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Transpo 2012 Mohammed Hadi, Yan Xiao, Tao Wang Lehman Center for Transportation Research Department of Civil and Environmental Engineering Florida International University Miami, FL October 30, 2012 Utilization of ITS Data for off-Line and Real-Time Assessment of Transportation System Performance
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Transpo 2012

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Transpo 2012. Utilization of ITS Data for off-Line and Real-Time Assessment of Transportation System Performance. Mohammed Hadi, Yan Xiao, Tao Wang Lehman Center for Transportation Research Department of Civil and Environmental Engineering Florida International University Miami, FL - PowerPoint PPT Presentation
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Page 1: Transpo 2012

Transpo 2012

Mohammed Hadi, Yan Xiao, Tao Wang

Lehman Center for Transportation ResearchDepartment of Civil and Environmental Engineering

Florida International UniversityMiami, FL

October 30, 2012

Utilization of ITS Data for off-Line and Real-Time Assessment of Transportation System

Performance

Page 2: Transpo 2012

BackgroundITS data can be used in combination with traffic

analysis, simulation modeling, data fusion/data mining and optimization for planning and operation

Real-time and Off-linePerformance measurements of transportation systemTransportation system modeling Benefits and costs assessment of ITS applications Associations of attributes utilizing data mining and

visualization methodsDecision support systemsPredictive travel time and impacts

Page 3: Transpo 2012

ITSDCAP ComponentsITS Data Capture and Analysis of Performance

(ITSDCAP) Capture and fusion of data from multiple sourcesData mining Performance measurements and visualization ITS evaluation/benefit-cost analysisModeling and analysis supportDecision support systems to be incorporated

Page 4: Transpo 2012

Data from Multiple SourcesSunGuide data (TSS, TVT data, incident, DMS,

etc.)InrixStatistics office dataCentral data warehouseWeather data Managed lane dynamic congestion pricing ratesWork zones Crash data/CARS511 dataFHP data

Page 5: Transpo 2012

Data GroupingData grouping allow the extraction and archiving

of data based on different conditionsTime-of-day, working days/holidays, day of the weekSpecific segmentsSimilarity in traffic patterns IncidentsWeather conditionsWork zones

Page 6: Transpo 2012

Progress Meeting

Selection based on Traffic Patterns

Page 7: Transpo 2012

Performance MeasurementsMobility measures

Reliability measures

Environmental measures

Safety measures

Page 8: Transpo 2012

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Page 9: Transpo 2012

Mobility and ReliabilityMobility measures: speed, density, queue

length/location, travel time, delay, vehicle-mile traveled (VMT), and vehicle-hour traveled (VHT)Alternative methods are incorporated to calculate

different measures based on point detector data and INRIX data. AVI data being incorporated and studied

Reliability measures: standard deviation/variance, Buffer Index, Failure/On-time performance, Planning Time Index based on the 95th or 80th percentile, Skew Statistics, and Misery IndexNew measures will potentially be incorporatedAt least one year of data

Page 10: Transpo 2012

Safety and Environmental ImpactsSafety: Estimate a number of safety measures

including crash frequency by crash type, crash frequency by severity, total crash frequency, crash rate by type, crash rate by severity, and total crash rate

Energy and Emission: Currently based on Mobile 6. When emission rates based on MOVES are calculated for Florida they will be incorporated

Page 11: Transpo 2012

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Page 12: Transpo 2012

Travel Time ComparisonI-95 NB from South of NW 62nd St. to Golden Glades

Interchange (Exit 12A)

9/1/2011

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0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00

Trav

el T

ime

(Min

utes

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Timestamp

TVT Link Travel Time

Inrix Travel Time

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0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00

Trav

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ime

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utes

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Timestamp

TVT Link Travel Time

Inrix Travel Time

9/22/2011

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IRISDS

Web-based real-time information sharing and decision support system Integrated Regional Information Sharing and Decision

Support system (IRISDS)

Proof of concept of two main components Information sharing (SunGuide C2C, transit AVL, INRIX)Decision support systems

Page 18: Transpo 2012

IRISDS

Page 19: Transpo 2012

Decision Support System

Incident impacts, impact index, and dashboardReal-time simulation of incidentsUtilizing bus travel time to estimate corridor travel timeEstimate diversion during incidents and potential

impacts on alternative routes

Page 20: Transpo 2012

Prediction of Incident Impacts

The prediction of impacts based on measured incident attributes include:

Predict lane blockage duration Predict potential for secondary incidents Predict delays and queue lengths Assigns a severity Index to each incident based on the

impacts and user assessment of impact weights

Page 21: Transpo 2012

Incident Impacts and Index