1

TRB 2007

Lianyu Chu*, K S Nesamani+, Hamed Benouar*

Priority Based HighOccupancy Vehicle

Lanes Operation

* California Center for Innovative Transportation (CCIT), University of California, Berkeley+ Institute of Transportation Studies (ITS), University of California, Irvine

TRB 2007

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TRB 2007

Current HOV lane Operation in Southern California

• HOV operations– HOV lane operates 24

hours a day• HOV lane restrictions

– HOV 2+, Buses & Car pools

• HOV lane type– Barrier-separated

• Criticism– Congested during peak

period & underutilize the roadway capacity during off-peak

– Limited ability to shift SOV to transits & Car pools

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TRB 2007

Alternative Strategies

• Allowing Single occupant Hybrid vehicles in HOV lanes– e.g. California, Virginia

• Part-time HOV operation– e.g. Northern California

• High Occupancy Toll Lanes– Solo drivers can use by

paying toll– e.g. SR-91, I-15, I-10

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TRB 2007

Priority Based HOV Lane Concept

• Proposed HOV lane operation:– Vehicles are prioritized

based on occupancy, emissions & toll;

– Allows vehicles with a certain priority level based on dynamic traffic conditions

• Purpose:– To optimally utilize the

current HOV lane facility

Priority Level Vehicle Type

6 Bus

5 HOV 4+

4 HOV 3+

3 HOV 2+

2 Hybrids, LEV

1 SOV with toll

0 SOV

• Suggested priority levels

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TRB 2007

Implementation Strategy

• Operational objective: – Maintain the traveling speed > 45mph (defined by SAFETEA-LU)

• System requirements– Reliable vehicle detection system– Variable message signs– User identification– Automatic payment system– Enforcement

• Determine priority levels based on – Dynamic traffic condition, which is measured by

• Level of service (LOS)• Speed• Throughput

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TRB 2007

Priority Based HOV Operation Algorithm

• Algorithm– Define: HOV section:

• the segment of HOV lane from a HOV entry point to HOV exit point.

– HOV section speed• measured by detectors in the

section.– HOV speed prediction – SOV toll is assumed to be a

fixed dollar amount in the study

– Priority decision model• Algorithm implementation

– A plugin developed using Paramics API

– Priority Decision Model

Priority decision model

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TRB 2007

Evaluation Methodology

Perform Paramics simulation runs

Calibrate the micro- simulation network

Performance measures

Compare different scenarios

Control strategy

Build micro-simulation model

Evaluation scenarios

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TRB 2007

Study Site

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TRB 2007

Microscopic Simulation Model• Study network:

– Located in Orange county, California (freeways)– Including 18-mile I-5, 12-mile I-405, and 10-mile SR-55 freeways

• Simulation model:– Paramics, developed by Quadstone– Model inputs:

• network geometry, • driver behavior, • vehicle characteristics, • demand and • zones

• Simulation model calibration:– Based on a previous study

• Simulation Period:– Morning peak period (6:00 – 8:00)

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TRB 2007

Simulation Network

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TRB 2007

Scenario Design

• Two scenarios:– Baseline: HOV 2+ HOV lane

operation– Priority based HOV lane operation

• HOV lane changing – occurs only at existing egress and

ingress area• Performance Measures

– Overall network performance• Vehicle hours traveled (VHT)• Vehicle miles traveled (VMT)• Total passenger travel time • Average travel speed

– HOV lane performance• Average lane speed• LOS• Average lane flow

Vehicle groups Share of vehicles (%)

Bus 0.5

HOV 4+ (including vanpool)

1.0

HOV 3 3.5

HOV 2 11.2

Hybrid (0.3%) andLEV (0.5%)

0.8

SOV willing to pay toll

3.6

SOV 79.4

• Share of different types of vehicles

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TRB 2007

Overall Network Performance

0

10

20

30

40

50

60

70

80

Total Passengertravel time (hrs)*10^3

Average TravelSpeed (mph)

Vehicle-milestraveled (VMT)*10^4

Vehicle-hourstraveled (VHT)*10^3

Base Scenario Priority-based Scenario

- Priority based scenario performs better in-terms of speed & travel time

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TRB 2007

HOV Lane Speeds on Different Corridors

46

48

50

52

54

56

58

60

62

64

I-405N I-405S I-5N I-5S I-55N I-55S

Freeways

Sp

eed

(m

ph

)

Base Scenario Priority-based Scenario

- HOV lane speed in priority based scenario has reduced marginally due to increase in flow

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TRB 2007

Mainline Speeds on Different Corridors

0

10

20

30

40

50

60

70

I-405N I-405S I-5N I-5S I-55N I-55S

Freeways

Sp

eed

(m

ph

)

Base Scenario Priority-based Scenario

- Mainline speed has increased in priority-based scenarios due to shift of SOV demand to HOV lanes

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TRB 2007

HOV Flows on Different Corridors

0

200

400

600

800

1000

1200

1400

1600

I-405N I-405S I-5N I-5S I-55N I-55S

Freeways

Vo

lum

e

Base Scenario Priority-based Scenario

- HOV flow throughput has increased in priority-based scenarios

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TRB 2007

Level of Service on HOV Lanes

0

10

20

30

40

50

60

70

LOS A LOS B LOS C LOS D

Perc

en

tag

e

Base Scenario Priority-based Scenario

- Priority based operation has reduced LOS since it has moved more vehicles to HOV lanes

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TRB 2007

Time Spent in Different Priority Levels

Freeways 

Prioritylevel 1

(%)

Prioritylevel 2

(%)

Prioritylevel 3

(%)

Prioritylevel 4

(%)

Prioritylevel 5

(%)

Prioritylevel 6

(%)

I-405N 79 11 7 2 1 0

I-405S 74 13 5 5 3 0

I-5N 74 12 8 4 2 0

I-5S 78 9 6 4 3 0

SR-55N 99 1 0 0 0 0

SR-55S 76 9 6 5 4 0

Total 80 9.2 5.3 3.3 2.2 0

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TRB 2007

Findings

• The proposed priority based HOV lane operation performs better:

– Total passenger travel time is improved by 10.3%– Travel speed is improved by 6.78%– HOV lane speed reduces marginally due to increase in flow– Mainline speed increases due to shift of SOV demand to HOV

lanes– HOV flow throughput increases– LOS is improved since more vehicles are moved to HOV lanes

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TRB 2007

Possible System Solution• Possible system components

– FasTrack • Electronic toll collection system used in California• Each vehicle has a transponder for user identification and payment

– CMS • Placed at proper locations• Showing current priority levels

– Algorithm for determining priority levels• Tradeoff between HOV lane performance & throughput

– Easy to be implemented in a barrier-separate HOV system• e.g. in Southern California

– Enforcement• Camera to identify priority evaders

• Keys to success – Technology– System reliability– Enforcement– Education

• Increase the awareness of the concept to users