Innova&on  for  be,er  mobility  

PLANNING FOR THE 21st CENTURY - EMERGING TRENDS Delivering Big Data to Planning Practitioners

October  30,  2015  

Sco,  Perley,  VP  Performance  Analy&cs  

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Agenda •  Overview  

–  iPeMS,  leading  Big  Data  analy&cs  

•  Big  Data  –  Types  of  Big  Data  –  NPMRDS  &  probe  data  

•  Applying  Big  Data  –  Telling  stories  &  client  examples  –  Freight  opportuni&es  –  SoMware  tools  to  leverage  Big  Data  

 

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•  Iteris  is  a  leader  in  soMware-­‐based  informa&on  solu&ons  for  the  Intelligent  Transporta6on  Systems  (ITS)  market    

•  We  focus  on  three  areas  in  the  ITS  market:  

–  Sensors:  Intersec&on  and  roadway  vehicular  detec&on      

–  Systems:  Provide  local,  state  and  federal  agencies  traffic  management  services    

–  Analy6cs:  Focused  on  traffic  and  weather-­‐related  data  and  analy&cs  soMware  to  both  public  and  commercial  customers  

Who We Are…

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What Iteris PeMS Provides… Powerful  Tools  Ac&onable  visualiza&ons  &  reports  to  support  opera&ons  &  planning  

Analy6cs  For  states  and  regions  to  support  System  Performance  

Supports  Many  Data  Types  Loops,  radar,  GPS,  Bluetooth,  toll  tags,  incidents,  accidents,  lane  closures,  managed  lanes,  signals,  and  transit  +  more  

Flexible  Deployment  Cloud-­‐hosted  or  agency-­‐hosted  models  

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What Iteris PeMS Does

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• Real-­‐&me  Archive  Data  Management  System  • Stores  all  types  of  data,  normalizes  schema  • Always  online,  always  available  • Many  opera&ons  and  planning  based-­‐tools  

Transporta&on  data  warehouse  

• Rolls  data  up  over  space  and  &me  • Stores  results  for  queries  • All  calcula&ons  are  done  in  real-­‐&me  

Calculates  performance  measures  

• Opera&ons,  maintenance,  planners,  decision  makers,  public  

Presents  a  variety  of  displays  for  different  users  

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What technologies can you use?

Or  a  hybrid  approach  which  uses  combina&ons  

of  all  detectors  

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What is big data?

Loca&on  Speed  Heading  

Couple  of  minutes  

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What is Big Data?

Segment  1   Segment  2   Segment  3  

19  mph   44  mph   63  mph  

@  7:15  AM  

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How does Big Data help? •  Greater  accuracy  

–  Current  approaches  not  sta&s&cally  sound  –  (More  vehicles)  X  (More  &mes)  X  (More  days)  

•  Reduced  costs  –  Travel  &me  runs  are  expensive  

–  Probe  data  is  cheaper  •  Deeper  insights  

–  Understand  reliability  –  Larger  coverage  

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Commercial Speed Data Providers Provider   Comment  

     

HERE   Providing  data  in  District  8,  freeways  and  arterials,  every  minute  in  real-­‐&me.      

     

INRIX   MTC  purchased  INRIX  data  in  the  Bay  Area      

     

NPMRDS   Free  FHWA  dataset  to  MPOs  (for  Na&onal  Highway  Network  only)    Freight  and  Auto  Travel  Times    

     

Tom  Tom        

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Big Data: Digging Deeper

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What does NPMRDS Big Data look like? TMC   Date   Epoch   Travel  Time  

(all)  Travel  Time  

(auto)  Travel  6me  (Freight)  

105N04105   9112014   138   59   55   65  

Date  mddyyyy    Epoch  Represents  &me  i.e.  5  min  period  since  midnight  (0  -­‐  287)  

0  1  

287  

00:00:00  to  00:04:59  00:05:00  to  00:09:59  23:55:00  to  23:59:59  

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Managing Big Data: Filling in Gaps

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Managing Big Data: Filling in Gaps

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Managing Big Data: Results

Process  

§  Raw  Data  are  processed  

§  Processing  with  a  series  of  methods  

§  Speeds  for  all  &me  intervals  are  produced  

15

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Defining the Story

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The Reliability Story

Reliability Standard

Nth  percen&le  

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The Reliability Story

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The Congestion & Delay Story

Speed  

Postmile  

Delay  

BoSleneck  Cause  

Back  of  Queue  

Slowing  Return  to  Free  Flow  

Threshold  

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Iteris Big Data Customer Success SFCTA   MTC  

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Freight vs. Auto: Discovering the Space-Time Pattern Between Freight and Passenger Car Speeds Using the National Performance Measurement Research Data Set

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Real-­‐6me  and  Historic  Data  Access  • Map-­‐based  visualiza&ons  of  traffic  speeds  • User-­‐selectable  date  ranges  on  reports  

Performance  Management  &  Analy6cs  • Reports  for  Links  and  Routes  • Time  series,  &me  of  day,  day  of  week  • Conges&on  contour  plots  

 

Archived  Data  Access  • Clearinghouse  containing  daily  files  of  various  &me  aggregates  to  support  agency  processing  

Interac6ve  Map  Func6ons  •  Speeds,  quality  and  speed  anomalies  •  Link  based  speeds    

Incorporating Big Data Into Software

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•  Real-time speed

•  Link information

•  Option to compare to monthly values

3rd Party Interactive Maps

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Traffic  Anomalies  Map  

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Crea6ng  Routes  

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Time Series Speed, Travel Time & Travel Time Reliability

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Time of Day Measures

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Routes: Contour Plots Finding Bottlenecks

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Probe Data: Automating a CMP

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Interactive Dashboards

•  Using  historical  data  or  pa,erns  

•  Monthly  and  annual  comparisons  

•  Summary  charts,  metrics  and  grades  

•  Animated  maps  to  show  TOD  and  DOW  data  

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Probe Data: Dashboard for Real-Time Operations

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Dashboard for Map-21 Historical Analysis using NPMRDS Data

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iPerform

Monthly  

Comparison  

Dynamic  

Geotags  

Measure  Selec&on  

Month  to  Month  &  Year  to  Year  

Maps  &  

Graphs  

Day  and  

Time  

Sliders  

Color  as  context  

Naviga&on  

KPI  

All  elements  change  with  new  selec&on  

Boundaries  

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iPeMS Dashboard: Map Visuals

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Dashboard: Time of Day

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Dashboard: Day of Week

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Dashboard: TTI

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Dashboard: Adding Volume to Get Delay

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Big Data Summary •  New  data  sets  provide  new  opportuni&es  

–  Broader  coverage  – More  &mes  

–  New  types  of  data  

•  Working  together  with  exis&ng  data  sets  –  Can  tell  new  and  richer  stories  –  Aggregate  to  understandable  summaries  and  detailed  reports  

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Questions? For  addi6onal  ques6ons:  

Sco,  Perley  

VP,  Performance  Analy&cs  

Phone:  570.470.4081  E-­‐Mail:  sip@iteris.com