Xpress Bus Data Collection Data is collected from two sources: (a)Driver surveys of ridership (weekly) (b)Revenue-based ridership (monthly) Revenue-based.

Slides:



Advertisements
Similar presentations
Interim Guidance on the Application of Travel and Land Use Forecasting in NEPA Statewide Travel Demand Modeling Committee October 14, 2010.
Advertisements

#EMF2014 Transportation Solution Roundtable. #EMF2014 Post-Presentation Discussion Period.
APC at NJT From Zero to 100% Dave Rynerson October 16, 2014.
How can we relieve congestion in the I-95 corridor? I-95 Congestion Relief Study.
GREATER NEW YORK A GREENER Travel Demand Modeling for analysis of Congestion Mitigation policies October 24, 2007.
NEW YORK CITY TRAFFIC CONGESTION MITIGATION COMMISSION NYSDOT Comments on New York City Traffic Congestion Mitigation Plan Bob Zerrillo, Director, Office.
SR520 Urban Partnership Project 2008 ITS Washington Annual Meeting November 12th, 2008 – Seattle Jennifer Charlebois, P.E. Tolling and Systems Project.
TRB Lianyu Chu *, K S Nesamani +, Hamed Benouar* Priority Based High Occupancy Vehicle Lanes Operation * California Center for Innovative Transportation.
The Potential BRT in Asia
Presentation to the Subcommittee on Highways and Transit and the House Committee on Transportation and Infrastructure Peggy Catlin, Deputy Executive Director.
11 May, 2011 Discrete Choice Models and Behavioral Response to Congestion Pricing Strategies Prepared for: The TRB National Transportation Planning Applications.
2010 Travel Behavior Inventory Mn/DOT TDMCC- Jonathan Ehrlich October 14, 2010.
The First International Transport Forum, May , Leipzig INDUCING TRANSPORT MODE CHOICE BEHAVIORIAL CHANGES IN KOREA: A Quantitative Analysis.
Engaging in Transportation Engineering Initiatives with K-12 Students Elementary & Middle School Centennial Place Academy Overview Georgia Tech researchers.
National Road Pricing Conference June 4, 2010 Mark Burris, Texas Transportation Institute Jessie Yung, Federal Highway Administration.
Bureau of Transportation Statistics U.S. Department of Transportation Overall Travel Patterns of Older Americans Jeffery L. Memmott
Transportation 101 June 12, Presenting Agencies  Southwestern PA Commission’s CommuteInfo program  GG & C Bus Company, Inc.  Mid Mon Valley Transit.
Transportation leadership you can trust. presented to TRB Planning Applications Conference presented by Vamsee Modugula Cambridge Systematics, Inc. May.
Transportation 101 August 7, Presenting Agencies  Southwestern PA Commission’s CommuteInfo program  IndiGO: Indiana County Transit Authority 
State of Transportation: Atlanta, GA Chris Clark University of New Orleans 10 February 2011.
MIAMI UNIVERSITY BUS SYSTEM IMPROVEMENT PLAN. What’s the problem? ●A current Miami student pays $66 per semester for transit fees that goes towards the.
Arriva in Southend Kevin Hawkins Commercial Director.
I-394 MnPASS Technical Evaluation Preliminary Findings March 23, 2006 Doug Sallman – Cambridge Systematics, Inc.
I-394 MnPASS Technical Evaluation Doug Sallman – Cambridge Systematics, Inc.
Soup to Nuts: Changing Operating Parameters for HOV Facilities Sponsored by the HOV Pooled-Fund Study and the Federal Highway Administration.
Client Name Here - In Title Master Slide Data Requirements to Support Road Pricing Analyses Johanna Zmud, Ph.D. NuStats Partners, LP Expert Forum on Road.
Convergence of Transportation Policy and RFID Enabler of Future Transportation Policy Chris Body Mark IV Vice President, Business Development.
Business Logistics 420 Public Transportation Lecture 19:Cost Models for Public Transportation.
Regional Priority Bus Transit Conference June 24, 2009.
Major Transportation Corridor Studies Using an EMME/2 Travel Demand Forecasting Model: The Trans-Lake Washington Study Carlos Espindola, Youssef Dehghani.
Transportation leadership you can trust. presented to 12 th Annual TRB Transportation Planning Application Conference presented by Dan Goldfarb, P.E. Cambridge.
Bigger Bang for the Buck Panel Discussion: Improving the ROI on Transit Investments with TDM.
Roads & Traffic Department College Green Public Transport Priority measure.
1 Challenge the future Feed forward mechanisms in public transport Data driven optimisation dr. ir. N. van Oort Assistant professor public transport EMTA.
00 Metropolitan Transit System Transit Serving Point Loma September 23, 2008.
ITS PCB T3 Webinar October 21, 2008 Montgomery County, Maryland Advanced Transportation Management System Automated Parking Information System Operational.
Marko Matulin University of Zagreb Faculty of Transport and Traffic Sciences Zagreb, 21 October 2013 CIVITAS-ELAN Measure 4.4: Mobility management for.
Assessing the Marginal Cost of Congestion for Vehicle Fleets Using Passive GPS Data Nick Wood, TTI Randall Guensler, Georgia Tech Presented at the 13 th.
Transportation Management, Intelligent Transportation Systems, and Other Adaptations to Maturity in the Highway Sector David Levinson.
Portland State University 11 By Maisha Mahmud Li Huan Evaluation Of SCATS Adaptive Traffic Signal Control System.
Rod Weis, Texas A&M University Lana Wolken, Texas A&M University Joe Richmond, University of North Texas Operating Your Own System Versus Contracting.
THE EL MONTE HOV / BUSWAY: A Policy Driven Experiment in Congestion Management Frank Quon Division of Operations Deputy District Director HOV LANES IN.
1 Weekly Supervisor Meeting – Project Waalbrug Project Waalbrug Improving transport accessibility in Nijmegen Bernat Goni, Vikash Mohan, Arjen van Diepen,
TPB CLRP Aspirations Scenario 2012 CLRP and Version 2.3 Travel Forecasting Model Update Initial Results Ron Kirby Department of Transportation Planning.
CTR Performance WSDOT Nisqually Board Room December 4, 2015 Lynn Peterson Secretary of Transportation 2013/2014 Cycle Additional CTR Performance Paul Mason.
Estimating Volumes for I-95 HOT Lanes in Virginia Prepared for: 2009 Planning Applications Conference Houston, TX May 18, 2009 Prepared by: Kenneth D.
Materials developed by K. Watkins, J. LaMondia and C. Brakewood Frequency Determination Unit 5: Staff & Fleet Scheduling.
Transportation: Issues and
1 FY2006 TDA Triennial Performance Audits Metropolitan Transportation Commission Programming & Allocations Committee October 4, 2006 GGBHTD (Golden Gate)
This Briefing is: UNCLASSIFIED 355th Logistics Readiness Squadron Vanpooling Program 2Lt Brittany Ziehler OIC, Distribution 17 Apr 09.
Community Partnership Program Don Okazaki, Planner Accessible Services King County Metro.
Transport.tamu.edu TAMING WILD BRONCOS Transit Management Changes, Financing, Training, Staffing Rod Weis, Texas A&M University Lana Wolken, Texas A&M.
The Current State-of-the-Practice in Modeling Road Pricing Bruce D. Spear Federal Highway Administration.
I-75 South Metro Managed Lanes. Project Description Two reversible toll lanes along I-75 South 12 miles from SR 155 to SR 138 Anticipated opening date.
Company LOGO Georgia Truck Lane Needs Identification Study Talking Freight Seminar March 19, 2008 Matthew Fowler, P.T.P Assistant State Planning Administrator.
Summary of the WILMAPCO Congestion Management Process Prepared for T3 Webinar September 18, 2007.
1 Toll Modeling Analysis for the SR 520 Bridge Replacement and HOV Project 19 th Annual International EMME/2 Users’ Conference October 19-21, 2005 Presented.
Gastonia Transit Expansion Study City Council/Planning Commission Joint Transportation Workshop September 13, 2007.
Successful Commute Programs Critical components include: 1.An active and informed Employee Transportation Coordinator (you!) 2.Guaranteed ride home 3.Parking.
Transportation Fee FY2016 January 16, Services Provided by Transportation Stinger Buses - Three routes with 10 buses operating weekdays and two.
Center for Urban Transportation Research | University of South Florida Performance Measurement.
WELCOME! Commute Trip Reduction (CTR) Survey Briefing.
Macro / Meso / Micro Framework on I-395 HOT Lane Conversion
Overview of FHWA CMAQ & System Performance Measures
Flagler County Fixed Route Transit Operation Plan
Nick Wood, P.E. Texas A&M Transportation Institute
Use of Transportation Network Companies among MARTA Patrons
Slugging in the I-395 Corridor
Instructor: Dr. Francisco Olivera CONCLUSIONS AND RECOMMENDATIONS
Performance Measurement
Presentation transcript:

Xpress Bus Data Collection Data is collected from two sources: (a)Driver surveys of ridership (weekly) (b)Revenue-based ridership (monthly) Revenue-based data serve as the control total for express bus passenger throughput, and the driver- collected data provide allocation ratios by route and time of day to disaggregate the total monthly bus ridership data to the scheduled vehicles for hourly and daily throughput estimation. Accuracy of driver-surveys is checked through field deployments (see below). 40 Felipe Castrillon, Maria Roell, Sara Khoeini, Randall Guensler The I-85 HOT Lane’s Impact on Atlanta’s Commuter Bus and Vanpool Occupancy Summary Commuter Bus (weekly): Vehicle occupancy decreased by -6.0 (-17%) and -3.3 (-11.5%) as vehicle throughput increased and person throughput remained mostly unchanged. Vanpool (weekly): Vehicle throughput increased by 15 units (13.3%). Total vanpool volume is insignificant compared to total corridor volume. Discussion: The data from this study cannot be used to draw specific conclusions regarding the HOT lane’s direct or indirect impact on the occupancy of buses and vanpools. Increased express bus service and reliability was concurrent with a fare increase. Behavioral data collection and analysis would be required to assess how HOT lane performance/price affected traveler decision making. This research was sponsored by the Georgia Department of Transportation. Opinions expressed here are those of the authors and not necessarily those of the Georgia Department of Transportation. Overview Atlanta opened its first High Occupancy Toll (HOT) lanes on October 2011, which were converted from High Occupancy Vehicle (HOV) lanes. In partnership, Georgia Tech established a research team to assess changes in vehicle throughput, vehicle occupancy, and passenger throughput associated with the I-85 HOV-to- HOT conversion. In order to assess these measures, commuter bus ridership, which carried a significant portion of ridership, could not be collected via the applied field data collection efforts. Moreover, the ridership and vehicle throughput effect on vanpools, which also ride on the managed lanes, is unknown. The purpose of this research is to estimate the change in vehicle and person throughput of alternative modes before and after the HOV-to-HOT conversion. Xpress Bus Results Xpress Bus Ridership Factors Express buses represent only about 0.1% of corridor vehicle throughput during the morning peak period, but carry more than 4% of person throughput during the morning peak. Express bus ridership in winter/spring 2012 was practically unchanged, given the number of buses added to service. The lack of maturity of the newly added bus lines (implemented in September 2011 and evaluated in February-April) may have played a significant role. Another major factor specific to winter/spring 2012, however, was a significant fare increase in 5 out of the 8 lines. Figure 1 – Driver survey count accuracy Vanpools Vanpool ownership by company: VPSI - ~50 vehicles Enterprise - 12 vehicles Post-conversion data: Vehicle occupancy is collected from surveys sent to the companies Vehicle throughput is collected from Peach Pass RFID tags Pre-conversion data: Vehicle occupancy from post-conversion is used due to lack of reliable data Vehicle throughput is factored using video collected data from Georgia Tech’s deployment Results: Deployment Area