Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control...

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Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center for Future Urban Transport www.its.berkeley.edu/volvocenter/
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Transcript of Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control...

Page 1: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

Luminy, October 2007

Traffic Flow in Networks:Scaling Conjectures, Physical Evidence,

and Control Applications

Carlos F. DaganzoU.C. Berkeley Center for Future Urban Transport

www.its.berkeley.edu/volvocenter/

Page 2: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

References

1. Daganzo, C.F. (1996) “The nature of freeway gridlock and how to prevent it" in Transportation and Traffic Theory, Proc. 13th Int. Symp. Trans. Traffic Theory (J.B. Lesort, ed) pp. 629 646, Pergamon Elsevier, Tarrytown, N.Y.

2. Daganzo, C.F. (2007) “Urban gridlock: macroscopic modeling and mitigation approaches” Transportation Research B 41, 49-62; “corrigendum” Transportation Research B 41, 379.

3. Daganzo, C.F. and Geroliminis, N. (2007) “How to predict the macroscopic fundamental diagram of urban traffic” Working paper, Volvo Center of Excellence on Future Urban Transport, Univ. of California, Berkeley, CA (submitted).

4. Geroliminis N., Daganzo C.F. (2007a) “Macroscopic modeling of traffic in cities” 86th Annual Meeting Transportation Research Board, Washington D.C.

5. Geroliminis, N. and Daganzo, C.F. (2007b) “Existence of urban-scale macroscopic fundamental diagrams: some experimental findings” Working paper, Volvo Center of Excellence on Future Urban Transport, Univ. of California, Berkeley, CA (submitted).

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Page 3: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

T

x L

Definitions

Flow, q = VKT / TL (veh/hr)

Density, k = VHT / TL (veh/km)

Speed, v = VKT / VHT (km/hr)

C-rate, f = Completions / TL (veh/km-hr)

(Daganzo, 1996)

Page 4: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

Link Laws

k0

Optimum Density

Density, kfmax

Max completion rate

C-rate, f

Flow, q

qmax, Capacity

d, kms per completion

(Daganzo, 2007)

• (q, k, v) related by FD

• q / f = d

• Optimal density (Capacity; Max C-rate)

Page 5: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

Composition: J Identical Links

Lj Lj = L dj = d

kj , qj , vj , fj

f f ; k k

(Daganzo, 2007)

q/Jq)/(TLJ)VKT(qj jj j

Page 6: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

Network of identical links: Jensen’s inequality: q ≤ Q(k)

If vi ~ constant:

q ~ Q(k)

f ~ Q(k) / d

Density

q( ki , qi )

d ( ki , qi )k q

f

Flow

C-rate

(Daganzo, 2007)

Conjectures

Real Networks:

• An MFD exists• Trip completions / Network flow ~ Constant

Page 7: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

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Ou

tflo

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Vehicle Accumulation

San Francisco Simulation: No Control

(Geroliminis & Daganzo, 2007a)

Page 8: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

• Fixed sensors500 ultrasonic detectors

– Occupancy and Counts per 5min

• Mobile sensors140 taxis with GPS

– Time and position– Other relevant data

(stops, hazard lights, blinkers etc)

• Geometric dataRoad maps(detector locations, link lengths, intersection control, etc.)

(Dec. 2001 data)

10 km2

(Geroliminis & Daganzo, 2007b)

Real World Experiment: Site Description

Page 9: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

Real World Experiment: The Demand

Occupancy by time-of-day Flow by time-of-day

(Geroliminis & Daganzo, 2007b)

Page 10: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

0

0.25

0.5

0.75

1

0 10 20 30 40 50 60 70o i (%)

q i/m

ax {q

i}

Detector #: 10-003D Detector #: T07-005D

Real World Experiment: The Detectors

oi (%)

q i (

dim

ensi

onle

ss)

Page 11: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

Real World Experiment: The Detectors

0

15

30

45

0 20 40 60 80o u (%)

qu (

vhs/

5min

)

A1B1C1D1A2B2C2D2

0

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20

30

40

0 20 40 60o u (%)

vu (

km

/hr)

A1

B1

C1

D1

A2

B2

C2

D2

(Geroliminis & Daganzo, 2007b)

Page 12: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

Real World Experiment:Taxis

Conjecture: Passenger carrying taxis use the same parts of the network as cars

(Geroliminis & Daganzo, 2007b)

Then:

taxi

taxi

u t u t

n t n t t

t t

Page 13: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

Filters to determine full vs. empty taxis

A stop is a passenger move, if:• hazard lights are ON or• parking brake is used or• left blinker is ON and taxi stops > 45 sec or • speed < 3 km/hr for >60sec

A trip is valid if:• trip duration > 5 min and length > 1.5 km and • trip distance < 2 × “Euclidean distance”

(Geroliminis & Daganzo, 2007b)

Page 14: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

A1

A3 A2

Taxi ID:1087 Date:12/14/2001

Direction:

A1→A2→A3→A4→A5→A6→A7→A8

Time Position Trip17:11.30 A1

17:22.00 A2

17:26.00 A3

17:48.00 A4

19:00.30 A5

19:34.30 A6

19:40.00 A7

19:57.00 A8

A5

A4

A8

A6

A7

1km

SEA

Area of Analysis

FULLEMPTYFULL

EMPTYFULL

EMPTYFULL

Illustration of Filter Results

(Geroliminis & Daganzo, 2007b)

Page 15: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

Illustration of Filter Results (Cont.)

0.5

0.8

1.1

1.4

1.7

2

3:35 6:05 8:35 11:05 13:35 16:05 18:35 21:05 23:35

time

outb

ound

/ in

boun

d

detectors

taxis

(Geroliminis & Daganzo, 2007b)

Page 16: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

Real World Experiment:Taxis

Conjecture: Passenger carrying taxis use the same parts of the network as cars

(Geroliminis & Daganzo, 2007b)

Then:

taxi

taxi

u t u t

n t n t t

t t

Page 17: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

Real World Experiment: Results

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v T (k

m/h

r)

12/14/2001,3.30-13.30

12/14/2001,13.30-24.00

^

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n (vhs)

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%error < 1/√average N' T

%error < 2/√average N' T

^

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time

P /

D

(km

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^

(Geroliminis & Daganzo, 2007b)

Page 18: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

Aggregate Dynamics

Given : inflow qin

Output: e = G(n)

e = G(n)

qin

n ))t(n(G)t(qdt

)t(dnin

(Daganzo, 2007)

n

Page 19: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

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de

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No Control With Control

Time

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ps

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de

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Restrict vehicles from entering

Finding: Effect of Control

(Geroliminis & Daganzo, 2007a)

Page 20: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

Ring Road Simulation: No Control

(Daganzo, 1996)

Page 21: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

Ring Road Simulation: Control

(Daganzo, 1996)

Page 22: Luminy, October 2007 Traffic Flow in Networks: Scaling Conjectures, Physical Evidence, and Control Applications Carlos F. Daganzo U.C. Berkeley Center.

Ongoing Work: San Francisco

(Daganzo & Geroliminis , 2007)

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