An Analytical Framework for Managed Lane Facility Performance Evaluation

An Analytical Framework for Managed Lane Facility Performance Evaluation

Xiaoyue Cathy Liu

University of Washington

To Be Presented at the Western ITE Annual Meeting in Santa Barbara, CA

June 26th, 2012

Outline

• General Background• Methodological Framework • Cross-Weave Module• Friction Module• Summary

2

Project Overview – Why Managed Lanes?

• Congestion • A total urban congestion cost of $101 billion and total delay

hours of 4.8 billion hours in 2010

• Vehicle Miles Traveled vs. Roadway Capacity Increase

• Limited Infrastructure Expansion Capability

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4

Background

• NCHRP 03-96 Project: Analysis of Managed Lanes on Freeway Facilities

• A methodological framework is needed for analyzing freeway facilities with ML and GP lanes operated parallelly• Composition and behavior characteristics difference• Interaction between the two lane groups

5Managed Lane Characteristics

• Operational Strategy: HOV vs. HOT• Separation Type

• Barrier• Buffer• Stripe

Image: I-394 MnPass WA SR 167 HOT

Image: SR 91 Express Lanes

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Managed Lane Access

Type A: At-Grade Lane-Change Access

Type B: At-Grade Ramp Access

Type C: Grade-Sep. Ramp Access

• The most common ML type is left-concurrent

7Single vs. Multiple Lanes

• Single ML Lane – Inability to pass slow lead vehicle

0

10

20

30

40

50

60

70

80

0 200 400 600 800 1000 1200 1400 1600 1800 2000

Spee

d (m

ph)

Flow (pc/h/ln)

I-405 SB Los Angeles, CA

Sloped

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Single vs. Multiple Lanes

• Two ML Lanes – Ability to pass slow lead vehicles

0

10

20

30

40

50

60

70

80

0 200 400 600 800 1000 1200 1400 1600 1800 2000

Spee

d (m

ph)

Flow (pc/h/ln)

I-110 NB Los Angeles, CA

Flat

Types of Interaction Between GP and MLs

• Friction Effect - between Adjacent GP and Basic Segments• Poorly-operating GP lanes will have an adverse effect on the

operations of the adjacent ML due to their proximity

• Due to the proximity of GPL and ML traffic, increasing congestion levels on GPLs are proved to have an adverse effect on ML operations, well before the ML demand reaches breakdown levels

• This effect is particularly significant at single lane buffer-separated ML facilities

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Frictional Effect

Types of Interaction Between GP and MLs

• Cross Weaving Effect – at ML On/Off Ramp Segments• Cross-weaving flows between a GP lane ramp and ML

access may affect GP capacity and speed

Components of the Proposed Method

12

• Method builds upon HCM2010 Freeway Facilities Chapter • But several changes are needed

• Developing managed lane segment types• New speed-flow relationships in the Managed Lanes, including

frictional impact of congestion levels in the GP lanes on ML operations

• Cross-Weave effects across GP lanes

• Implementation to occur in FREEVAL Computational Engine

Step 1: Input DataDemand (GP+ML)Geometry (GP+ML)Time-Space Domain

Step 2: Adjust demand according to spatial and time units established

(if necessary)

Step 3: Compute Segment CapacitiesGP segments using existing methods

ML segments using new/revised methods

Step 4a: Adjust Segment CapacitiesEffects of weather and work zones

Step 4b: Cross-Weave AdjustmentReduction in GP Segment Capacity

resulting from ML Cross-Weave Flows

Step 5: Compute d/c ratiosAll lane groups

Step 7: Adjacent Friction EffectsEvaluate interaction between adjacent

GP and ML lane groups

Step 9: Compute Facility MOEsAssign appropriate level of service

Step 6a: Compute UndersaturatedService Measures

Computed for each lane group

Step 6b: Compute Oversaturated Service Measures


Legend

Existing HCM2010 Step

Existing HCM2010 Step with ML modifications

New Computational Step for ML analysis

Step 8: Lane Group LOSAssign LOS to each lane group considering

all friction and interaction effects



(if necessary)














Legend






Proposed Methodology



(if necessary)














Legend






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Segment Types for Speed-Flow Curves

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Quantifying Frictional Effect

vC-FFS=S 1

BP)-(c

BP)-(v CS)-(SBP -SBP=S

2

2

C

C

2fnff BP)-(v C-S=S

Where: S =Speed (mph) FFS = Free Flow Speed (mph) C1 = Linear Coefficient (or slope) v = Flow Rate (pcphpl) c = Maximum Observed Flow (pcphpl) SBP = Speed at Breakpoint (mph) CS = Speed at Capacity (mph) BP = Flow at Breakpoint C2 = Calibration Constant Sf = ML Speed during GP Congestion Snf = Speed of the corresponding non-friction curve for the same flow rate Cf = Friction Curve Constant

Quantifying Cross-Weave Effect

17Results Analysis

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Capacity Adjustment/Reduction Factor

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CRF Regression

where CW is the cross-weave flow measured in vph, Lcw-min is the length from the ramp gore to the beginning of BOA measured in ft, and number of GP lanes ranging from 2 to 4

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Computational Engine: FREEVAL-ML

• Build on FREEVAL-2010• Allow analysis of parallel GP and ML facility with common

lane groups • Development of aggregated and comparative performance

measures

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Summary

• A methodological framework is developed for analyzing freeway facilities with ML and GP lanes operated parallelly

• New modules incorporated in the analysis framework, such as friction module and cross-weave module are quantified via empirical research

• The computational engine is able to evaluate the parallel ML facilities and provide performance assessment to the users

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Documents

An Analytical Framework for Managed Lane Facility Performance Evaluation