performance-based management of traffic signals

TRANSPORTATION RESEARCH BOARD

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Performance-Based Management of Traffic

SignalsMay 28, 2020

2:00-3:30 PM Eastern

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#TRBwebinar

Learning Objectives

#TRBwebinar

1. Identify intersections and systems that could benefit from performance-based operation

2. Identify traits of locations that have successfully installed performance-based systems

Anyone can measure signal performance.

And most do.

Why Automate?

1. Attract funding

Why Automate?

1. Attract funding2. Avoid costly assumptions

Why Automate?

1. Attract funding2. Avoid costly assumptions3. Buy time

Why Automate?

1. Attract funding2. Avoid costly assumptions3. Buy time4. Bonus: Look for trouble

Happy sleuthing!

NCHRP 03-122PERFORMANCE-BASED

MANAGEMENT OF TRAFFIC SIGNALS

TRB WEBINARALISON TANAKA, PE

ITS Section

Portland Bureau of Transportation

MAY 28, 2020

DECEMBER 2018

Signal performance measures profoundly change all aspects of traffic signal operations from planning to design and implementation through better-informed, data-driven decisions. This guidebook provides information to help agencies invest in signal performance measures as part of a comprehensive approach to performance-based management.

NCHRP PROJECT 03-122 2

FOCUS FOR THE GUIDEBOOK

DECEMBER 2018

CHAPTER 1. ROADMAP TO PERFORMANCE MEASURESIntroduction to signal performance measures, benefits, required investments, and the guidebook chapters.


DECEMBER 2018NCHRP PROJECT 03-122

FLOW OF INFORMATION

4

SOLVE PROBLEMS

FASTER

AUTOMATE ALERTS FOR PROACTIVE

MANAGEMENT

REDUCE MODELING NEEDS FOR EXISTING

CONDITIONS

IDENTIFY HIGH-PRIORITY

LOCATIONS

TRACK PROGRESS TOWARDS AGENCYGOALS

PRODUCE SHARABLE

REPORTS THAT SUMMARIZE

IMPACTS


SIGNAL PERFORMANCE MEASURE BENEFITS

5

Chapter

6

Chapter

5

Chapter

4

Chapters

2+3


IMPLEMENTING SIGNAL PERFORMANCE MEASURES

6

Select Performance

Measures

Procure Resources

Conduct System Needs

Gap Assessment

Determine

Implementation Scale

Integrate into Agency

Practice

Apply Performance

Measures

Verify System

Configure System5

8

7

6

1

4

3

2

DECEMBER 2018

CHAPTER 2. PERFORMANCE MEASURE SELECTIONAlign performance measures with agency goals, objectives, and methods of signal system management using the outcome-based process.


DECEMBER 2018

Results in signal timing that is based on the operating environment, users, user priorities by movement, and local operational objectives.


OUTCOME-BASED PROCESS

Communication Equipment Health

Detection Equipment Health

Vehicle Delay

Pedestrians

Bicycles

Safety

Vehicle Progression

Rail

Emergency Vehicles

Transit

TrucksOBJECTIVES

DECEMBER 2018NCHRP PROJECT 03-122 9

• Percent of movements with queues that exceed storage

• Percent of vehicles entering on red

• Number of conflicting movements


SAFETY

10

3INTERSECTION /

UNCOORDINATED TIMING

• 3.10 Estimated Queue Length

• 3.11 Oversaturation Severity Index

• 3.15 Estimated Pedestrian Conflicts

• 3.16 Yellow/Red Actuations

• 3.17 Red-Light-Running (RLR) Occurrences

AGGREGATED STATUS REPORT(S) INDIVIDUAL PERFORMANCE MEASURE(S)

45

SYSTEM / COORDINATED

TIMING

ADVANCED SYSTEMS AND APPLICATIONS

2DETECTION

1COMMUNICATION

EXAMPLE


ADDITIONAL RESOURCES

11

Pooled Fund Study Reports and Workshop

Performance Measures for

Traffic Signal Systems: An

Outcome-Oriented

Approach

Integrating Traffic Signal

Performance Measures into

Agency Business Processes

January 2016 ATSPM

Workshop Presentations

Indiana Traffic Signal Hi

Resolution Data Logger

Enumerations

High-Resolution Data Enumerations

Utah DOT Open Source Software

Utah Department of

Transportation ATSPM Website

FHWA Open Source

Application Development

Portal (OSADP) ATSPM Source

Code

Utah Department of

Transportation ATSPM GitHub

Development Website

NCHRP 3-90: Operation of Traffic Signals in

Oversaturated Conditions

Operation of Traffic Signal

Systems in Oversaturated

Conditions, Volume 1:

Practitioner Guidance

Operation of Traffic Signal

Systems in Oversaturated

Conditions, Volume 2: Final

Report

ATSPM Webinars FHWA EDC-4 ATSPM Website

AASHTO Innovation Initiative FHWA Every Day Counts

http://dx.doi.org/10.5703/1288284315333

http://dx.doi.org/10.5703/1288284316063

http://docs.lib.purdue.edu/atspmw/2016/Presentations/

http://dx.doi.org/10.4231/K4RN35SH

http://udottraffic.utah.gov/atspm/

https://www.itsforge.net/index.php/community/explore-applications#/30/133

https://github.com/udotdevelopment/ATSPM

http://dx.doi.org/10.17226/22290

http://dx.doi.org/10.17226/22289

http://aii.transportation.org/Pages/AutomatedTrafficSignalPerformanceMeasures.aspx

https://www.fhwa.dot.gov/innovation/everydaycounts/edc_4/atspm.cfm


ADDITIONAL RESOURCES

12

FHWA Benefits and Costs of Implementing

Automated Traffic Signal

Performance MeasuresUDOT ATSPM User Case Examples

BONUS!

http://udottraffic.utah.gov/ATSPM/Images/ATSPM_User%20Case%20Examples_Manual_20200128.pdf

DECEMBER 2018

CHAPTER 3. PERFORMANCE MEASURE DETAILSLearn about 26 signal performance measures – required inputs, resulting outputs, example applications, and additional references.


DECEMBER 2018

3.11 Oversaturation Severity Index

3.12 Pedestrian Volumes

3.13 Pedestrian Phase Actuation and Service

3.14 Estimated Pedestrian Delay

3.15 Estimated Pedestrian Conflicts

3.16 Yellow/Red Actuations

3.17 Red-Light-Running (RLR) Occurrences

3.18 Effective Cycle Length

3.19 Progression Quality

3.20 Purdue Coordination Diagram

3.21 Cyclic Flow Profile

3.22 Offset Adjustment Diagram

3.23 Travel Time and Average Speed

3.24 Time-Space Diagram

3.25 Preemption Details

3.26 Priority Details


PERFORMANCE MEASURES

3.1 Communication Status

3.2 Flash Status

3.3 Power Failures

3.4 Detection System Status

3.5 Vehicle Volumes

3.6 Phase Termination

3.7 Split Monitor

3.8 Split Failures

3.9 Estimated Vehicle Delay

3.10 Estimated Queue Length

ORGANIZATIONAL

OPERATIONS

DESIGN & CONSTRUCTION

PLANNING

MAINTENANCE

STAKEHOLDERS

• Identify when vehicles are arriving during the cycle (i.e. on green or red) for a particular phase or overlap at an intersection.

APPLICATIONS


COMMUNICATION

COORDINATED

UNCOORDINATED

DETECTION

ADVANCED

Shows individual vehicle arrival times relative to green intervals.

DESCRIPTION

EQUIPMENT HEALTH

PEDESTRIANS

VEHICLE PROGRESSION

VEHICLE DELAY

BICYCLES

TRANSIT

EMERGENCY VEHICLES

RAIL

TRUCKS

SAFETY

OBJECTIVES

CENTRAL SYSTEM LOW-RESOLUTION

CONTROLLER HIGH-RESOLUTION

VENDOR-SPECIFIC

DATA SOURCES

• Did offset adjustments improve progression for a particular approach at an intersection?

EXAMPLE USES

3.20 PURDUE COORDINATION DIAGRAM

AVI / AVL /SEGMENT SPEED

EXAMPLE

DECEMBER 2018

CHAPTER 4. SYSTEM NEEDS FOR PERFORMANCE MEASURESDetermine if resources need to be procured to achieve selected signal performance measures.


DECEMBER 2018

Determine if additional equipment and/or staff are needed to deploy desired signal performance measures, considering agency resources as well as those that may be shared with other agencies.


GAP ASSESSMENT

Controller High-Resolution Data

Central System Low-Resolution Data

Vendor-Specific Data

Automated Vehicle Identification (AVI) Data

Probe Vehicle Segment Speed Data

Automated Vehicle Location (AVL) Data

Connected Vehicle (CV) Data

DATASOURCES


• Because of the large amount of data, system management may be challenging.

TIMESTAMP EVENT CODE PARAMETER DESCRIPTION

02/15/17 12:01:16.0 8 4 Phase 4 Begin Yellow Clearance

02/15/17 12:01:16.0 8 8 Phase 8 Begin Yellow Clearance

02/15/17 12:01:19.4 81 9 Detector 9 Off

02/15/17 12:01:19.5 10 4 Phase 4 Begin Red Clearance

02/15/17 12:01:19.5 10 8 Phase 8 Begin Red Clearance

02/15/17 12:01:20.0 1 2 Phase 2 Begin Green

02/15/17 12:01:20.0 1 6 Phase 6 Begin Green

02/15/17 12:01:25.5 82 19 Detector 19 On

02/15/17 12:01:28.0 81 19 Detector 19 Off

02/15/17 12:01:29.3 82 9 Detector 9 On

CHALLENGES

EXAMPLE DATA: 1/10-SECOND ENUMERATIONS


CONTROLLER HIGH-RESOLUTION DATA

19

INTERNAL

EXTERNAL

Timestamped “events” (e.g., detector inputs and signal display outputs) recorded by the controller at 1/10-second resolution.

DESCRIPTION

• Highly-detailed records allow a wide variety of signal performance measures to be calculated.

CAPABILITIES

EXAMPLE


ATSPM SYSTEM COMPONENTS

20

COMMUNICATION DETECTION DATA LOGGING DATA STORAGE SOFTWARE

High-Resolution Data

Other Data Source

Hardware

Cloud

Operating System

Software

Database Software

ATSPM System Software

Central System Software


DETECTION

21

Equipment used to detect presence of roadway users required for many measures.

DESCRIPTION• Distance from the stop bar (i.e. advance,

stop bar, past the stop bar)

• Type of wiring (i.e. lane-by-lane, multi-lane)

• Type of detection (i.e. presence, count)

• Filtering options (e.g., speed settings)

• Detector channel mapping

CONSIDERATIONS• Stop bar presence

• Stop bar count

• Advance

• Automated Vehicle Identification (AVI)

• Automated Vehicle Location (AVL)

• Pedestrian

• Speed

OPTIONS

EXAMPLE

DECEMBER 2018

CHAPTER 5. IMPLEMENTATION OF PERFORMANCE MEASURESProgram intersections, verify the ATSPM system is reporting accurate information, and use reports to make signal timing and maintenance adjustments.



INTERSECTION CONFIGURATION REQUIREMENTS

23

Signal ID Number (e.g., IP address)

Controller Controller Type

Firmware Version

Approach Northbound

Southbound

Westbound

Eastbound

Phase Number (e.g., Phases 1-8)

Channel Number (e.g., Channels 1-96)

Type

Stop Bar Presence

Stop Bar Count

Advance

AVI/AVL

Pedestrian

Speed

Location

(Advance Only)

Distance from stop bar (e.g., 400 feet)

Speed on approach (e.g., 40 mph)

Lane Number

Left 1, 2, n

Left-Thru 1, 2, n

Thru 1, 2, n

Thru-Right 1, 2, n

Right 1, 2, n

Bicycle 1, 2, n

DATA LOGGING DETECTION

VERIFICATION

DECEMBER 2018

Data Availability

Timestamps

Intersection Configuration

Detector Configuration

Data Verification


Before time zone adjustment Plan 1 shown starting at 1:00 AM because data is recorded using UTC

Force-offs (indicative of coordination) shown starting at 1:00 AM

After time zone adjustment Timestamps adjusted to local time zone so Plan 1 shown starting at 6:00 AM

Force-offs (indicative of coordination) shown starting at 6:00 AM


TIMESTAMPS

25

Data is not being reported at the correct times.

POTENTIAL ISSUE• Enumerations timestamped

using Coordinated Universal Time (UTC).

• Daylight savings time is not enabled.

POTENTIAL CAUSE EXAMPLE: DATA REPORTED AT CORRECT TIMES?

Time (Hour of Day)

Ph

ase

Nu

mb

er

Time (Hour of Day)

Ph

ase

Nu

mb

er

EXAMPLE

DECEMBER 2018

5.5.8 Time-of-Day (TOD) Plans

5.6.1 Cycle Length

5.6.2 Splits

5.6.3 Offsets

5.7.1 Advanced Signal Systems

5.7.2 Preferential Treatment

5.8.1 Communication

5.8.2 Signal Cabinet Equipment

5.8.3 Vehicle Detection

5.8.4 Pedestrian Detection


VALIDATION

5.5.1 Yellow Change

5.5.2 Red Clearance

5.5.3 Minimum Green

5.5.4 Maximum Green

5.5.5 Passage Time

5.5.6 Pedestrian Intervals

5.5.7 Recalls

Identify high max-outs during low-volume periods


5.8.3 VEHICLE DETECTION

27

• Alarms

• Phase termination

• Outage locations

• Equipment type and age

CONSIDERATIONS EXAMPLE3.1 COMMUNICATION STATUS3.2 FLASH STATUS3.3 POWER FAILURES3.4 DETECTION SYSTEM STATUS3.5 VEHICLE VOLUMES3.6 PHASE TERMINATION3.7 SPLIT MONITOR3.8 SPLIT FAILURES3.9 ESTIMATED VEHICLE DELAY3.10 ESTIMATED QUEUE LENGTH3.11 OVERSATURATION SEVERITY INDEX3.12 PEDESTRIAN VOLUMES3.13 PEDESTRIAN PHASE ACTUATION AND SERVICE3.14 ESTIMATED PEDESTRIAN DELAY3.15 ESTIMATED PEDESTRIAN CONFLICTS3.16 YELLOW/RED ACTUATIONS3.17 RED-LIGHT-RUNNING (RLR) OCCURRENCES3.18 EFFECTIVE CYCLE LENGTH3.19 PROGRESSION QUALITY3.20 PURDUE COORDINATION DIAGRAM3.21 CYCLIC FLOW PROFILE3.22 OFFSET ADJUSTMENT DIAGRAM3.23 TRAVEL TIME AND AVERAGE SPEED3.24 TIME-SPACE DIAGRAM3.25 PREEMPTION DETAILS3.26 PRIORITY DETAILS

PERFORMANCE MEASURES

4.1 Detection

STM2 REFERENCE

High number of max-outs overnightIdentify detectors not reporting volumes

Phase 6 gapping out after bad detector splice fixed

Lane 3 detector not reporting volumes until bad splice fixed

Time (Hour of Day)

Ph

ase

Nu

mb

er

Time (Hour of Day)

Vo

lum

e (

Ve

hic

les

Pe

r H

ou

r)

EXAMPLE

PREDICTIVE TOOLS AUTOMATED ALERTS AGGREGATED REPORTS

Use high-resolution data to develop

predictive models (e.g., Purdue Link

Pivot Analysis)

Automatically flag issues and alert

technicians to issues and

inefficiencies

Identify “hot spots,” compare to

historical data, and produce shareable

reports

Data EntryIntersections with a low number of records in the database

Max-OutPhases with a high number of max-outs during low-volume periods

Pedestrian CallPhases with a high number of pedestrian actuations during low-volume periods

Detector CountAdvance detectors reporting low volumes during high-volume periods

Force-OffPhases with a high number of force-offs during low-volume periods


REPORTING ADVANCEMENTS

28

108-second offset adjustment recommended based on

maximum arrivals on green

NBL Ph5(6) experiencing highest number of split

failures throughout the day

DECEMBER 2018

CHAPTER 6. INTEGRATION INTO AGENCY PRACTICEStrategies to fully integrate signal performance measures into agency management practices, create collaboration opportunities between groups, share resources, and communicate benefits.


DECEMBER 2018

Defines “basic service” as it relates to the traffic signal system, demonstrates needs, identifies how well expectations are being met, and prioritizes investments.


TRAFFIC SIGNAL MANAGEMENT

PLAN (TSMP)

DECEMBER 2018

Organizational framework used to describe the level of management formality and optimization, ranging from ad-hoc actions to managed, optimized procedures.


CAPABILITY MATURITY

MODEL (CMM)

ORGANIZATIONALTRANSPORTATION

PLANNING

DESIGN AND

CONSTRUCTION

TRAFFIC

OPERATIONSMAINTENANCE

Performance-

based prioritization

Shareable reports

Quantitative

tracking

Agency policies

and standards

Inter-agency

collaboration

IT staff

Model validation

Evaluate benefit /

cost for programs

and grants

Compare

equipment types

Evaluate

maintenance of

traffic (MOT)

Continuously-

available data for

less modeling

Automated alerts

for operational

issues

Prioritize signal

retiming

Confirm public

service requests

Continuously-

available data to

support

preventative

maintenance

Automated alerts

for maintenance

issues

Prioritize

improvements


IMPACT TO AGENCY ACTIVITIES

32

Performance-Based Management of Traffic Signals

Mark Taylor, P.E., PTOE

UDOT Traffic Signal Operations Engineer

Experiences from Agencies that Have Deployed Practices

Photo Courtesy: Utah DOT

Evolution of Traffic Signal Performance MeasuresElectromechanical

Firmware – Data Loggers - ATSPMs

Photo Courtesy: INDOT & PURDUE University

Photo Courtesy: Econolite & New York City

Serial Inputs Test Location – Purdue

Image Courtesy: Wavetronix

Automated Traffic Signal Performance Measures Basic Concept

- 1/10th sec. data - Signal controller - Intersection, Corridor, City, System

Automated Data Collection

Useful Information about Performance

Why model or estimate what you can now measure and automate?

TimestampEvent Code

Event Parameter

5/19/2020 3:08:44.8 9 25/19/2020 3:08:44.8 9 65/19/2020 3:08:46.6 1 35/19/2020 3:08:46.6 1 85/19/2020 3:08:46.6 11 25/19/2020 3:08:46.6 11 65/19/2020 3:08:51.4 82 595/19/2020 3:08:51.6 81 59

End of Yellow Ø2 & Ø6

Begin of Green Ø3 & Ø8

End of Red Clearance Ø 2 & Ø6

Detector On Ch. 59

Detector Off Ch. 59

Automated Traffic Signal Performance Measures

Image Courtesy: Utah DOT - https://udottraffic.utah.gov/atspm

Purdue Coordination Diagram

Turning Movement Counts

Purdue Split Failure

Purdue Phase Termination

Image Courtesy: Utah DOT

Various Performance Measures from ATSPMs

Timing and Actuation

Pedestrian Delay

Percent of Signals Communicating Example: Utah(That Should be Communicating)


Power Failures Example: Indiana(Logged over six months for nine corridors)

Image Courtesy: NCHRP Project 03-122 & Purdue University

0

1300

100

400

800

500600700

1100

9001000

300

1200

200

Throughput Volume Example: Pennsylvania

Volume Peak~1200 VPH

12PM

Flow

Rat

e(V

PH)

Free Plan 2Plan 1

7AM 7PM 12PM 7PM

Volume Peak~1250 VPH

Plan 1 Free Plan 2

Flow

Rat

e(V

PH)

7AMImage Courtesy: Pennsylvania DOT

BEFORE RETIMING AFTER RETIMING

Purdue Coordination Diagram Example: VirginiaBefore Offset Adjustment

After Offset Adjustment

Image Courtesy: NCHRP Project 03-122 & Virginia DOT

Time-of-Day vs Peer-to-Peer & Custom Logic Example: Utah (Purdue Coordination Diagram)

Time-of-Day

Peer-to-Peer & Custom Logic

85% Arrival on GreenCycle Length 90 s or 120 s

Cycle Length varies 45 s to 120 s88% Arrival on Green

Mountain View & 12600 South WB – Wed. September 2, 2015

Mountain View & 12600 South WB – Tues. October 20, 2015


Initial Percent Arrival on Green

Increase in Percent Arrival on Green

Decrease in Percent Arrival on Green

Corridor Midday Arrival on Green

74%

7%

Progression Quality Example: Utah(Offset Adjustment Impact on Percent on Green -POG)

Image Courtesy: NCHRP Project 03-122 & Utah DOT

Image Courtesy: Georgia DOT

Purdue Split Failure Example 9:00 AM to 7:00 PM: Georgia

Before Condition§ 97 split failures

After Condition (green time increased 5-7 s)§ 55 split failures§ 43% reduction

Photo Courtesy: Google Maps; Image Courtesy: Utah DOT

Consideration for Pedestrian Delay: Example: Utah

8:

BEFORE: Uncoordinated

020

80100120

6040

Delay (sec) AFTER: Coordinated

7:15 am7:30 am 7:45 am 8:00 am7:15 am 7:30 am 7:45 am

Ave. Delay: 38 sec.Ave. Delay: 48 sec.

87 7

ATSPM Daily System Health Alerts – Utah (Year 2019)No ATSPM Data: identifies signals with < 500 records in the database between midnight and midnight the previous day.

1Too Many Max Outs: identifies phases with > 90% max outs in at least 50 activations between 1 a.m. and 5 a.m.

2Too Many Force Offs: identifies phases with > 90% force offs in at least 50 activations between 1 a.m. and 5 a.m.

3Too Many Ped Calls: identifies phases with > 200 pedestrian activations between 1 a.m. and 5 a.m.

4Low PCD Detector Count: identifies phases with PCD detectors with < 100 vehicles between 5 p.m. and 6 p.m. the previous day.

5

No ATSPM Data, 83, 11%

Too Many Force Offs, 17, 2%

Too Many Max Outs, 337, 45%

Low PCD Count, 163, 22%

Too Many Ped Calls, 148, 20%

ATSPM DETECTOR ISSUES - AUTOMATED

748 Detector Issues Identified and Corrected during Year 2019

Left Turn Gap Analysis Example: Georgia(If Using FYA, When to go from Protected/Permitted to Protected Only by TOD?)

Percent of Gap Tim

e > 7.4 SecondsN

umbe

r of G

aps

Time (Hours: Minutes of the Day)

Protected Only Phasing from 3:00 PM

to 7:00 PM?


Image Courtesy: Georgia GOT

System Wide Dashboards: Example: Georgia (April 2020)

Utah

Electronic Logbook for Traffic Signals & ITS - Utah

Why Use an Electronic Logbook?• Easier to retrieve, read, sort and analyze• Need a system to manage remote changes• Provide access to all agency programs • Improved management, security and accountability

Photo Courtesy: Utah DOT

Electronic Locks

Central Traffic Signal Management System

Optimizing Progression at Traffic Signals - Utah

ØTraditional Retiming: 3 to 5 Years

ØArtificial Intelligence / Machine Learning Retiming: Every Other Month

Photo Courtesy: Image purchased from istockphoto.com Image Courtesy: Utah DOT - Created by Avenue Consultants

Today’s Presenters#TRBwebinar

Darcy Bullock, PurdueUniversity

Alison Tanaka, Mark Taylor, Utah DOT Portland, OR DOT

Phil Rust, City of San Diego

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performance-based management of traffic signals

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