John R. Kasich, GovernorJerry Wray, Director “Big Data & Asset Management” Ohio Planning Conference 2014

John R. Kasich, GovernorJerry Wray, Director Ohio Department of Transportation Big Data: Asset Management Andrew Williams, Administrator Office of Technical Services

Big Data Big data is a collection of large data sets so large and complex that it becomes difficult to process using on-hand database management tools. More data tends to lead to more accuracy. More accurate analyses may lead to more confident decision making. And better decisions can mean greater operational efficiencies, cost reductions and reduced risk.

The four dimensions of use  Aspects of the way in which users want to interact with their data…  Totality: Users have an increased desire to process and analyze all available data  Exploration: Users apply analytic approaches where the schema is defined in response to the nature of the query  Frequency: Users have a desire to increase the rate of analysis in order to generate more accurate and timely business intelligence  Dependency: Users’ need to balance investment in existing technologies and skills with the adoption of new techniques

Data Cycle

Asset Management Video Click link below to watch Asset Management Video on YouTube: Big-Data-Video.aspx

John R. Kasich, GovernorJerry Wray, Director Ohio Department of Transportation Managing Big Data – with GIS Dave Blackstone Transportation Information Management Section / Office of Technical Services

County Boundaries

Township Boundaries

City Boundaries

Urban Boundaries

State Route System (19,467 miles)

State (19,467) & County (28,973)

State (19,467), County (28,973) & Township (41,530)

State (19,467), County (28,973), Township (41,530) & Muni (31,664)

Road Inventory

PCR

ELLIS

ELLIS

Surface Projects & PCR

Bridges

Bridges by System

Bridges by GA

Bridges

Bridges & OSIP Imagery

Rail Lines

Rail Crossings

Airports

Intermodal

Crashes

Crashes by Severity

ADT

Underground Mines

Underground Mines & Road Segments

Road Section & Mines

PCR

ADT

Crash

ADT-PCR-Crash

Number of Crashes/Segment

Crash Rate

Contact Information  Dave Blackstone  Office of Technical Services  Transportation Information Management Section    TechServ/Pages/default.aspx

John R. Kasich, GovernorJerry Wray, Director Ohio Department of Transportation Big Data – It All “Counts” Dave Gardner Traffic Monitoring Section / Office of Technical Services

Traffic Monitoring Section

Traffic Monitoring Program  Count Programming  Data Collection  Data Processing & Editing  Reporting

ODOT Count Program Where do we (ODOT) collect traffic data?  3 – Year Cycle –State System Roads (Interstate, US, and State Routes) –14,200  6-Year Cycle (Local Roads) –HPMS Universe Counts – 4,200 –Safety – 3,700 –Modeling – 5,500  Additional Counts Received from –County Engineers – 6,200 –MPOs – 12,000  Total Program Counts – 45,800

Data Collection - Types of Counts  Portable Vehicle Classification Counts  Portable Vehicle Volume Counts  Manual Intersection Turning Movement Counts  Permanent Traffic Counter  Weigh-In-Motion (WIM)

ODOT Count Program How do we (ODOT) collect traffic data?  Short Term Counts –ODOT - Collected by 3 Consultants Statewide –Local Agency Coordination – Have acquired close 18,000 counts from the county engineers and MPOs.

ODOT Count Program How do we (ODOT) collect traffic data?  Permanent Counts – ODOT/Contractor Maintained

ODOT Count Data Processing (Current)  Short Term Counts -VB.net application/Access Database  Permanent Counts -Traffic Keeper Ohio (TKO) Client/Server  Weigh-In-Motion -TKO/Mainframe

Reporting  Annual Average Daily Traffic (AADT)  Vehicle Volume Data  Vehicle Classification Data  Adjustment Factors  Various Summary Reports:  Daily  Weekly  Annually  By direction, by lane  Equivalent Single Axle Loadings (ESALs)

ODOT Count Data Reporting (Current) Traffic Survey Report/Map

ODOT Count Data Reporting (Current) TIMS

ODOT Count Data Processing (Future)  Midwestern Software Solutions -Cloud based system -Offers Traffic Count Database, Traffic Count Segments, and Turning Movement Modules -Consolidates processing, storage, and reporting for Short term, permanent, and turning movement counts.

ODOT Count Data Reporting (Future)

ODOT Count Data Processing (Future)  Integration with: -Roads and Highways (RI) -TIMS -BTRS -Safety -Permitted Lane Closure -Pavements -Others

Contact Information  Dave Gardner  Office of Technical Services  Traffic Monitoring Section    TechServ/Pages/default.aspx

John R. Kasich, GovernorJerry Wray, Director Ohio Department of Transportation Brian Schleppi Infrastructure Management Section / Office of Technical Services

1 Cycle of Images Roughly 27,000 miles X 200 shots per mile X 4 camera views (left, front, right, & rear) = over 21 million images = over 11 TB of data (single copy)

1 Cycle of Images ~ $ 1 million to support per cycle < 5 cents per image really becomes < 1 cent per image when you prorate for other data collected  Road profiles  Macrotexture  Rutting  Surface images  Spatial reference

1 Cycle of Images All data inclusive of:  Linear Reference: County, Route, Logpoint/Milepoint  Spatial Reference: Latitude & Longitude  Date & Time Stamp  Free access to ODOT & J. Q. Public

Asset Extractions from Images Building Asset Inventories for Barrier and Overhead Signs 71,816 barrier runs for 5,612 miles of barrier Concrete barrier (rigid) 1,031 miles Guardrail barrier (semi-rigid) 4,296 miles Flexible barrier (cable rail) 284 miles 25 interns completed in 3 weeks time

Overhead Sign Inventory Collection Process

Locating signs with BOX 76 Left click and use cursor to drag a box around sign.

Recording info into database 77 Once sign or signs are boxed, now fill out the database record window.

Selecting Correct Sign 78 Select correct sign based off of image.

Legend Data & Number Of Signs 79 Select number of signs being collected. Any wording on signs will be placed in the Legend.

Selecting Sign Supports 80 Select sign support from support menu.

Continue Collecting 81

Macrotexture Analysis Safety Component Proactively Identify potential High Wet Crash locations

1 Cycle of network road profiles Roughly 27,000 miles X 5280 feet per mile X 12 elevation points per mile X 2 wheel paths mile = over 3.4 Billion stored profile points

Network Road Profiles  FHWA / MAP-21 Requirement to report data nationally as performance metric (IRI)  Used in OH DOT’s Pavement Management System  Leveraged to develop IRI based smoothness specifications for highway construction

International Roughness Index (IRI) Using profiles to simulate vehicle response (What the public “feels”)

Click the link below to watch Road Profiling Videos nce/Pages/Road-Profiling-Videos.aspx

Network Road Profiles  In-house Research –Interstate Bridges 2.5 X rougher than Pavement –Bridges make up less than 4% of network by length –Bridges raised network IRI by almost 8%  Set the stage to develop PN 555, IRI for Bridges –Happy motoring public –Infrastructure Benefits

Contact Information  Brian Schleppi  Office of Technical Services  Infrastructure Mangement Section    TechServ/Pages/default.aspx