Welcome, Dr. Levinson!

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ITS Lab Members 1 Welcome, Dr. Levinson! PSU ITS Lab: Bertini Group

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Welcome, Dr. Levinson!. PSU ITS Lab: Bertini Group. Rafael J. Fernández-Moctezuma. 3 rd year Ph.D. Student in Computer Science Areas of Interest Data Stream Management Systems Intelligent Transportation Systems Thesis Topic: Inter-operator feedback, bounded execution guarantees. - PowerPoint PPT Presentation

Transcript of Welcome, Dr. Levinson!

Page 1: Welcome, Dr. Levinson!

ITS Lab Members

1

Welcome, Dr. Levinson!

PSU ITS Lab: Bertini Group

Page 2: Welcome, Dr. Levinson!

ITS Lab Members

3rd year Ph.D. Student in Computer Science Areas of Interest

Data Stream Management Systems Intelligent Transportation Systems

Thesis Topic: Inter-operator feedback, bounded execution guarantees

2Rafael J. Fernández-Moctezuma

Rafael J. Fernández-Moctezuma

Page 3: Welcome, Dr. Levinson!

ITS Lab Members

• Deal efficiently with high-volumes of incoming data

• Traffic Data CS theory– Inter-Operator Feedback– Guarantees on Bounded Stream

Query Execution

Work with Prof. Maier, and Prof. Tufte3Rafael J. Fernández-Moctezuma

Data Stream Management Systems

(a) Centralized Adaptation (b) Localized Adaptation

DUPLICATE

σC σ¬C

IMPUTE

PACE

Page 4: Welcome, Dr. Levinson!

ITS Lab Members

• Big picture: Adapt to incoming data characteristics to perform near real-time imputation

• Looked at diverse strategies, not all amicable for low latency processing

• Spatial and Temporal models, some heuristic, some statistical.

Work with Prof. Bertini, Prof. Maier, and Prof. Tufte4Rafael J. Fernández-Moctezuma

On-Line Imputation StrategiesA B C

SB SCSA

Direction of flow

Page 5: Welcome, Dr. Levinson!

ITS Lab Members

• Work toward automatic bottleneck detection

• “Living history” of Portland Bottlenecks

• Can process one year of data per corridor in one day (commodity PC)

Work with Prof. Bertini, Jerzy Wieczorek, Huan Li

Bottleneck Identification

5Rafael J. Fernández-Moctezuma

Page 6: Welcome, Dr. Levinson!

ITS Lab Members

• Where do we position loop detectors to better operate the freeway infrastructure?

• Challenges: What’s “better”? Optimal ramp metering? Better travel time estimations? Early bottleneck detection?

• Recently focused on Linear Programming approach for early bottleneck detection

Work with Prof. Figliozzi, Prof. Bertini6Rafael J. Fernández-Moctezuma

Optimal Sensor Placement

Page 7: Welcome, Dr. Levinson!

ITS Lab Members

1st year Graduate Student in Transportation Engineering

Current Research Topics in the ITS Lab Impacts of Sensor Spacing on Accurate Freeway Travel

Time Estimation for Traveler Information Dynamic Bi-level Programming Models for Distribution

Centers Location

7Wei Feng

Wei Feng

Page 8: Welcome, Dr. Levinson!

ITS Lab Members

• Compute VHT errors of different travel time estimation methods where transition happens

8Wei Feng Work with Porf. Bertini

Travel Time Estimation/Sensor Spacing

• Calculate relationship between all types of errors and sensor spacing for each method

Page 9: Welcome, Dr. Levinson!

ITS Lab Members

• Minimize the combined cost of VHT error cost and sensor construction cost.

• Express optimal sensor spacing with parameters: speed, flow and cost coefficients.

• Sensitivity analysis of parameters to the optimal sensor spacing.

9Wei Feng Work with Porf. Bertini

Travel Time Estimation/Sensor Spacing

Page 10: Welcome, Dr. Levinson!

ITS Lab Members

Travel Time Estimation/Sensor Spacing

10Wei Feng Work with Porf. Bertini

• Convert absolute VHT error or percentage VHT error into money, and how to set the conversion coefficient?

• What would be the reasonable constraints of absolute VHT error and percentage VHT error when applying optimization method?

Page 11: Welcome, Dr. Levinson!

ITS Lab Members

• Upper level: Minimize total cost (system minimization)

• Lower level: Minimize distribution cost (customer minimization)– Radial distribution– Multi TSP distribution– Multi VRP distribution

11Wei Feng Work with Porf. Figliozzi

Dynamic Bi-level Model for DC Location

• Solution Algorithm: Cluster and Approximation

Page 12: Welcome, Dr. Levinson!

ITS Lab Members

Ph.D Student in Civil Engineering Areas of Interest

Freeway Management and Operation Transit Operation Intelligent Transportation System Climate Change

12Huan Li

Huan Li

Page 13: Welcome, Dr. Levinson!

ITS Lab Members

• Assess optimal stop spacing considering access cost and riding & stopping cost

13Huan Li

Transit Service Evaluation

On-BoardComputer

Radio

DoorsLift

APC (Automatic Passenger Counter)

Overhead SignsOdometer

Signal Priority EmittersStop Annunciation Memory Card

RadioSystem

Garage PC’s

Radio AntennaGPS Antenna

Navstar GPS Satellites

Control Head

• Use high resolution archived stop-level data– One year’s worth of data– Referring all routes in

Portland Metropolitan region every trip every bus stop event

Page 14: Welcome, Dr. Levinson!

ITS Lab Members

14Huan Li

Transit Service EvaluationR

oute

No.

Serv

ice

Dat

e

Leav

e Ti

me

Stop

Tim

e

Arr

ive

Tim

e

Bad

geD

irect

ion

Trip

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Loca

tion

IDD

wel

lD

oor

Lift

Ons

Offs

Est.

Load

Max

Spe

edPa

ttern

Dis

tanc

e

X C

oor.

Y C

oor.

14 01NOV2001 8:53:32 8:49:15 8:53:28 285 0 1120 4964 0 0 0 0 0 21 41 10558.58 7644468 67600514 01NOV2001 8:55:00 8:51:41 8:54:46 285 0 1120 4701 4 0 0 0 1 20 50 15215.05 7649112 67632814 01NOV2001 8:56:22 8:52:00 8:55:08 285 0 1120 4537 36 3 0 6 0 26 34 15792.35 7649674 676220

Page 15: Welcome, Dr. Levinson!

ITS Lab Members

• Analyze lane changing effect on speed using lane by lane oblique curve

• “Historical data”• Automatically identify HOV lane

merging and diverging features– Indicator: piece wised linear regression for

curve fitting– Endogenous Model vs. Extraneous Model

Traffic Flow Features on HOV lane

15Huan Li

Page 16: Welcome, Dr. Levinson!

ITS Lab Members

• Next step: compose oblique method with threshold based identification method

• Other applications: incident detection, bottleneck identification….

16Huan Li

Traffic Flow Features on HOV lane

Page 17: Welcome, Dr. Levinson!

ITS Lab Members

• Civil engineering undergraduate, senior (focus on transportation)

• Areas of Interest– Transp. system sustainability– Modeling transp. emissions and diffusion

• Honor Program – Thesis topic: Carbon Sponsoring for Personal Travel

17Alex Bigazzi

Alex Bigazzi

Page 18: Welcome, Dr. Levinson!

ITS Lab Members

• Sustainability performance measures for the transportation data archive at PSU– Emissions: currently MOBILE 6.2, will use MOVES– Fuel Consumption– Cost of Delay– Personal Mobility (PHT, PHD, PMT)

18Alex Bigazzi

‘Greening’ PORTAL

Page 19: Welcome, Dr. Levinson!

ITS Lab Members

• Errors from temporal aggregation

• Data source: disaggregate speeds from loop data

• Event: car passes over loop• Error 1: Time resolution

– Shock speed

19Alex Bigazzi

ITS Data Aggregation Effects

10 20 30 60 120 300 6000%

10%

20%

30%

40%

50%Shock Speed Error

0.5 km2.0 km

Aggregation Width (sec)

MA

PE

Page 20: Welcome, Dr. Levinson!

ITS Lab Members

• Error 2: Parameter distribution– Speed distribution narrows

• Underestimate emissions, delay– Travel time errors from using

time mean speed• Underestimate delay• Corrected using harmonic mean• Can be estimated w/ variance

ITS Data Aggregation Effects

20Alex Bigazzi

10 20 30 60 120 300 600 900 1800 3600

Aggregated Delay, Calulated and Lost

Aggregation Width (sec)

Dela

y (10

00 h

ours

)

0

5

10

15

20

Aggregate EstimateDistribution ErrorTMS Error

Page 21: Welcome, Dr. Levinson!

ITS Lab Members

• Framework for individuals to seek direct, voluntary carbon offsets for personal travel

• Targets carbon reductions outside of current monetary-based offset programs

• Project objectives:– Establish calculation methods for carbon outputs– Develop effective and simple online interface– Analyze initial feedback from pilot users

21Alex Bigazzi

CarbonSponsor.org

Page 22: Welcome, Dr. Levinson!

ITS Lab Members

1st year M.S. Student in Civil Engineering Areas of Interest

Traffic Flow Theory Intelligent Transportation Systems

Possible Thesis Topics: Uncertainty Propagation in Traffic Flow Models or Bottleneck Identification using FOTO and ASDA Models

22Meead Saberi K.

Meead Saberi K.

Page 23: Welcome, Dr. Levinson!

ITS Lab Members

• Dealing with two large databases of traffic data and weather data (PORTAL)

• Traffic and weather data fusion and quality

23Meead Saberi K.

Effects of Weather on Traffic Flow on Freeways

Page 24: Welcome, Dr. Levinson!

ITS Lab Members

• Effects of precipitation, visibility and wind speed on: speed and flow (average, standard deviation, and statistical significance)

• Probabilistic Approach: using cumulative distribution function

24Meead Saberi K.

Effects of Weather on Traffic Flow on Freeways

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No Rain Very Light Rain Light Rain Moderate Rain

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10andless

10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50 50-55 55-60 60and

more

Speed (mph)

Freq

uenc

y (%

)

No RainRainy

0

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Average Speed (mph)

1 - C

umul

uativ

e D

istri

butio

n Fu

nctio

n

Page 25: Welcome, Dr. Levinson!

ITS Lab Members

25Meead Saberi K.

Segment Level Analysis of Travel Time Reliability

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0:00 6:00 12:00 18:00

Time of Day

Trav

el T

ime

Cost

($)

Average Travel Time Standard Deviation of Travel Time

Breaking the overall I-5 NB freeway into shorter segments; this study shows how travel time reliability can vary across freeway segments using different reliability measures.

Page 26: Welcome, Dr. Levinson!

ITS Lab Members

26Meead Saberi K.

Segment Level Analysis of Travel Time Reliability

0:00 2:15 4:306:45 9:00

11:15 13:30 15:4518:00 20:15 22:30

286.1

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290.54

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0.00

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S e g me n t

Buff

er In

dex

n

i jijii SSSVarCVar

1

),cov(2)()(

• Segment ranking based on travel time reliability

• Reliability of corridor vs. segments

Page 27: Welcome, Dr. Levinson!

ITS Lab Members

Master Student in Civil engineering at the ENTPE 5 month internship at the ITS Lab Areas of Interest:

Traffic flow theory Transportation Economics

27Helene Siri

Helene Siri

Page 28: Welcome, Dr. Levinson!

ITS Lab Members

ENTPE : Civil engineering school (Lyon) Structure, environment, urbanism and transportation

Transportation department at the ENTPE LET (CNRS - University of Lyon II – ENTPE) LICIT (INRETS – ENTPE)

28Helene Siri

About the ENTPE

Page 29: Welcome, Dr. Levinson!

ITS Lab Members

Loop Detector Data from lane 3 northbound station 20 on the I-880 freeway

Aggregation of data indifferent samplingperiods

29Helene Siri

A practice study for ITS data aggregation

5 5.5 6 6.5 7 7.5 8 8.5 9 9.5 100

500

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30 sec1min5min15min

Time (h)Fl

ow (

veh/

h)

Page 30: Welcome, Dr. Levinson!

ITS Lab Members

Net speed on a urban grid with different densities of intersections and different legal posted speed

Developing a program using Matlab to estimate Net speed

30Helene Siri

Net Speed Calculator

Page 31: Welcome, Dr. Levinson!

ITS Lab Members

ITS Data Aggregation using NGSIM Data

31Helene Siri

Next step:

Page 32: Welcome, Dr. Levinson!

ITS Lab Members

2nd year M.S. Student in Statistics ITS Research:

Historical and real-time bottleneck identification

Statistics Research: Minimum Kolmogorov-Smirnov Estimation (MSKE) with

censored data

32Jerzy Wieczorek

Jerzy Wieczorek

Page 33: Welcome, Dr. Levinson!

ITS Lab Members

• Using speed data to track historical congestion and rank bottlenecks by cost

• Incorporating historical information into model to predict real-time bottleneck behavior

Work with Prof. Bertini, Huan Li,Rafael J. Fernández-Moctezuma

Bottleneck Identification

33Jerzy Wieczorek

A

B

C

Bottleneck

Estimated Propagation Speed

A – 25 mphB – 22 mphC – 21 mph

Activation

Deactivation

90% percentile of historicalbottlenecks

A

B

C

Bottleneck

Estimated Propagation Speed

A – 25 mphB – 22 mphC – 21 mph

Activation

Deactivation

90% percentile of historicalbottlenecks

A

B

C

Bottleneck

Estimated Propagation Speed

A – 25 mphB – 22 mphC – 21 mph

Activation

Deactivation

90% percentile of historicalbottlenecks

Page 34: Welcome, Dr. Levinson!

ITS Lab Members

• Expanding model to use volume data

• Validating against ground truth from Bertini-Cassidy method

Work with Prof. Bertini, Huan Li,Rafael J. Fernández-Moctezuma

Bottleneck Identification

34Jerzy Wieczorek

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NB I-5 Detector 12 (Milepost 299.7), Feb 7 2008

Speed (mph)

Vol

ume

(vpl

ph)

FreeflowCongested

Page 35: Welcome, Dr. Levinson!

ITS Lab Members

• Choose distribution and parameter estimates that minimize the K-S statistic (max. vertical difference in CDFs)

Work with Prof. Kim35Jerzy Wieczorek

Minimum K-S Estimation

θ = 96.1

θ = 72.2

Page 36: Welcome, Dr. Levinson!

ITS Lab Members

• Extend to censored data

• Evaluate in comparison with MLEs (standard)

• Create R library if worthwhile

Work with Prof. Kim36Jerzy Wieczorek

Minimum K-S Estimation