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Agenda

National issues in traffic signal

control

Every Day Counts and Adaptive

Signal Control Technologies

Existing Algorithms

ASCT Implementation in Puerto Rico

Corridor Optimization with ACS-Lite

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2007 National Traffic Signal Report Card

Improper traffic signal timing

accounts for 5-10% of all traffic delay

on major roadways

Incorrectly functioning traffic sensors

do not serve all vehicles and

pedestrians equitably.

Drivers must wait through more than

one green signal at an intersection,

causing long queues and clogged

intersections.

Report Card Findings

Topic Area Existing conditions / problems

Management

Score: D-

• Philosophy for signal operation not documented or shared

• Annual reviews of major roadways are rarely conducted

• No established business plan for transportation operations

with clearly defined performance measures and goals

Signal Operation in

Coordinated

Systems

Score: D

• Traffic signal timing is rarely reviewed

• Signal technicians are not current on the use of modern

software

• Timing plans are not in place for emergencies and special

events

Signal Timing

Practices Score: C

• Intersection operations are infrequently checked in the field

to accommodate changing traffic conditions.

Traffic Monitoring &

Data Collection

Score: F

• Real-time traffic data are seldom available to the traveling

public for information and route planning

• Few, if any, quality checks for traffic monitoring and

collection systems

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veh

icle

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PEAK 15 Min

Opportunities to Improve Traditional

Traffic Signal Timing

Traditional signal timing process emerged

between 1940’ss & 1960’s

Limited signal timing plans

Variable & unpredictable traffic conditions

Every Day Counts “Every Day Counts is designed to identify and deploy

innovation aimed at shortening project delivery, enhancing

the safety of roadways, and protecting the environment”

Víctor Méndez, FHWA Administrator

Every Day Counts

Make FHWA a greener Agency and reduce their

carbon footprint

Accelerating Technology and Innovation

Deployment

Warm Mix Asphalt

Prefabricated Bridge Elements and Systems

Adaptive Signal Control Technology

Safety Edge

Geosynthetic Reinforced Soil

Shortening Project Delivery

Shortening Project Delivery Toolkit

Accelerated Project Delivery

Methods Adaptive Signal

Control Technology

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Adaptive Signal Control Technology

What is ASCT?

Sensors monitor traffic

Software evaluates

performance

Timing updated if necessary

Process repeats

What is ASCT?

Sensors monitor traffic

Software compares to baseline timing plan

Timing change if necessary

Process repeats

Sensors

•Type

•Placement

•Effective

•Well-maintained

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What is ASCT?

Sensors monitor traffic

Software compares to baseline timing plan

Timing change if necessary

Process repeats

Evaluate Performance

•Data

•Timing Parameters

•Algorithms & Models

•Frequency of Analysis

What is ASCT?

Sensors monitor traffic

Software compares to baseline timing plan

Timing Updates if necessary

Process repeats

Update Timing

•Uncongested

•Splits

•Offset

•Cycle PM Peak Period Demand

250

300

350

400

450

500

3:0

0 - 3:1

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5 - 6:3

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6:4

5 - 7:0

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Time

De

ma

nd

(V

PH

) SB

NBLT

WBLT

WBEB

NB

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What is ASCT?

Sensors monitor traffic

Software compares to baseline timing plan

Timing change if necessary

Process repeats

Continuous

Monitoring

•24/7

•Weekdays, Weekends

•Holidays

•Special Events

•Incidents

Implementation Goals for

Adaptive Signal Control Technologies

Goal 1

By December 2011, ASCT will

be comprehensively evaluated

and demonstrated to

underscore its opportunities

and benefits

Goal 2

By December 2012, ASCT /

EDC tools will be used by 40

agencies

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EXISTING ALGORITHMS

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Existing Algorithms

SCATS

ACS Lite

RHODES

SCOOT

OPAC

InSync Prediction Generators

Prediction Generators

Prediction Generators

Prediction Receiver

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System Requirements

Algorithm Controller type Detection Required

Field /Central Based

Algorithm

Field Processor Required

ACS Lite Various legacy controllers/cabiets

Existing stop bar detection by phase. Prefer one or more advance detectors per coordinated phase

Field or central

Yes

SCATS SCATS firmware on EPAC M50 and 2070

Stop bar only by lane Central No

SCOOT SEPAC firmware on EPAC M50 and 2070

stop bar and upstream detection

Central No

RHODES Siemens NextPhase 1.7.6c-2070

stop bar and upstream detection

Field Yes

OPAC Econolite ASC2, ASC3; Other NTCIP controllers on way

stop bar and upstream detection

Field or central

Yes

InSync Various - can work with most controller firmware

Video stop bar only Field Yes

Cost Comparison

Algorithm Detection cost

Aditional hardware

cost

Average software

developer cost

Average total cost per

intersection

ACS Lite $35,000 $0 $4,500 $39,500

SCATS $20,000 $0 $17,000 $37,000

SCOOT $50,000 $0 $20,000 $70,000

RHODES $50,000 $50,000 $50,000 $150,000

OPAC $50,000 $1,200 $3,000 $54,200

InSync N/A N/A N/A $78,000

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ASCT Deployment Status

SCATS

SCOOT

ACSLite

InSync

RHODES

OPAC

LA ATCS

State with Active ASCT

State with Pending ASCT

Traffic Signal Modernization Project and

Adaptive Signal Control in Puerto Rico

Update traffic signal equipment with Econolite ASC/3

NEMA TS2/NTCIP Actuated Controllers

Replacement of wire detection loops with Autoscope

Rack Vision Terra video detection system

Installation of radar sensors for traffic data collection

(volume, vehicle classification, speeds) in segments

Installation of video cameras for traffic and incident

monitoring

Installation of wireless communication infrastructure in

PR-2 corridor

Establish a local Traffic Management Center at

Mayaguez HTA Regional Office 19

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Econolite Signal Control

Equipment

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Autoscope Rack Vision Terra

Video Detection System

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Traffic Monitoring, Data Collection

and Communication Equipment

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MMA TMC and

Centracs Signal Management System

Provides a platform

for monitoring and

control of all signals

in the corridor.

ASCT can be

incorporated

to optimize signal

cycles and offsets.

Provides reports of flow

by lane in different

periods of time, vehicle

type, lane utilization and

space-time diagrams.

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Typical ACS Lite System

CORRIDOR OPTIMIZATION WITH

ACS-LITE

1. Split tuning algorithm

2. Offset tuning algorithm

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Collect Data

1. SPLIT TUNING ALGORITHM

Ø3

Ø7

Ø4

Ø8

Ø4

Ø7

Ø3

Ø3 Ø8

Ø5

Ø2

Ø7 Ø4

Ø1

Ø6

Ø5

Ø2

Ø5

Ø2

Correlate data to signal

phasing

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Averaging

Ø3 Cycle 1

Ø3 Cycle 2

Ø3 Cycle n-1

Ø3 Cycle n

Ø3 Phase

Utilization

Perform Analysis

Ø3 Ø8

Ø5

Ø2

Ø7 Ø4

Ø1

Ø6

Implement phase split

adjustments

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Volume and occupancy data is collected by

the advanced detectors usually 250 feet or

more upstream of the stop bar.

Collect data from

advance detectors

on coordinated

approaches

2. OFFSET TUNING ALGORITHM

Phase State

Volume

Occupancy

Green Interval

Vehicles arriving during

yellow and red intervals

Statistical flow profile using the volume

and occupancy data.

Develop a Statistical Flow Profile

correlated to the phase state

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Phase State

Volume

Occupancy

Green Interval

Red Arrow points out vehicles arriving

before the start of green. Shifting the

offset to the left will match the green

interval to a greater percentage of arrivals.

Perform analysis to capture the most

arriving flow during the green interval

Phase State

Volume

Occupancy

Green Interval

Implement offset adjustment

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ACS-Lite Idaho Case Study

• US-95 section in Coeur d’Alene,

Idaho with four signalized

intersections

• Evaluation conducted using PM

peak traffic conditions

• Traffic volumes, turning

movements and network

geometry information were taken

from an existing Synchro model

• Signal timing plans were

extracted from field controllers

Corridor Travel Time Comparison

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ACS-Lite Fulton Co. Case Study

Cascade Road section in

Atlanta, GA with 5 signalized

intersections

Deployment of ACS-Lite

included:

Upgrade controller firmware

Convert controller database

Set up detectors

System Integration Page 36

Side Street Queue Length Comparison

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ACS-Lite Morgantown, VA Case Study

Highway corridor with 19

signalized intersections

Vehicle counts were obtained

from 14 hour field

observations

Three TOD timing plans were

developed in Synchro

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Average Delay Comparison

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Corridor Travel Times

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Arrivals on Green w/o ACS-Lite

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Arrivals on Green w/ ACS-Lite

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Conclusions

Opportunities for improvements in traffic signal

operations with ACST are

Non-saturated corridors

Irregular traffic patterns / diverge from simulated

conditions

Improvements in travel time and arrivals on green,

individual intersection delay might increase

Corridor selection guidelines for ASCT

implementation are not developed

Issues with high left-turn movements and

pedestrian flows & preemption operation

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References

FHWA. 2010. Every Day Counts Summit

Presentations. Atlanta, GA.

Transpo Group. 2007. US-95 ACS-Lite System

Evaluation. Idaho.

Wang, J. et al. Evaluation of ACS Lite Adaptive

Control using Sensys Arterial Travel Time Data

Day, C. et al. 2011. Adaptive Signal Control

Performance Measures: A Central System-in-the-

Loop Simulation Case Study.

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