empirical evaluation of transit signal priority through fusion of heterogeneous transit and traffic...

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Empirical Evaluation of Transit Signal Priority Transportation Seminar March 6, 2015 Wei Feng, Chicago Transit Authority Miguel Figliozzi, Portland State University Robert Bertini, Cal Poly State Univ., San Luis Obispo (Doug Beghtel/The Oregonian)

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Page 1: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Empirical Evaluation of Transit Signal Priority

Transportation Seminar March 6, 2015

Wei Feng, Chicago Transit AuthorityMiguel Figliozzi, Portland State UniversityRobert Bertini, Cal Poly State Univ., San Luis Obispo

(Doug Beghtel/The Oregonian)

Page 2: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Background—Transit Signal Priority

2

PassiveActiveReal-time optimal

Green extensionEarly Green

Kamila Widulinski and Matthew Lapointe (2013)

2

Page 3: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Background—Transit Signal Priority

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 measures/evaluation

Pre-install

Before / after

3

Page 4: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Motivation

Unique set of complementary data sources

TriMet Bus AVL/APC data

City of PortlandSCATS signal phase log data

Intersection vehicle count data

SCATS: Sydney Coordinated Adaptive Traffic System

AVL: Automatic Vehicle LocationAPC: Automatic Passenger Count

4

Page 5: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Research Questions

Current TSP system in Portland:– Effectiveness and efficiency? – Time savings for buses vs. delay to cross street vehicles– Green extension vs. early green phases?– Near-side vs. far-side bus stops?– Any problems and improvement opportunities?

5

Page 6: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Study Corridor

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

6

Page 7: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Bus stop-to-stop segments

6 near-side segments

12 far-side segments

7

Page 8: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

SCATS Signals

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

nds

Intersections / Directions

Median Cycle Length, Green phase and red phase duration

Red

Green

8

Page 9: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Data Integration

Bus ALV/APC Database

SCATS Vehicle Count Database

SCATS Signal Phase Log Database

Bus Stop-to-Stop Trip Database

TSP Performance

Evaluation

9

Page 10: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Bus Stop-to-Stop Trip Attributes

• Bus departure/arrival time

• Passenger activities

• Signal phase start/end time

• Priority request

• Upstream/downstream distance

Input data

• Probability of arriving at

intersection in:

– Green

– Red

– Green extension

– Early green

• Signal delay

• Time savings

Output variables

10

Page 11: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Bus Time Saving (Early Green)

𝑑𝑑1

Arrival time

Departure time

𝑅𝑅𝑗𝑗𝑠𝑠

𝑅𝑅𝑗𝑗𝑒𝑒 = 𝐸𝐸𝐸𝐸𝑗𝑗𝑠𝑠

𝑎𝑎𝑎𝑎𝑖𝑖

𝑑𝑑𝑎𝑎𝑖𝑖

𝑅𝑅𝑗𝑗+1𝑠𝑠 𝑅𝑅𝑗𝑗+1𝑒𝑒

𝑣𝑣𝑚𝑚𝑚𝑚𝑚𝑚

𝑑𝑑2 𝑣𝑣𝑚𝑚𝑚𝑚𝑚𝑚𝑎𝑎𝑙𝑙𝑎𝑎𝑟𝑟

𝐸𝐸𝐸𝐸𝑗𝑗𝑒𝑒

EB 39th

speed (mph)

Den

sity

0 5 15 25 35

0.00

0.10

0.20

am

11

Page 12: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Bus Time Saving (Green Extension)

𝑑𝑑1

Arrival time

Departure time

𝑅𝑅𝑗𝑗𝑠𝑠 𝑅𝑅𝑗𝑗𝑒𝑒

𝑎𝑎𝑎𝑎𝑖𝑖

𝑑𝑑𝑎𝑎𝑖𝑖

𝐸𝐸𝐸𝐸𝑗𝑗𝑒𝑒 = 𝑅𝑅𝑗𝑗+1𝑠𝑠 = 𝑎𝑎𝑟𝑟

𝑅𝑅𝑗𝑗+1𝑒𝑒

𝑣𝑣𝑚𝑚𝑚𝑚𝑚𝑚

𝑑𝑑2 𝑎𝑎𝑙𝑙

𝐸𝐸𝐸𝐸𝑗𝑗𝑠𝑠

12

Page 13: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Key Performance Measures

– TSP Frequency

– TSP Effectiveness (for each TSP request)Probability of benefiting from a TSP phaseExpected time saving

– TSP Efficiency (for each TSP phase)Probability of being beneficial to a TSP requestExpected time saving per second of TSP phase duration

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Page 14: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

TSP Frequency

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)

14

Page 15: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

When A TSP Request Will Benefit from GE/EG

Benefit from Green Extension

Benefit from Early Green

Green

GE

Red-GE

Cycle

Green

Red-EG

EG

Cycle

15

Page 16: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Potential Results of A TSP Request

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 = Red/Cycle on-time EG = Red/Cycleon-time GE = GE/Cycle on-time GE = GE/Cycle

near

near

near

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Page 17: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Actual Outcomes of TSP Requests

TSP request

No TSP phase within the cycle

TSP phase within the cycle

GE

EG

Both GE and EG

Neither GE or EG

GE: Green ExtensionEG: Early Green

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Page 18: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Actual Outcomes of TSP Requests

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

18

Page 19: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

TSP Effectiveness

Bus trips that request TSP

Green extension

TSP request

No TSP phase within the cycle

TSP phase within the cycle

a b c

1 3

Early

On-time

Late3

1

a

b

c

Time saving

Effectiveness Benefit

GE or/and EG

2

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Page 20: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

TSP Request Outcomes for GE

a b cd

near

near

near

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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Page 21: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

TSP Request Outcomes for 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

near

near

near

21

Page 22: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Actual TSP Effectiveness

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

22

Page 23: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Ideal TSP Effectiveness

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 = Red/Cycle on-time EG = Red/Cycleon-time GE = GE/Cycle on-time GE = GE/Cycle

near

near

near

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Page 24: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Passenger Time Saving per TSP Request

∑𝑖𝑖 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 𝑠𝑠𝑎𝑎𝑣𝑣𝑇𝑇𝑠𝑠𝑠𝑠 𝑓𝑓𝑓𝑓𝑓𝑓𝑇𝑇 𝐸𝐸𝐸𝐸𝑖𝑖∑𝑖𝑖 𝑇𝑇𝑇𝑇𝑇𝑇 𝑓𝑓𝑇𝑇𝑟𝑟𝑟𝑟𝑇𝑇𝑠𝑠𝑎𝑎𝑖𝑖

∑𝑖𝑖 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 𝑠𝑠𝑎𝑎𝑣𝑣𝑇𝑇𝑠𝑠𝑠𝑠 𝑓𝑓𝑓𝑓𝑓𝑓𝑇𝑇 𝐸𝐸𝐸𝐸𝑖𝑖∑𝑖𝑖 𝑇𝑇𝑇𝑇𝑇𝑇 𝑓𝑓𝑇𝑇𝑟𝑟𝑟𝑟𝑇𝑇𝑠𝑠𝑎𝑎𝑖𝑖

0

5

10

15

20

25

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

seco

nds

from GE from EG

24

Page 25: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

TSP Phase Triggered by TSP Requests

TSP phase

No TSP request within the cycle

TSP request within the cycle

EB

WB

Both EB and WB

Neither EB or WB

GE or EG

25

Page 26: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

% of GEs Associated to TSP Requests From

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

100%

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

Neither EB nor WB EB EB and WB WB

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Page 27: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

% of EGs Associated to TSP Requests From

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

100%

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

Neither EB nor WB EB EB and WB WB

27

Page 28: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

TSP Efficiency

TSP phase

No TSP request within the cycle

TSP request within the cycle

a b c

1 2 3

Early

On-time

Late3

2

a

b

c

Time saving

Efficiency Benefit

GE or EG

Bus trips that request TSP

Green extension

28

Page 29: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Actual Green Extension Efficiency

a b cd

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

100%

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

out of cycle c: early b: on-time a: late

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Page 30: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Actual Early Green Efficiency

a b cd

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

100%

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

out of cycle c: early b: on-time a: late

30

Page 31: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

TSP Efficiency (Time Saving vs. Delay)

TSP phase

Major street bus and other vehicles time saving

Minor street other vehicles delay

Major street other vehicles time saving

GE or EG

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Page 32: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Bus Passenger Time Saving per EG

020406080

100120140

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

nds

near-side far-side

∑𝑗𝑗 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 𝑠𝑠𝑎𝑎𝑣𝑣𝑇𝑇𝑠𝑠𝑠𝑠 𝑓𝑓𝑓𝑓 𝐸𝐸𝐸𝐸𝑗𝑗∑𝑗𝑗 𝐸𝐸𝐸𝐸𝑗𝑗

32

Page 33: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Bus Passenger Time Saving per GE

020406080

100120140

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

nds

near-side far-side

∑𝑗𝑗 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 𝑠𝑠𝑎𝑎𝑣𝑣𝑇𝑇𝑠𝑠𝑠𝑠 𝑓𝑓𝑓𝑓 𝐸𝐸𝐸𝐸𝑗𝑗∑𝑗𝑗 𝐸𝐸𝐸𝐸𝑗𝑗

33

Page 34: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Vehicle Time Savings and Delay

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Page 35: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Green Extension Efficiency

Assume single occupancy vehicles

0

10

20

30

40

50

60

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

seco

nds

Minor street vehicle delay Major street vehicle time savingMajor street passenger time saving

35

Page 36: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Early Green Efficiency

Assume single occupancy vehicles

0

10

20

30

40

50

60

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

seco

nds

Minor street vehicle delay Major street vehicle time savingMajor street passenger time saving

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Page 37: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Summary of Findings

Green extension • Too many late green extension phases• Time savings ≈ Delay

Early green • Time savings > Delay

TSP performance • Vary significantly across intersections• Big gap between actual and ideal performance

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Page 38: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Conclusions

• Proposed TSP performance measures can help identify problems/improvement opportunities and support planning decisions

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

• TSP effectiveness and efficiency can be greatly affected by control logic, parameter calibration and signal detection/communication reliability

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Page 39: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Future Work

• Consider vehicle queuing effect when estimating bus arrival time probabilities at intersections

• Utilize new and higher resolution data such as:– 5-second bus AVL data (finer bus trajectory between bus stops)– TSP Optical detector log data (priority log in/out records)

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Page 40: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Acknowledgements

Steve CallasDavid Crout

Peter KoonceWillie Rotich

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Page 41: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

Questions?

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Page 42: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

On Average

TSP request

On-time

No TSP phase within a cycle

Within a cycle but early

Within a cycle but late

GE EG

1.5% 10%

2.5% 5%

25% 1%

55%

Bus time saving 0.3s 0.5s

Passenger time saving 7.5s 10s

= 100%

Actual Ideal

GE EG

6% 27%

0% 0%

0% 0%

67%

= 100%

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Page 43: Empirical Evaluation of Transit Signal Priority through Fusion of Heterogeneous Transit and Traffic Signal Data and Novel Performance Measures

On Average

TSP phase

On-time

No TSP request within a cycle

Early

Late

GE EG

5% 40%

3% 30%

64% 8%

Bus passenger time savings 20s 90s

28% 22%

Duration 7s 11s

Major street vehicle time savings

Minor street vehicle delay

60s 300s

80s 200s

=100% =100%

Actual Ideal

100%

0%

0%

0%

GE or EG

=100%

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