2003.

What is the Model??? A Primer on Transportation Demand Forecasting Models Shawn Turner Theo Petritsch Keith Lovan Lisa Aultman-Hall.

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.

Economic Costs of Critical Infrastructure Failure in El Paso-Juarez Region Border to Border Transportation Conference November 20, 2014 Jeff Shelton, Sharada.

Subarea Model Development – Integration of Travel Demand across Geographical, Temporal and Modeling Frameworks Naveen Juvva AECOM.

CE 2710 Transportation Engineering

Agenda Overview Why TransCAD Challenges/tips Initiatives Applications.

The Paso del Norte Watershed Council Promoting ecosystem health and economic sustainability in the Paso del Norte Watershed.

GEOG 111/211A Transportation Planning UTPS (Review from last time) Urban Transportation Planning System –Also known as the Four - Step Process –A methodology.

Major Water Research & Outreach Programs New Mexico State University.

Luci2 Urban Simulation Model John R. Ottensmann Center for Urban Policy and the Environment Indiana University-Purdue University Indianapolis.

Planning Process ► Early Transport Planning  Engineering-oriented  1944, First “ O-D ” study  Computational advances helped launch new era in planning.

Opportunities & Challenges Using Passively Collected Data In Travel Demand Modeling 15 th TRB Transportation Planning Applications Conference Atlantic.

Interfacing Regional Model with Statewide Model to Improve Regional Commercial Vehicle Travel Forecasting Bing Mei, P.E. Joe Huegy, AICP Institute for.

New Mexico Texas Water Commission Update for Good Neighbor Environmental Board June Bobby Creel & John Burkstaller New Mexico Water Resources Institute.

Framework for Model Development General Model Design Highway Network/Traffic Analysis Zones (TAZs) Development of Synthetic Trip Tables Development of.

GIS Techniques and Algorithms to Automate the Processing of GPS- Derived Travel Survey Data Praprut Songchitruksa, Ph.D., P.E. Mark Ojah Texas A&M Transportation.

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.

Presented to presented by Cambridge Systematics, Inc. Transportation leadership you can trust. An Integrated Travel Demand, Mesoscopic and Microscopic.

Measuring Transit-Coverage Level- Of-Service in U.S. Border Cities Luis David Galicia, Ph.D. Texas A&M Transportation Institute

Validate - A Nationwide Dynamic Travel Demand Model for Germany Peter Vortisch, Volker Waßmuth, PTV AG, Germany.

May 7, 2013 Yagnesh Jarmarwala Phani Jammalamadaka Michael Copeland Maneesh Mahlawat 14 th TRB National Transportation Planning Applications Conference.

Act Now: An Incremental Implementation of an Activity-Based Model System in Puget Sound Presented to: 12th TRB National Transportation Planning Applications.

Computers in Urban Planning Computational aids – implementation of mathematical models, statistical analyses Data handling & intelligent maps – GIS (Geographic.

Travel Demand Forecasting: Trip Distribution CE331 Transportation Engineering.

Big Data “Triage” for Long Range Planning Transportation Engineering and Safety Conference Reuben S MacMartin December 12, 2014.

Transportation Planning, Transportation Demand Analysis Land Use-Transportation Interaction Transportation Planning Framework Transportation Demand Analysis.

David B. Roden, Senior Consulting Manager Analysis of Transportation Projects in Northern Virginia TRB Transportation Planning Applications Conference.

Overview Freight Modeling Overview Tianjia Tang, PE., Ph.D FHWA, Office of Freight Management and Operations Phone:

Borderplex Gridlock Jaime Muniz, Arien Hardin, Michael Maillet.

Getting to Know Cube.

Paul Metaxatos Urban Transportation Center University of Illinois at Chicago CTS-IGERT – Weekly Seminar May 14, 2009 Some Issues in Transportation Demand.

Integrated Travel Demand Model Challenges and Successes Tim Padgett, P.E., Kimley-Horn Scott Thomson, P.E., KYTC Saleem Salameh, Ph.D., P.E., KYOVA IPC.

Effectiveness of Wastewater Treatment Plants in Reducing Pathogens in the Paso del Norte Region Geoffrey B. Smith New Mexico State University, Las Cruces,

Exploring Cube Base and Cube Voyager. Exploring Cube Base and Cube Voyager Use Cube Base and Cube Voyager to develop data, run scenarios, and examine.

KIT – University of the State of Baden-Wuerttemberg and National Laboratory of the Helmholtz Association INSTITUTE FOR ECONOMIC POLICY RESEARCH (IWW),

4 th Bi-Annual Border to Border Transportation Conference South Padre Island, Texas November 13-15, 2012 US-Mexico Cross-Border Freight Traffic Trends.

FDOT Transit Office Modeling Initiatives The Transit Office has undertaken a number of initiatives in collaboration with the Systems Planning Office and.

Enhancement and Validation of a Managed-Lane Subarea Network Tolling Forecast Model May 19, 2005 Stephen Tuttle (RSG), Jeff Frkonja (Portland Metro), Jack.

Modeling and Forecasting Household and Person Level Control Input Data for Advance Travel Demand Modeling Presentation at 14 th TRB Planning Applications.

How Does Your Model Measure Up Presented at TRB National Transportation Planning Applications Conference by Phil Shapiro Frank Spielberg VHB May, 2007.

an Iowa State University center SIMPCO Traffic Modeling Workshop Presented by: Iowa Department of Transportation and Center for Transportation Research.

A Tour-Based Urban Freight Transportation Model Based on Entropy Maximization Qian Wang, Assistant Professor Department of Civil, Structural and Environmental.

National Modeling TRB Transportation Planning Applications Conference May 5, 2013.

PDNWC Coordinated Database Project Briefing of Congressional Staff NM Water Resources Research Institute, 4 August 2004 El Paso Water Utilities, 10 September.

Utilizing GIS and EMME/2 for Evaluating the Impacts of Development Nathan Masek GIS Transportation Planner Bernalillo County Public Works Division Albuquerque,

Urban Planning Group Implementation of a Model of Dynamic Activity- Travel Rescheduling Decisions: An Agent-Based Micro-Simulation Framework Theo Arentze,

Travel Demand Forecasting: Traffic Assignment CE331 Transportation Engineering.

Transportation Planning: An Introduction CE331 Transportation Engineering.

Responses to Gas Prices in Knoxville, TN Vince Bernardin, Jr., Ph.D. Vince Bernardin, Jr., Ph.D. Bernardin, Lochmueller & Associates Mike Conger, P.E.

Reconciliation of regional travel model and passive device tracking data 14 th TRB Planning Applications Conference Leta F. Huntsinger Rick Donnelly.

Applications in Mobile Technology for Travel Data Collection 2012 Border to Border Transportation Conference South Padre Island, Texas November, 13, 2012.

Sustainability Performance Measures for the City of El Paso’s Rapid Transit Systems Kyle Ibarra, Sun Metro Transit Tara Ramani, Texas A&M Transportation.

1st November, 2016 Transport Modelling – Developing a better understanding of Short Lived Events Marcel Pooke – Operational Modelling & Visualisation Manager.

Validating Trip Distribution using GPS Data

Jim Henricksen, MnDOT Steve Ruegg, WSP

Chapter 4. Modeling Transportation Demand and Supply

Travel Demand Forecasting: Mode Choice

Using Google’s Aggregated and Anonymized Trip Data to Estimate Dynamic Origin-Destination Matrices for San Francisco TRB Applications Conference 2017 Bhargava.

Jim Lam, Caliper Corporation Guoxiong Huang, SCAG Mark Bradley, BB&C

Unique Challenges Urban and economic factors Geographic limitations

Chattanooga Transportation Data Collection Review

TNMUG – MPO Data Needs Discussion Knoxville Regional TPO Perspective

Pan American Caravan for Health United States of America-Mexico Border National Infant Immunization Week Paso del Norte Region 21 April 2008 Sunland Park,

Comparison and Analysis of Big Data for a Regional Freeway Study in Washington State Amanda Deering, DKS Associates.

Presentation transcript:

5 th Bi-Annual Border to Border Conference Development of an Origin-Destination Matrix for the Paso Del Norte Region (Regional Master Network Phase IV) McAllen, Texas November 19 th, 2014

Background The Center for International Intelligent Transportation Research (CIITR) is committed to enhancing the quality of life for the Paso Del Norte Region and to developing solutions that can be successfully applied in other U.S. border environments

Background Project Phases: 1. Integration of the Transportation Network and Transportation Analysis Zones (TAZs) Ciudad Juarez and Las Cruces 2. Integration of El Paso’s Network and TAZs into the Regional Network 3. Exploring alternatives to build a regional Origin- Destination Matrix (ODM) 4. Developing the regional ODM (current)

Background Paso Del Norte: El Paso, TX Las Cruces, NM Ciudad Juarez, CHI Source: Organization of Economic Cooperation and Development

Background

Regional MN Integration El Paso, Texas Las Cruces, New Mexico Ciudad Juarez, Chihuahua

Background (strategic grid for checking)

Background Most common problems related to network-based modeling at CIITR: missing links incorrect attributes incorrect names directionality and topology lack of projection/coordinate system no metadata

Literature Review Four-Step Trip based traditional Approach Activity-based approach Simplified Geographic Origin-Destination Generation (SGODG) Development of origin–destination matrices using mobile phone call data Dynamic Origin-Destination Demand Estimation and Prediction for Off-line and On-line Dynamic Traffic Assignment Operation.

Summary of Findings Alternative/Method Approximated Cost (thousand dollars) AdvantagesDisadvantages Direct Measurements$420-$500 Accurateness and reliability Cost and time consuming Traffic Counts + Algorithms $80-$90Few steps for its implementation Computer processing and algorithm development time Simplified Geographic$40-$45 Low-cost alternative Calibration and validation Household Data (regressions) $80-$110Time and resources savings: quicker implementation than other methods Household data acquisition (Ciudad Juarez) TRANUS land use based$55-$65Direct generation of a regional O-D Calibration/Validation (International POE) Cellphone Data$75-$82Accurateness suitable for big areas Relatively expensive, time consuming processing (Different cell providers policies) Bluetooth TechnologyN/AEasy to implement, Excellent for External-to-External O-D Not suitable for internal zones (O-D). Low capture range and high cost. No vehicle classification.

OD Demand Calibration Framework

Data Collection (El Paso)

Data Collection (Ciudad Juarez)

Data Collection (Las Cruces)

Data Collection (Pneumatic Road Tube Installation and Manual Counts)

Data Collection (24-hr Camera Equipment)

Next Steps (TAZ Restructure) Utilizing GIS to Create the Lower Rio Grande Valley Travel Demand Model Geographies (Kevin Hall-Border to Border 2012)

Next Steps (TAZ Restructure)

Questions? Contact Information: Luis David Galicia Assistant Research Scientist Texas Transportation Institute The Texas A&M University System 4050 Rio Bravo Drive, Suite 151 El Paso, Texas (915)