Transit Signal Priority Evaluation and Performance Measures

Miguel A. FigliozziProfessor Civil and Environmental EngineeringPortland State University

NITC Webinar - October 26, 2016

Background—Transit Signal Priority

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Transit signal priority (TSP)* is the process of:- detecting transit vehicles approaching signalized

intersections and- adjusting the signal phasing in real time to reduce

transit delay

*Furth, P. G., and T. H. J. Muller. Conditional Bus Priority at Signalized Intersections: Better Service with Less Traffic Disruption.

In Transportation Research Record: Journal of the Transportation Research Board, No. 1731, TRB, National Research Council, Washington, D.C., 2000, pp. 23–30.

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TSP Elements

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(a) An onboard priority request generator

(b) A detection system that receives the priority request and informs the traffic controller

(c) A priority control strategy at the signal controller

Background—Transit Signal Priority

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Why TSP ?

Benefits*

- Improve transit reliability- Allow late bus recovery - Speed improvements?- TSP is relatively inexpensive and “easily

implemented”

*Albright, E., & Figliozzi, M. (2012). Factors influencing effectiveness of transit signal priority and late-bus recovery at signalized-intersection level. Transportation Research Record: Journal of the Transportation Research Board, (2311), 186-194.

Evaluation? Not so easy…

Background—Transit Signal Priority

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Evaluation methods

• Analytic: Lin (2002); Abdy & Hellinga (2011)

• Simulation: Furth & Muller (2000); Dion et al. (2004)

• Empirical: Kimpel et al. (2005); Albright & Figliozzi (2012)

Performance measures

• Bus travel time

• Schedule adherence

• Headway variability

• Delay for other vehicles

• Lack of effectiveness and efficiency performance

Pre-install

Before / after, using bus data and at the corridor level

Not a comprehensive list !

Why another study?

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Evaluation methods

• Real-world data

• Several intersections

• Integration of:

– bus data location with

– signal timing and phases

Performance measures

• At the intersection level

• New PMs to measure TSP effectiveness and

efficiency

• Comparison of early green (EG) and green

extension (GE) strategies

Study Corridor

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21st 26th 33rd 39th 42nd 50th 52nd 65th 69th 71st, 72nd 82ndMilwaukie

12 SCATS signals

SE Powell Blvd.

Bus Route 9

Bus Route 66

Near-side: 26th EB26th WB

33rd EB 42nd EB43rd WB

72nd EB

Far-side: 50th EB50th WB33rd WB

39th EB39th WB 72nd WB

52nd EB52nd WB

65th EB65th WB

69th EB 71st EB

Far-side (12)

Near-side (6)Stop-to-stop segment

Bus stop-to-stop segments

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6 near-side segments

12 far-side segments

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TSP in our case study

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Green extensionEarly Green

Kamila Widulinski and Matthew Lapointe (2013)

TSP request is sent when: 1) on-route,2) doors are closed, and3) >30 seconds late.

(a) An onboard priority request generator

(b) A detection system that receives the priority request and informs the traffic controller

(c) A priority control strategy at the signal controller determines whether to grant a TSP phase, which TSP phase shouldbe granted, and when the TSP phase should start and end

SCATS: adaptive traffic control

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0

20

40

60

80

100

120

140

E W E W E W E W E W E W E W E W E W E W E W E W

MKE 21st 26th 33rd 39th 42nd 50th 52nd 65th 69th 71st 72nd

Seco

nd

s

Intersections / Directions

Median Cycle Length, Green phase and red phase duration

Red

Green

Data Integration

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Bus ALV/APC Database

SCATS Vehicle Counts

Database

SCATS Signal Phase Log Database

Bus Stop-to-Stop Trip Database

TSP Performance

Evaluation

Geometry, trajectories

VERY DIFFICULT !!!

TSP Phases

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• An early green phase truncates a red phase and begins the green phase early to help transit vehicles begin moving early

• A green extension phase extends a green phase to speed bus passage through an intersection before the signal turns red

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EG Phase: trajectories and probabilities

𝑑1

Arrival time

Departure time

𝑅𝑗𝑠

𝑅𝑗𝑒 = 𝐸𝐺𝑗

𝑠

𝑎𝑡𝑖

𝑑𝑡𝑖

𝑅𝑗+1𝑠 𝑅𝑗+1

𝑒

𝑣𝑚𝑎𝑥

𝑑2 𝑣𝑚𝑎𝑥𝑡𝑙𝑡𝑟

𝐸𝐺𝑗𝑒

EB Mke_21st

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0

EB 26th

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0EB 33rd

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0

EB 39th

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0

EB 42nd

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0

EB 50th

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0

EB 52nd

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0

EB 65th

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0

EB 69th

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0

EB 71st

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0EB 72nd

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0

WB 21st_Mke

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0

WB 26th

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0

WB 33rd

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0

WB 39th

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0

WB 42nd

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0

WB 50th

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0

WB 52nd

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0WB 65th

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0

WB 71st_69th

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0

WB 72nd

speed (mph)

Density

0 5 15 25 35

0.0

00.1

00.2

0

am

We know bus times and locations before/after crossing the intersection We know signal timing and phases

We do not know bus arrival time at the intersection

GE Phase : trajectories and probabilities

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𝑑1

Arrival time

Departure time

𝑅𝑗𝑠 𝑅𝑗

𝑒

𝑎𝑡𝑖

𝑑𝑡𝑖

𝐺𝐸𝑗𝑒 = 𝑅𝑗+1

𝑠 = 𝑡𝑟

𝑅𝑗+1𝑒

𝑣𝑚𝑎𝑥

𝑑2𝑡𝑙

𝐺𝐸𝑗𝑠

Forensic work: many potential cases depending on the stop departure and arrival times, timing of the phases, and bus speed probability distribution

Research Objectives/Questions

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• Define performance measures

• Green extension (GE) vs. early green (EG)? Which one is more effective?

• Time savings tradeoffs: buses, passengers, main arterial, and cross streets

Proposed Performance Measures

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– TSP Frequency• Is TSP working properly?

– TSP Responsiveness • Are TSP phases granted after a request?

– TSP Timeliness • From the bus point of view

• What is the probability of benefiting from a TSP phase request?

• What is the expected time saved per request?

– TSP Efficiency • From the traffic signal system point of view

• What is the expected bus/passenger time saved per phase granted?

• Normalized to seconds per second of TSP phase duration

TSP Frequency

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0102030405060708090

26th 33rd 39th 42nd 50th 52nd 65th 69th 71st 72nd

Average number of bus trips per day

requested TSP did not request TSP

0102030405060708090

26th 33rd 39th 42nd 50th 52nd 65th 69th 71st 72nd

Average number of TSP phases per day

Green Extension (GE) Early Green (EG)

Is the system working?

Responsiveness: Actual Outcomes of TSP Requests

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0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

EB WB EB WB EB WB EB WB EB WB EB WB EB WB EB WB

39th 42nd 50th 52nd 65th 69th 71st 72nd

Neither GE nor EG EG Both GE and EG GE

near

near

near

Granted within a cycle

TSP Timeliness: GE

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a b cd

ne

ar

ne

ar

ne

ar

0%10%20%30%40%50%60%70%80%90%

100%

EB WB EB WB EB WB EB WB EB WB EB WB EB WB EB WB

39th 42nd 50th 52nd 65th 69th 71st 72nd

d: no GE a: late GE b: on time GE c: early GE

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TSP Timeliness: EG

a b cd

0%10%20%30%40%50%60%70%80%90%

100%

EB WB EB WB EB WB EB WB EB WB EB WB EB WB EB WB

39th 42nd 50th 52nd 65th 69th 71st 72nd

d: no EG a: late EG b: on time EG c: early EG

ne

ar

ne

ar

ne

ar

TSP Effectiveness

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0%10%20%30%40%50%60%70%80%90%

100%

EB WB EB WB EB WB EB WB EB WB EB WB EB WB EB WB

39th 42nd 50th 52nd 65th 69th 71st 72nd

on-time EG on-time EG on-time GE on-time GE

near

near

near

Probability that a bus requesting TSP will benefit from a TSP phase

Passengers: avg. time saved per TSP Request

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σ𝑖 𝑇𝑖𝑚𝑒 𝑠𝑎𝑣𝑖𝑛𝑔 𝑓𝑟𝑜𝑚 𝐺𝐸𝑖σ𝑖 𝑇𝑆𝑃 𝑟𝑒𝑞𝑢𝑒𝑠𝑡𝑖

σ𝑖 𝑇𝑖𝑚𝑒 𝑠𝑎𝑣𝑖𝑛𝑔 𝑓𝑟𝑜𝑚 𝐸𝐺𝑖σ𝑖 𝑇𝑆𝑃 𝑟𝑒𝑞𝑢𝑒𝑠𝑡𝑖

0

5

10

15

20

25

39th 42nd 50th 52nd 65th 69th 71st 72nd

seco

nd

sfrom GE from EG

i = intersection index

Y axis: average total passenger time savings per TSP request

Passengers: Avg. Time Saved per EG phase

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0

20

40

60

80

100

120

140

EB WB EB WB EB WB EB WB EB WB EB WB EB WB EB WB

39th 42nd 50th 52nd 65th 69th 71st 72nd

seco

nd

snear-side far-side

σ𝑗 𝑇𝑖𝑚𝑒 𝑠𝑎𝑣𝑖𝑛𝑔 𝑜𝑓 𝐸𝐺𝑗

σ𝑗 𝐸𝐺𝑗

Y axis: average total passenger time

per second of granted EG phase

Passengers: Avg. Time Saved per GE phase

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0

20

40

60

80

100

120

140

EB WB EB WB EB WB EB WB EB WB EB WB EB WB EB WB

39th 42nd 50th 52nd 65th 69th 71st 72nd

seco

nd

s

near-side far-side

σ𝑗 𝑇𝑖𝑚𝑒 𝑠𝑎𝑣𝑖𝑛𝑔 𝑜𝑓 𝐺𝐸𝑗

σ𝑗 𝐺𝐸𝑗

NOTE: same scale for the vertical axis

Y axis: average total passenger time

per second of granted GE phase

TSP Efficiency (Time Saving vs. Delay)

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TSP phase

Time savings for major street bus and traffic

Delays for vehicles on the minor street

Time savings for major street traffic

GE or EG

Minor streets delay is greatly affected by queue length at the time EG or GE is granted; this is especially important when cross streets have a significant traffic volume.

Summary of Findings

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Green extension • Too many late green extension phases• Overall time savings ≈ Delay

Early green • Overall time savings > Delay

TSP performance • Vary significantly across intersections• Opportunity: significant gap between actual

and ideal performance

Discussion

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• Findings from this study may be site-specific, but the methodology is transferable to other corridors/cities

• Proposed TSP performance measures can help identify problems/improvement opportunities

• Laborious and difficult data integration process

• Importance of synchronization and data accuracy (dealing with a few seconds)

Discussion

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• Reliable data transmission, accurate bus location, fast response from the controller

• Impacts of queuing, bus stop location, and signal detection/communication reliability (check in/out)

• Too many GE phases? Better location and data transfer technology may be needed for GE

• SCATS: what is the TSP logic?

• Glass half full or half empty?

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Acknowledgements

Steve Callas

David Crout

Willie Rotich

Peter Koonce

References

• Feng, W., Figliozzi, M., & Bertini, R. L. (2015). Empirical Evaluation of Transit Signal Priority: Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures. Transportation Research Record: Journal of the Transportation Research Board, (2488), 20-31.

• Albright, E., & Figliozzi, M. (2012). Factors influencing effectiveness of transit signal priority and late-bus recovery at signalized-intersection level. Transportation Research Record: Journal of the Transportation Research Board, (2311), 186-194.

• Feng, W. (2014). Analyses of bus travel time reliability and transit signal priority at the stop-to-stop segment level. Portland State University, PhD dissertation.

• Papers can be downloaded from: http://www.pdx.edu/transportation-lab/publications-by-area

• Report can be downloaded from: http://trec.pdx.edu/research/researcher/Figliozzi/4164/related/products

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Questions?