Midcon August Presenters: Joseph Drahos and Shawn Blaesing-Thompson

Transcription

1 Midcon August 2015 Presenters: Joseph Drahos and Shawn Blaesing-Thompson

2 Introduction Pavement Marking Management Task Force Look at most effective use of allocated paint program dollars Almost $7 million a year to maintain consistent pavement markings Leverage existing historical reflectivity readings, GPS AVL, grooved locations Identify existing areas of grooved stripes to assess paint longevity

3 Background Paint Reflectometers LTL-X Retroreflectometers Purchased 12 units in 2004 Advertised with ability to export Limitations prevent exporting Roadvista StripeMaster 2 Purchased 6 units in 2014 Touch based Export via USB LTL-X Roadvista

4 Background Laserlux Van For interstate and major four-lane roadways High speed measurements Not being collected staffing vacancies Data available Fall 2002 Fall 2012 GPS/AVL Paint trucks equipped 6 striping paint trucks and curb trucks EZ-Liner and Skipline upgraded GPS in 2012

5 Reflectometer Data Previous Collection Process Historically provided via spreadsheets at predetermined points Manually wrote, then later inputted into sheets, then sent to central office Collected every 5 miles in the Spring; 10 miles in the Fall Compiled by central office sent to INTRANS Current Paint Process Workflow Limited paint funds result in prioritization Avg paint cycle mid-april to mid-october Priority 1 & 2 every year when possible Priority 3 & 4 every 2-3 years, sometimes 4 Leveraged a new process spring 2015 for reflectance data input using IPad and Fulcrum application Collected Line Types White Edge Line (WEL) Yellow Edge Line (YEL) Yellow Center Line (YCL) White Dashed Center Line (WDC) Four Priority Groups Priority 1 All YCL Priority 2 All edge line on A roads Priority 3 All edge line on 2 lanes Priority 4 All edge on other routes

6 Data Analysis Preliminary Findings Mean Pass/Fail Values for each line type.

7 Data Analysis Preliminary Findings Percent passing for each line type

8 Data Analysis

9 Data Analysis

10 Data Analysis Preliminary Findings Yellow Lines

11 Data Analysis Preliminary Findings Yellow Centerlines Fall 2014 Paint, Spring 2015 Reflectance Readings

12 Data Analysis WEL

13 Data Analysis YCL

14 Data Analysis Combining datasets Grooving data and change in paint reflectivity between years/seasons looking for validation that grooving extends lifespan of paint Questions for ongoing analysis Does pavement grooving make a difference? Does it make sense to apply higher quality paint in high traffic areas? What kind of degradation is seen between fall and spring? What kind of degradation is seen due to winter weather events as well as looking at traffic volumes?

15 Resources for Field Staff

16 Future Process Transitioning Resources for the Districts Not a significant need for statistics and analytical work Primary concern on where to paint to support operational decision-making Analytics for Management 2014 DOT Strategic Plan key initiative towards change Decision-making using data driven performance metrics Need for a refined process and product that is more strategic/less operational

17 Conclusion Refining the Process is Ongoing Period of Transition New team members Data standardization and review is ongoing Continued outreach with the district paint crews Data Available Percent passing for all paint line types Average reflectance for all paint line types Maps showing pass/fail and grooving information for all paint line types GPS/AVL data from

18 Acknowledgements Iowa DOT Pavement Marking Management Task Force Iowa DOT District Paint Crews Office of Maintenance GIS Interns Institute for Transportation Safety (INTRANS) research team Specifically Inya Nlenanya, Nicholas Burdine, and Omar Smadi

19 THANK YOU Joseph Drahos Iowa DOT Office of Systems Planning Shawn Blaesing-Thompson Iowa DOT Maintenance Office