DRIVE Net: An E-Science Transportation Platform for Big Data, Big Discoveries, and Big Decisions PacTrans STAR Lab University of Washington July 17, 2015.

Slides:

Advertisements

Similar presentations

Overview Examples of TranSight Applications What Does TranSight Analyze? Model Structure.

Advertisements

Overview of a Timely Publication. Transportations importance has been recognized since colonial times National defense Economic vitality Quality of life.

VTrack: Energy-Aware Traffic Delay Estimation Using Mobile Phones Lenin Ravindranath, Arvind Thiagarajan, Katrina LaCurts, Sivan Toledo, Jacob Eriksson,

Jack Faucett Associates and ECONorthwest Presented to the 2012 Symposium on Mileage-Based User Fees and Transportation Finance Summit Presented By Michael.

GIS and Transportation Planning

Overview  Improving highway safety is a priority for all state transportation departments.  Key roadway characteristics can be used to identify sections.

CALTRANS’ TRANSPORTATION SYSTEM MANAGEMENT & OPERATIONS CTP 2040 PAC 1 Kris Kuhl Assistant Division Chief, Division of Traffic Operations 4/15/2014 CREATING.

The US 101 Mobility Study will -  Examine current and future conditions, identify key deficiency areas and propose multi-modal improvement packages along.

Mobile Resource Manager v2. Core Pillars  Engine - High fuel costs, vehicle maintenance  Productivity - Customers expect increasing levels of service.

1 Civil GPS Service Interface Committee (CGSIC) Rudy Persaud U.S. DOT-FHWA APEC GNSS Implementation Team Seattle, WA June 23, 2010 State and Local Government.

Transportation Data Palooza Washington, DC May 9, 2013 Steve Mortensen Federal Transit Administration Data for Integrated Corridor Management (ICM) Analysis,

Visual Traffic Simulation Thomas Fotherby. Objective To visualise traffic flow. –Using 2D animated graphics –Using simple models of microscopic traffic.

Transforming Transportation: The Role of Intelligent Transportation Systems Matthew J. Schiemer, PE August 18, 2011.

Archived Data User Services (ADUS). ITS Produce Data The (sensor) data are used for to help take transportation management actions –Traffic control systems.

June 16, 2004 Dr. Robert Bertini Michael Rose Evaluation of the “COMET” Incident Response Program Oregon Department of Transportation.

Congestion Reduction Using Intelligent Transportation Systems Ben Sperry University of Evansville University of Evansville MESCON March 25, 2006.

Intelligent Transportation System Using GIS

Pacific Northwest Transportation Consortium University Transportation Center For Region 10 PacTrans Safety Research and Education Overviews Universities.

European Intelligent Transportation Systems Market B Published Feb

Yinhai Wang University of Washington and Harbin Institute of Technology For OpenITS Symposium Oct.

Florida Department of Transportation District 4 TSM&O Program Advanced Transportation Management System (ATMS) Installation in South Broward County ATMS.

Sensys 2009 Speaker:Lawrence.  Introduction  Overview & Challenges  Algorithm  Travel Time Estimation  Evaluation  Conclusion.

School travel planning an engineer will love. School travel in Moonee Valley Need: A more planned and coordinated approach to active travel program delivery.

Institute for Transportation Research and Education – N.C. State University High Resolution In Vehicle Sensing Nagui M. Rouphail.

Regional Traffic Monitoring System for Maryland’s Eastern Shore Dr. Gang-Len Chang Traffic Safety and Operations Lab University of Maryland, College Park.

Truths and Myths about Traffic Data Truths and Myths about Traffic Data ITSA Presentation June 2007 AirSage Proprietary & Confidential.

Freight Analysis Framework version 3 (FAF3) __________ Talking Freight Webinar October 2010.

Freight Bottleneck Study Update to the Intermodal, Freight, and Safety Subcommittee of the Regional Transportation Council September 12, 2002 North Central.

Intelligent Transportation System (ITS) ISYM 540 Current Topics in Information System Management Anas Hardan.

Quantifying Transportation Needs and Assessing Revenue Options: The Texas Experience presented to The Arkansas Blue Ribbon Committee on Highway Finance.

4-1 Model Input Dollar Value  Dollar value of time  Accident costs  Fuel costs  Emission costs.

A Military Logistics and Transportation Security Application.

Automobiles. Intelligent Transportation System Intelligent Transportation System –  It is a real time transportation networks management solution with.

WSDOT SW Region, Vancouver, WA December 7, 2009 WSDOT SW Region, Vancouver, WA December 7, 2009 Tolling Study Committee.

Integration of Transportation System Analyses in Cube Wade L. White, AICP Citilabs Inc.

1 IntelliDrive SM Research, Development and Emerging Technologies National ITS Perspective Panel Joseph I. Peters, Ph.D. Federal Highway Administration.

The Science of Prediction Location Intelligence Conference April 4, 2006 How Next Generation Traffic Services Will Impact Business Dr. Oliver Downs, Chief.

Abstract Transportation sustainability is of increasing concern to professionals and the public. This project describes the modeling and calculation of.

The Fully Networked Car Geneva, 4-5 March Ubiquitous connectivity to improve urban mobility Hermann Meyer ERTICO.

Traffic Safety and Operations Lab Dept. of Civil and Environmental Engineering University of Maryland, College Park Maryland State Highway Administration.

INTELLIGENT TRANSPORTATION SYSTEM BY – ANTARA DEY SIKDAR M.T.R.P, Ist SEMESTER B.E.S.U.

1. Variety of modes (types) of transport (public and private) 2. Density of transport networks more nodes and.

Transportation leadership you can trust. presented to Safety Data Analysis Tools Workshop presented by Krista Jeannotte Cambridge Systematics, Inc. March.

Robert Brydia Project Lead, I-35 Traveler Information During Construction Texas A&M Transportation Institute WORK ZONES & LARGE TRUCKS THE CENTRAL TEXAS.

Motivation Low operating cost Large monitoring area Emergency response.

Better Roads. Better World. Green, Accessible, Intelligent Transport (GAIT) Dr. Hediye Tüydeş Yaman Assoc.Prof. Middle East Technical University.

Wireless Sensor Network Solutions Regional Mobility Solutions Sensys Networks and the Sensys Networks logo are trademarks of Sensys Networks, Inc. Other.

DRIVE Net: A Large-Scale Online Data Platform for Performance Analysis and Decision Support Yinhai Wang PacTrans STAR Lab University of Washington

Abstract Background Methodology Methods While the project is in the data-collection and background research phase, there are several studies that utilize.

1 Update on the Congestion Management Process (CMP) and Related Data Activities Wenjing Pu COG/TPB Staff Travel Management Subcommittee Meeting May 26,

Capstone Project Fall Course Information Instructor Ye Zhao –Office: MSB 220 – Fall 2015 (MSB162) –Time: Tue, Thu 10:45am.

© Infotripla Ltd 2005 Traffic monitoring with FCD- and traffic signal data in Tampere region VIKING Workshop Best practices on monitoring deployment 5.

TRAVEL TIME ANALYSIS Use of Data IN-KY-OH Traffic Incident Management Conference October 9, 2015 Dayton, OH.

December 17, 2010 Developing Transit Performance Measures for Integrated Multi-Modal Corridor Management.

Presented By: Jizhou Wu.  Traffic causes inconvenience to students  Driving consumes fuel energy and money  Driving causes environment issues  Driving.

Summary of the WILMAPCO Congestion Management Process Prepared for T3 Webinar September 18, 2007.

PG Funding and Management Strategies Paris Some thoughts on Road Pricing.

INTEGRATING ASSESSMENT OF THE ECONOMIC BENEFITS OF TRANSPORTATION IMPROVEMENTS IN PROJECT-LEVEL ALTERNATIVES ANALYSIS Meiwu An, Pikes Peak Area Council.

Intelligent and Non-Intelligent Transportation Systems 32 Foundations of Technology Standard 18 Students will develop an understanding of and be able to.

Athens, Conference Hall, Ministry of Infrastructure, Transport and Networks, 5&6 November 2015 ALTERNATIVE-COLLECTIVE PATTERNS OF OWNERSHIP AND USE OF.

2040 LONG RANGE PLAN UPDATE Congestion Management Process Plan (CMPP) Major Update February 24, 2016.

Real-Time Traffic Network Management System Hossein Hashemi Transportation Research Laboratory.

Chapter 12: Urban Transportation Policy “Everything in life is somewhere else, and you get there in a car.” E. B. White, One Man’s Meat, (NY: Harper &

Urban Mobility Management and Emissions Measurement System Boile Maria 1,2 Afroditi Anagnostopoulou 1 Evangelia Papargyri 1 1 Centre for Research and Technology.

Intelligent Transportation System

Performance-Based Planning:

Emily Guenther Zach Olson Laura Scott Cameron Wein

How technology and data can bring needed improvements to air quality and the environment Dr Dave Williams 8th November 2018.

Twin 33s Update Monday, June 10, 2019.

Presentation transcript:

DRIVE Net: An E-Science Transportation Platform for Big Data, Big Discoveries, and Big Decisions PacTrans STAR Lab University of Washington July 17, 2015 John Ash Wenbo Zhu

PacTrans STAR Lab Research on DRIVE Net Background 1 What causes congestion and how to mitigate it? How much fuel and time wasted? How much extra pollution caused by traffic jam? Image source:

PacTrans STAR Lab Research on DRIVE Net Background 2 Picture source: How to monitor health condition of transportation infrastructure? Which infrastructure piece is the most critical for the roadway network?

PacTrans STAR Lab Research on DRIVE Net Other Sample Key Questions How to quantify the benefit from a transportation investment? How to measure vehicle miles of travel/vehicle hours of travel? What is the impact of a road construction project on travel? How to estimate traffic emissions at a given location and time? What is the impact of toll on users of different income levels? Where do pedestrians go and how to improve their safety? Which route deserves top priority to build? How to improve transit services without adding new resources? How does congestion form up and how to mitigate it? How much does an incident cost and how to reduce the cost? Where do trucks go and how to guide them to the best routes? 3

PacTrans STAR Lab Research on DRIVE Net Background 4 To answer critical transportation questions and make informed decisions, we need

PacTrans STAR Lab Research on DRIVE Net Data Hurdles 5 Segmented by jurisdictions Lack of standardization

PacTrans STAR Lab Research on DRIVE Net Age of Big Data 6 Traffic Sensors Transportation Big Data!

PacTrans STAR Lab Research on DRIVE Net Age of Big Data 7 Image sources:

PacTrans STAR Lab Research on DRIVE Net Digital Roadway Interactive Visualization and Evaluation Network (DRIVE Net) The system under development at the STAR Lab is called Digital Roadway Interactive Visualization and Evaluation Network (DRIVE Net) DRIVE Net is a system for the data sharing, visualization, modeling, and analysis Web-based system for e-science investigations Display real-time traffic information Data sharing platform Tools to evaluate and analyze data Standardized procedures Data quality control 8

PacTrans STAR Lab Research on DRIVE Net

New Generation Online Platform 10

PacTrans STAR Lab Research on DRIVE Net Key Features HCM Analysis Maps and Data Multi-Modal Detection Travel Time Analysis Safety Performance Upcoming Features 11

PacTrans STAR Lab Research on DRIVE Net Ongoing Functions Interstate Elevation Data 12

PacTrans STAR Lab Research on DRIVE Net Interstate Elevation Data Google Earth elevation extraction tool 13

PacTrans STAR Lab Research on DRIVE Net Interstate Elevation Data Interstate elevation curves Fuel consumption analysis Grade effects on traffic flow, speed, accidents, etc. 14

PacTrans STAR Lab Research on DRIVE Net 15 Thanks for your attention! DRIVE Net current developers: Ruimin Ke Dr. Weibin Zhang