the moving dynamic nature of progression curves for freeway incident related congestion

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THE MOVING DYNAMIC NATURE OF PROGRESSION CURVES FOR FREEWAY INCIDENT RELATED CONGESTION Neveen Shlayan PhD Student Transportation Research Center University of Nevada, Las Vegas

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The Moving Dynamic Nature of Progression Curves for Freeway Incident Related Congestion. Neveen Shlayan PhD Student Transportation Research Center University of Nevada, Las Vegas. Introduction . Incidents on urban freeways Causing congestion and delays in both directions - PowerPoint PPT Presentation

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Page 1: The Moving Dynamic Nature of Progression Curves for Freeway Incident Related Congestion

THE MOVING DYNAMIC NATURE OF PROGRESSION CURVES FOR FREEWAY

INCIDENT RELATED CONGESTION

Neveen ShlayanPhD Student

Transportation Research CenterUniversity of Nevada, Las Vegas

Page 2: The Moving Dynamic Nature of Progression Curves for Freeway Incident Related Congestion

Introduction Incidents on urban freeways Causing congestion and delays in both

directions Secondary impact has been poorly

defined by using static time and length thresholds

Does not cover the full range of effects, Resulting in erroneous datahttp://www.youtube.com/watch?v=q0FIO775hEE

Page 3: The Moving Dynamic Nature of Progression Curves for Freeway Incident Related Congestion

Why Does it Matter? Incident Management Policy Making Studying the overall impact of an incident

Financial Fatalities Productivity

Proper Definition of Secondary Incidents Secondary incidents compose 20 percent

of all nonrecurring events (Federal Highway Administration, FHWA-OP-04-052, 2004)

Page 4: The Moving Dynamic Nature of Progression Curves for Freeway Incident Related Congestion

Outline Thorough study of freeway incidents and

the progression curve Classical progression curves Case study in the Seattle, Washington VISSIM simulations Proposed Novel Progression Curve Conclusion

Page 5: The Moving Dynamic Nature of Progression Curves for Freeway Incident Related Congestion

FACTSTexas Transportation Institute, FHWA-HOP-09-005, 2008

Incidents cause 33% to 60% of all delays The capacity of the facility is reduced by

up to 17% (shoulder only) 63% one lane obstruction 77% two lane obstructions 50% due to “rubbernecking” effect

Page 6: The Moving Dynamic Nature of Progression Curves for Freeway Incident Related Congestion

NHP Average Arrival, Management, and Clearance times for incidents

on the I15 interchange in the Las Vegas Area

Page 7: The Moving Dynamic Nature of Progression Curves for Freeway Incident Related Congestion

Static Thresholds for Secondary Congestion

The maximum queue clearance length and clearance time for the incident

Carlos Sun and Venki Chilukuri Secondary Accident Data Fusion for Assessing Long Term Performance of Transportation Systems. US Department of Transportation, (MTC Project 2005-04):1–38, 2007.

Page 8: The Moving Dynamic Nature of Progression Curves for Freeway Incident Related Congestion

Dynamic Thresholds for Secondary Congestion

It was found that static and dynamic thresholds can vary in incident definitions by 30 percent.

Carlos Sun and Venki Chilukuri Secondary Accident Data Fusion for Assessing Long Term Performance of Transportation Systems. US Department of Transportation, (MTC Project 2005-04):1–38, 2007.

Page 9: The Moving Dynamic Nature of Progression Curves for Freeway Incident Related Congestion

Case StudyThe I-5 and I-405 interchange near Linwood north of Seattle, WA

An accident occurred at 2:55pm

Queue length of 2.3 “rubbernecking”

Page 10: The Moving Dynamic Nature of Progression Curves for Freeway Incident Related Congestion

Progression of the

queue after the incident clearance extends to twelve miles even after an hour from clearance

Page 11: The Moving Dynamic Nature of Progression Curves for Freeway Incident Related Congestion

VISSIM Simulations

Artificially Creating Accidents by Lane Obstructions and Speed Reduction

Page 12: The Moving Dynamic Nature of Progression Curves for Freeway Incident Related Congestion

Simulations Scheme Tracking the locations

of front and back of the queue

In the direction of the accident

In the opposite direction of the

accident “rubbernecking”

Low traffic volume (3000 vph)

Moderate traffic volume (5000 vph)

High traffic volumes (8000 vph)

Four, three, and two lane obstructions

Page 13: The Moving Dynamic Nature of Progression Curves for Freeway Incident Related Congestion
Page 14: The Moving Dynamic Nature of Progression Curves for Freeway Incident Related Congestion

Moving Dynamic Progression Curve

Page 15: The Moving Dynamic Nature of Progression Curves for Freeway Incident Related Congestion

Conclusion

Secondary congestion is highly dynamic

Secondary Incidents definition must be case specific

Page 16: The Moving Dynamic Nature of Progression Curves for Freeway Incident Related Congestion

Future Work• Development of detailed models that

will study all types of secondary congestion based on Shock wave analysis

A software is being built that will process data using the above analysis that will identify secondary incidents mapped to their primary ones

Page 17: The Moving Dynamic Nature of Progression Curves for Freeway Incident Related Congestion

Thank You!