1 RANKING OF FUNCTIONAL REQUIREMENTS/ TOPIC AREAS FOR NEEDED RESEARCH BY THE TRB TRAFFIC SIGNAL SYSTEMS COMMITTEE JULY 21, 2002 MID-YEAR MEETING IN SALT.

Slides:



Advertisements
Similar presentations
Overview What is the National ITS Architecture? User Services
Advertisements

Travel Time Estimation on Arterial Streets By Heng Wang, Transportation Analyst Houston-Galveston Area Council Dr. Antoine G Hobeika, Professor Virginia.
Transit Signal Priority Applications New Technologies, New Opportunities Peter Koonce, PE APTA BRT Conference – Seattle, WA Wednesday, May 5, 2009 Technology.
Byron Becnel LA DOTD June 16, Microscopic simulation models simulate the movement of individual vehicles on roads It is used to assess the traffic.
Introduction to VISSIM
Dynamic Traffic Assignment: Integrating Dynameq into Long Range Planning Studies Model City 2011 – Portland, Oregon Richard Walker - Portland Metro Scott.
Transportation Engineering
INTRODUCTION TO TRANSPORT Lecture 3 Introduction to Transport Lecture 4: Traffic Signal.
Transportation Data Palooza Washington, DC May 9, 2013 Steve Mortensen Federal Transit Administration Data for Integrated Corridor Management (ICM) Analysis,
EX-1 Intersections & Interchanges Improved Traffic Signal Control Ramp metering Intersection Collision Avoidance Systems Automated Enforcement.
Lecture #12 Arterial Design and LOS Analysis. Objectives  Understand the factors in arterial design Understand how arterial LOS is determined.
CTC-340 Signals - Basics. Terms & Definitions (review) Cycle - Cycle Length - Interval -. change interval - clearance interval- change + clearance = Yi.
TRANSPORT MODELLING Lecture 4 TRANSPORT MODELLING Lecture 4 26-Sep-08 Transport Modelling Microsimulation Software.
Advanced Traveler Information System ATIS. What are Intelligent Transportation Systems (ITS) ? The application of advanced sensor, computer, electronics,
Low Delay Marking for TCP in Wireless Ad Hoc Networks Choong-Soo Lee, Mingzhe Li Emmanuel Agu, Mark Claypool, Robert Kinicki Worcester Polytechnic Institute.
REAL-TIME SOFTWARE SYSTEMS DEVELOPMENT Instructor: Dr. Hany H. Ammar Dept. of Computer Science and Electrical Engineering, WVU.
Month XX, 2004 Dr. Robert Bertini Using Archived Data to Measure Operational Benefits of ITS Investments: Ramp Meters Oregon Department of Transportation.
Optimal Adaptive Signal Control for Diamond Interchanges Using Dynamic Programming Optimal Adaptive Signal Control for Diamond Interchanges Using Dynamic.
Customized Simulation Modeling Using PARAMICS Application Programming Interface Henry Liu, Lianyu Chu & Will Recker.
 Life in communities has changed over the years.  One of those changes is in transportation. Transportation is a way of moving people or things from.
Traffic Incident Management – a Strategic Focus Inspector Peter Baird National Adviser: Policy and Legislation: Road Policing.
2015 Traffic Signals 101 Topic 7 Field Operations.
2015 Traffic Signals 101 Topic 11 Emergency Vehicle Preemption (EVP) and Railroad (RR) Preemption.
RT-TRACS A daptive Control Algorithms VFC-OPAC Farhad Pooran PB Farradyne Inc. TRB A3A18 Mid-Year Meeting and Adaptive Control Workshop July 12-14, 1998.
Transportation leadership you can trust. presented to Talking Operations Webinar presented by Richard Margiotta Cambridge Systematics, Inc. June 28, 2006.
Oregon Microsimulation Roundtable March 2012
Freight Bottleneck Study Update to the Intermodal, Freight, and Safety Subcommittee of the Regional Transportation Council September 12, 2002 North Central.
Envisioned Role for NTI Concerning ITS Deployment in Egypt by Dr. Mahmoud EL-HADIDI Professor of Telecommunications at Cairo U & Consultant at NTI 3 rd.
VII Data Characteristics for Traffic Management: Task Overview and Update 21 June 2006 Karl Wunderlich Fellow, Transportation Analysis.
ITS (u-Transportation) for u-City 29 th APEC Transportation Working Group Meeting Taipei, Chinese Taipei 9-13 July 2007 The Korea Transport Institute.
Role of the Highway-Rail Intersection in the National ITS Architecture IEEE WG14 June 20, 2000 Bruce Eisenhart Lockheed Martin Architecture Development.
A Case Study of Promoting Metropolitan Freight Collaboration: The Twin Cities Experience Performance Management Framework Minnesota Department of Transportation.
1 Modeling Active Traffic Management for the I-80 Integrated Corridor Mobility (ICM) Project Terry Klim, P.E. Kevin Fehon, P.E. DKS Associates D.
Incident Management in Central Arkansas: Current Settings and Proposed Extensions Weihua Xiao Yupo Chan University of Arkansas at Little Rock.
HYBRID ROUTING PROTOCOL FOR VANET
Dixie Regional ITS Architecture Project Summary July 31, 2006.
WSDOT SW Region, Vancouver, WA December 7, 2009 WSDOT SW Region, Vancouver, WA December 7, 2009 Tolling Study Committee.
Transit Priority Strategies for Multiple Routes under Headway-based Operations Shandong University, China & University of Maryland at College Park, USA.
Accuracy in Real-Time Estimation of Travel Times Galen McGill, Kristin Tufte, Josh Crain, Priya Chavan, Enas Fayed 15 th World Congress on Intelligent.
NATMEC June 5, 2006 Comparative Analysis Of Various Travel Time Estimation Algorithms To Ground Truth Data Using Archived Data Christopher M. Monsere Research.
Prediction of Traffic Density for Congestion Analysis under Indian Traffic Conditions Proceedings of the 12th International IEEE Conference on Intelligent.
November 15, 2005 Dr. Robert Bertini Dr. Sue Ahn Using Archived Data to Measure Operational Benefits of a System-wide Adaptive Ramp Metering (SWARM) System.
Walter Kulyk, P.E. Director, Office of Mobility Innovation Federal Transit Administration Session 11: ITS Research in the U.S. and Abroad 2007 ITSA Annual.
Siemens Traffic Controls Ltd ITSE99/Standards 1 Traffic Management and Control Workshop on Research and Technological Development for Information Society.
Strategic Highway Research Program 2 Project L07 Identification and Evaluation of the Cost- Effectiveness of Highway Design Features to Reduce Nonrecurrent.
1 Using Intelligent Transportation Systems (ITS) Technologies and Strategies to Better Manage Congestion Jeffrey F. Paniati Associate Administrator of.
TRANSIMS Version 5 Network Files January 20, 2011 David Roden – AECOM.
Transportation Research Board Report Ray Derr.
Context and Priorities April 9,  Why FHWA Focuses on Improving Operations  FHWA Operations Program Areas  Key Current Program Priorities.
Corridor Congestion Management Innovation for better mobility sm.
Modeling Drivers’ Route Choice Behavior, and Traffic Estimation and Prediction Byungkyu Brian Park, Ph.D. Center for Transportation Studies University.
Transit Signal Priority: Managing Expectations Kevin N. Balke, Ph.D., P.E TransLink ® Research Center Director Texas Transportation Institute Transportation.
Using Archived Data to Measure Operational Benefits of a System-wide Adaptive Ramp Metering (SWARM) System Data Collection Plan / Experimental Design May.
1 CEE 8207 Summer 2013 L#6 Queue. 2 Queueing System Provide a mean to estimate important measures of Highway Performance  Travel time  Speed Affects.
Integrated Corridor Management Initiative ITS JPO Lead: Mike Freitas Technical Lead: John Harding, Office of Transportation Management.
Overview of King County Transit Signal Priority Program T3 Webinar January 22, 2008.
CEE 495/771 – Fall 2008 Topic 9 Ramp Metering Ramp Metering.
ABJ60 – Spatial Data and Information Science – Operations and Congestion Operations and Congestion.
Intelligent and Non-Intelligent Transportation Systems 32 Foundations of Technology Standard 18 Students will develop an understanding of and be able to.
TSSM BI-WEEKLY MEETING and Stakeholder Update
Intelligent Transportation System
Traffic Control & Coordination
MOVA Traffic Signal Control Trial
Non-recurrent Congestion & Potential Solutions
Macroscopic Speed Characteristics
SAE DSRC Technical Committee work and outlook
Transit Signal Priority: Evolution
MODULE 2: TSMO Strategies
MODULE 2: TSMO Strategies
Presentation transcript:

1 RANKING OF FUNCTIONAL REQUIREMENTS/ TOPIC AREAS FOR NEEDED RESEARCH BY THE TRB TRAFFIC SIGNAL SYSTEMS COMMITTEE JULY 21, 2002 MID-YEAR MEETING IN SALT LAKE Note: These requirements were first defined by the committee in the early 90s; 9 were added at the 2000 Seattle meeting. By design, explanation/discussion of content & definition did NOT take place - the idea was to get a sense of the committee regarding research priorities. From this list, Research Problem Statements can be developed. Following are in three priority groups (High, Medium, Low) per the voting; no specific order within a group. - Jim Powell 7/23/02

2 High 1. Provide on-line (real-time) creation or modification of traffic plans. (B5) 2. Provide for integration of available data from multiple sources (B1) (e.g., travel time, queue lengths) into required traffic plans (phasing, timing, related functions); use expert systems? 6. Provide travel time estimation and verification. (A5) (i.e., for better timing plans and routing strategies; use probe vehicles?) 7. Provide plan selection by notification of congestion or near saturation conditions. (C5)

3 High (cont.) 17. Provide processing of preempt/priority vehicle requests. (A3) (e.g., emergency vehicle, transit veh., other ITS subsystems) 28. Closely spaced intersections. 30. Traffic safety related to signal system operation. 31. Ramp metering interaction with traffic signals.

4 Medium 3. Provide processing of data from other data collection devices/techniques. (A2) (e.g., above ground detectors/video detectors, environ. detectors, “probe” vehicles) 4. Provide arterial incident detection. (A4) (i.e., additional detection hardware & software) 5. Provide techniques for short term traffic flow prediction. (B4) 9. Provide several control objectives. (C8) (e.g., min. delay, queue/congestion dissipation, demand “gating”, improved air quality)

5 Medium (cont.) 12. Provide an on-line presentation of traffic demand, short term estimates and available system responses. (F12) (i.e., so operators can make final decision on control changes). 20. Provide for implementation of adaptive control algorithms at the controller. (D7) 29. Traffic models/simulation.

6 Low 11. Provide measures of long term traffic trends. (A6) (i.e., post processing and analysis capabilities for performance evaluation and system planning) 13. Provide on-line, expert system calculation of actual values for intersection/system measures of effectiveness specific to the various control objectives. (G2) 25. Pedestrian/bicycle issues. 26. Commercial vehicle issues. (e.g., special timing, relation to ITS systems/routing, etc.) 27. Driver expectations.

7 Low (cont.) 32. Driver expectancy at grade crossings. 33. Detection/classification of train movements (relative to grade crossings).