case studies: using signal performance metrics to optimize

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Case Studies: Using Signal Performance Metrics to Optimize Traffic Signal Operations March 6, 2018

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Page 1: Case Studies: Using Signal Performance Metrics to Optimize

Case Studies: Using Signal Performance Metrics to Optimize Traffic Signal OperationsMarch 6, 2018

Page 2: Case Studies: Using Signal Performance Metrics to Optimize
Page 3: Case Studies: Using Signal Performance Metrics to Optimize

WHAT ARE SPMs?

Traffic Signal Performance Measures

- Modernize traffic signal management

- Provide high-resolution data

- Support performance-based maintenance and ops

- Improve safety and efficiency

- Cut congestion and cost

Page 4: Case Studies: Using Signal Performance Metrics to Optimize

TRADITIONAL:● Complaint driven● Resource constrained● Reactive signal operations & maintenance● Improvement is project based, not continuous

AN EVOLUTION IN SIGNAL MANAGEMENT

RECOMMENDED:● Continuous Improvement● Measurement Driven● Proactively planning and management● Prove the impact of your work● Secure funds with data driven arguments

Page 5: Case Studies: Using Signal Performance Metrics to Optimize

BENEFITS OF PERFORMANCE MEASURES WHAT GETS MEASURED GETS DONE

High resolution data collection

Data analysis and performance report tools

Data-driven improvements

Page 6: Case Studies: Using Signal Performance Metrics to Optimize

BENEFITS OF SIGNAL PERFORMANCE MEASURES WHAT GETS MEASURED GETS DONE

High resolution data collection

Data analysis and performance report tools

Data-driven improvements

Page 7: Case Studies: Using Signal Performance Metrics to Optimize

PERCEIVED CHALLENGES

TECHNICAL LOGISTICS

“How do we get started?”

Communications Modern controllers & detectionData security Support from IT departmentImplementation consulting

I have to solve it all to try this!

ADOPTION

“How do we get started?”

Data isn’t accessible ExpensiveAnother tool I have to learn What do these graphs mean?I don’t have time to figure this out

How do I explain this to my boss?

Page 8: Case Studies: Using Signal Performance Metrics to Optimize

THE SMARTLINK STACK

Spectrum HardwareCommunicate data securelyUnlock data from infrastructureEnhance detection

Spectrum SignalsReceive traffic incident alerts Gain visibility of traffic networkIntegrate data with existing software

Spectrum Traffic InsightsMeasure traffic performancePrioritize resources Share data

Insights

Inform

Monitor

Communicate

Acquire

Page 9: Case Studies: Using Signal Performance Metrics to Optimize

THE FULL TRAFFIC PICTURE

1: Intersection ViewDetector and signal performance data at the intersection

2: Corridor ViewAggregate intersection data and augment with travel time data

3: Network ViewAggregate corridor data with maintenance details, origin destination analysis, computer vision and summary reports

Page 10: Case Studies: Using Signal Performance Metrics to Optimize

Improving Maintenance and Operations

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Maintenance & Operations

REGION OF WATERLOO

CHALLENGES:

● Rural railway crossing

● 22 minute commute each direction

● 37 Rail Preempt Threshold Exceeded in one year

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Maintenance & Operations

PRIOR TO MIOVISION:● Complaint driven ● Time consuming communication and resolution

WITH ATSPMs:● Minimum 75 hours saved (~2 person weeks/year)● Resolution at the click of a button to inform rail company● Fewer citizen complaints● Safer road

“With Spectrum you have streaming video and real-time alertscoming back to essentially do the fieldwork from the trafficmanagement center, and get issues cleared more quickly.”

Mark Liddell, Region of Waterloo Traffic Analyst

REGION OF WATERLOOREGION OF WATERLOOREGION OF WATERLOOREGION OF WATERLOO

Page 14: Case Studies: Using Signal Performance Metrics to Optimize

Improving Maintenance and Operations

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PIMA COUNTY

Maintenance & Operations

WEST INA ROAD CONSTRUCTION

● Construction at West Ina Rd and I-10

● On / Off Ramp closure expected for 24 months

● Goal: measure and manage impact on Ina Rd corridor

Page 16: Case Studies: Using Signal Performance Metrics to Optimize

W INA ROAD STUDY CORRIDOR

● 4 Intersections equipped with Miovision Spectrum along W Ina Rd ● Before / During / After data used to measure impact of closures and new timing plans

PIMA COUNTY CORRIDOR ANALYSIS OVERVIEWPIMA COUNTY

Page 17: Case Studies: Using Signal Performance Metrics to Optimize

TRAVEL PATTERN CHANGES

PIMA COUNTY CORRIDOR ANALYSIS OVERVIEW

● OD (Origin-Destination) changes before and after the interchange closure● Corridor length trips decreased significantly, but N La Cañada Dr and N La Cholla still used heavily

Feb 1st, 2016 May 4th, 2016

PIMA COUNTY

Page 18: Case Studies: Using Signal Performance Metrics to Optimize

N LA CAÑADA DR NB AND SB● Small effect of interchange closure on the number of split failures on the NB traffic ● Significant improvement after the signal retiming

SPLIT TREND ANALYSIS

BeforeClosure

AfterClosure

AfterRetiming

PIMA COUNTY

Page 19: Case Studies: Using Signal Performance Metrics to Optimize

EFFECTS ON PROGRESSION

● Significant improvement in progression after retiming on the NB movement using Arrivals on Red

After:

Before:

ARRIVALS ON REDPIMA COUNTY

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EFFECTS ON PROGRESSION

● Significant improvement in progression after retiming on the NB movement using Purdue Coordination

After:

Before:

PURDUE COORDINATION DIAGRAMPIMA COUNTY

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TRAVEL TIME

EFFECT ON TRAVEL TIME● Non-optimal cycles can increase the travel time/delay● A before and after travel time analysis reveals minimal impact of signal retiming on corridor travel time

After:

Before:

PIMA COUNTY

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Improving Traffic Performance

Page 23: Case Studies: Using Signal Performance Metrics to Optimize

SPECTRUM CAMERA360ENABLES DETECTION

● Detection is key to ATSPMs

● Leverage detection zones and computer vision for greater accuracy

● SmartView 360 fisheye camera provides split approach view

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SPECTRUM CAMERA360MULTI-MODAL STUDIES

● 24/7, 365 video analyzer product in cabinet

● On-demand TMC and classification studies with 95% accuracy (including ped and bike)

● Remote video monitoring and review

Page 25: Case Studies: Using Signal Performance Metrics to Optimize

THE PROBLEM:Eastbound Joy - Left Turn

- Queue failing to empty at afternoon rush hour- Causing a backup so far back that it blocks the thru traffic

Quick Case Study: City of DetroitCITY OF DETROIT

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Quickly identify top offending intersections on the Intersection Report Card

CITY OF DETROIT

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Requirements: Requires stopbar presence detection

OCCUPANCY RATIOa.k.a. Green Occupancy, Red Occupancy

SPLIT FAILURESa.k.a. Purdue Split Failure

Requirements: Requires stopbar presence detection

CITY OF DETROIT

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CITY OF DETROIT

Split Trend Analysis - Drilldown to analyze the problem

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THE SOLUTIONReallocate 3s of green time from the NB/SB movements to the EB/WB movements during the PM Peak

CITY OF DETROIT

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Verify change didn’t negatively impact other movements

CITY OF DETROIT

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Visually assess impact of changeBEFORE AFTER

CITY OF DETROIT

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The result…41.7% reduction in Split Failures at Intersection

CITY OF DETROIT

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MIOVISION ATSPM ADOPTION MODELProblem Discovery

Integration Planning

Procurement Support Implementation

Continuous Improvement

Translate challenges into requirements

Provide expertise on securing funding

Ensure deployment is timely & success

Continue to understand and innovate based on your evolving needs

▸ Problem discovery▸ Stakeholder involvement

▸ Technical planning document▸ Business case development

▸ Grant application writing▸ Technical specifications

▸ Project management▸ Detailed installation instructions

▸ Product discovery managers▸ Product roadmaps

Work to understand your challenges

MIO

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WH

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Provide technical details about existing infrastructure

Support grants applications or vying for internal funding

Access to relevant staff for installation and training

Feedback about how Miovision products can better meet your needs

Engagement from relevant stakeholders

WH

AT W

E AS

K O

F YO

U

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Thank you

Erin [email protected]