1. Iowa State University Gainesville, Florida March 20, 2001

2. N C R S T INFRASTRUCTURE ISU/CTRE Projects 1.Access Management 2.Collection of Inventory Elements

3. N C R S T INFRASTRUCTURE Project #1: Access Management

4. N C R S T INFRASTRUCTURE source: http://www.fhwa.dot.gov/////realestate /am_mich.pdf The Problem One person dies every 13 minutes (all crashes) Economic Cost  Crashes in US - $150.5 billion/year (1994)  Congestion – $72 billion/year (For 68 major Metropolitan areas in U.S.A) System-wide crash data now available No comprehensive inventory available On-road data collection is resource intensive

5. N C R S T INFRASTRUCTURE What Is Access Management? “Access Management is the process that provides access to land development while simultaneously preserving the flow of traffic on the surrounding road system in terms of safety, capacity, and speed”. (Source: Federal Highway Administration, United States Department of Transportation)

6. N C R S T INFRASTRUCTURE Statistical Relationship Between Access Density and Crash Rates There is evidence of a strong relationship between commercial driveway density and crashes

7. N C R S T INFRASTRUCTURE There is a strong correlation between access density and rear-end collisions

8. N C R S T INFRASTRUCTURE Safety Benefits: Iowa Case Studies Seven Iowa case studies were made on a “before and after” basis Case studies show nearly a 40 percent average reduction in accident rates after projects incorporating access management treatments were completed

9. N C R S T INFRASTRUCTURE Safety Benefits: Crash Reduction By Type For Iowa Case Studies

10. N C R S T INFRASTRUCTURE Research Problem Access management data collection methods  time consuming  resource intensive process. Lack of quantitative, comprehensive access data makes systematic identification of locations that would benefit from improved access management difficult, if not impossible.

11. N C R S T INFRASTRUCTURE Research Approach Survey DOTs Perform quantitative analysis Develop qualitative method Evaluate qualitative method Make recommendations

12. N C R S T INFRASTRUCTURE Survey of State DOTs 10 state DOTs (8 responded)  Florida-- Kansas  South Dakota-- Wisconsin  Michigan-- Colorado  Oregon-- Iowa Access management data elements collected Method of collecting data

13. N C R S T INFRASTRUCTURE Survey of State DOTs None maintain a comprehensive database of access related data elements Usually collect as needed (corridor level) Several  are in the process of developing one or  have indicated an inclination towards maintaining one.

14. N C R S T INFRASTRUCTURE Survey of State DOTs None maintain a comprehensive database of access related data elements Several  are in the process of developing one or  have indicated an inclination towards maintaining one. DOTData Collection Method Comments Florida Video logging and surveying Driveway locations are collected if part of an improvement project or permit Kansas Location reference system and GPS receivers KDOT is investigating the option of utilizing aerial imagery for data validation and display South Dakota Plan sheets from construction projects Aerial photography is used for planning and project development, but not as a data collection tool for access management Wisconsin Photo logs and from driveway permits Aerial photography is only used for route layout and design, but not as a data collection tool for access management Michigan Video logs Collects as needed Colorado Video logs, aerial photos Vertical and oblique aerial imagery for access management but do not store. Oregon Video logs, Manual Data collection, Aerial photos

15. N C R S T INFRASTRUCTURE Perform quantitative analysis Select statistical access management/crash model  Other research organizations  Crash rate are ƒ(#commercial driveways, median type, etc.) 10 study segments  US 69 corridor in the city of Ames, IA **Crash rate is # of crashes per million vehicles or per million vehicle miles

16. N C R S T INFRASTRUCTURE Perform quantitative analysis Identify access-management related features required by crash models Extract access-management related elements  Evaluate aerial photographs at different resolutions  Make recommendations on level required

17. N C R S T INFRASTRUCTURE Data Aerial Images  Iowa DOT (6-inch pixel, panchromatic)  Story county engineer’s office (2-foot pixel, panchromatic)  1 meter Crash Data  Iowa Department of Transportation Attributed Road network  AADT  Speed Limit

18. N C R S T INFRASTRUCTURE Access Related Data Elements Access roads  Presence  Configuration Driveways  Number  Dimensions  Frequency  Continuity  Vertical grade Medians  Type  Length Turn lanes  Length  presence Intersections  Proximity  Frequency

19. N C R S T INFRASTRUCTURE Data Extraction

20. N C R S T INFRASTRUCTURE Identifying Medians Look for object markers along the center of the Road. Object markers are an important source of identifying the type and length of raised medians Pavement markings Depressed medians can be identified with ease as most of them are covered with Vegetation

21. N C R S T INFRASTRUCTURE Identifying Driveways Sharp difference in shade from the surrounding area Cuts along the curb Vehicular movement captured at the time of taking the photograph and parked vehicles may also be used as a source to identify driveway entrances Problems  Tree Cover (Dense Vegetation)  Several close driveways appear as one

22. N C R S T INFRASTRUCTURE Perform quantitative analysis Calculate baseline crash rates for each location

23. N C R S T INFRASTRUCTURE Develop qualitative method Establish method to rank locations using aerial photographs according to “perceived” level of access management Such as  1 – good access management  2 – average access management  3 – poor access management

24. N C R S T INFRASTRUCTURE Develop qualitative method Define characteristics of ranking category, i.e.  1 = good o Defined by few driveways, presence of medians Get expert input (multiple assessors) Compute descriptive statistics for assigned scores (mean, deviation) Develop qualitative crash model

25. N C R S T INFRASTRUCTURE Evaluate qualitative method Compare crash rates for quantitative versus qualitative Is qualitative “good” enough?

26. N C R S T INFRASTRUCTURE Cost Analysis Compute cost of data collection and database development tasks on a unit basis Extrapolate for systematic analysis Compare cost of quantitative and qualitative methods, at various scales

27. N C R S T INFRASTRUCTURE Anticipated Results (late April) Recommendations for resolution required for quantitative assessment (6-inch) Recommendations for resolution and methods required for qualitative evaluation (1-meter) Comparison of model performance using quantitative vs. qualitative Cost benefit assessment

28. N C R S T INFRASTRUCTURE Project #2 : Collection of Inventory Elements

29. N C R S T INFRASTRUCTURE The Problem/Opportunity DOT use of spatial data  Planning  Infrastructure Management  Traffic engineering  Safety, many others Inventory of large systems costly  e.g., 110,000 miles of road in Iowa

30. N C R S T INFRASTRUCTURE Research Objective Can remote sensing be used to collect infrastructure inventory elements? What accuracy is possible/necessary? Cost effective?

31. N C R S T INFRASTRUCTURE Research Approach Identify common inventory features Identify existing data collection methods Use aerial photos of different resolutions to extract inventory features Statistical comparison Define resolution requirements Benefit/cost analysis Recommendations

32. N C R S T INFRASTRUCTURE Identify common inventory features Requirements of Highway Performance Monitoring System requirements Survey States  LRS requirements  Pavement management system  Data for planning and design functions  Highway needs studies  Safety studies

33. N C R S T INFRASTRUCTURE Traditional Data Collection Methods Field data collection  GPS  traditional surveying  manual Video-log van Aerial photography

34. N C R S T INFRASTRUCTURE Datasets 2-inch dataset 6-inch dataset 2-foot dataset 1-meter dataset * not collected concurrently

35. N C R S T INFRASTRUCTURE Pilot Study Locations

36. N C R S T INFRASTRUCTURE Statistical comparison Percent Recognition Accuracy Between operator variability

37. N C R S T INFRASTRUCTURE Percent Recognition Performance measure Number of features recognized in aerial photos versus ground truth  e.g. 90% of driveways can be identified using 6-inch resolution photos

38. N C R S T INFRASTRUCTURE Percent Recognized

39. N C R S T INFRASTRUCTURE Percent Recognition (Presence of Medians) 2-foot images  Identified 5 of the 9 cases where medians were present (55.6%)  4 not recognized  Could not identify type 6-inch images correctly  Identified 9 of the 9 cases  Correctly identified type of median 7 out of 9

40. N C R S T INFRASTRUCTURE Percent Recognition (surface type) 2-foot: pavement type was identified 0% of the time 6-inch: pavement type was identified 100% of the time

41. N C R S T INFRASTRUCTURE Accuracy Required accuracy depends on application Positional accuracy Linear measurements  lane width, length of turning lane, etc.  measure from aerial photos vs. ground truth

42. N C R S T INFRASTRUCTURE Positional Accuracy Located versus actual position RS vs.GPS Collected 50 points with kinematic GPS Centimeter accuracy Compared to 4 datasets  Selected same 50 points on photos  Latitude/longitude Root mean square (RMS)

43. N C R S T INFRASTRUCTURE RMS 6-inch rms = 2.3 3.9 feet at 95 th confidence interval 2-foot rms = 3.0 5.3 feet at 95 th confidence interval

44. N C R S T INFRASTRUCTURE Accuracy Linear Measures On-road collected/measured  Driveway widths  Median length

45. N C R S T INFRASTRUCTURE Between operator variability Amount of variability between different operators in selecting and locating a feature’s position Measure of operator input error

46. N C R S T INFRASTRUCTURE Comparison of Methods Types  Field (kinematic GPS)  RS  Video log Cost Advantages/Disadvantages

47. N C R S T INFRASTRUCTURE Field Data Collection (Cost) Cost $1500 for 50 points w/ kinematic GPS for services from engineering co. Included:  2 days x 2 people for field data collection  1 day x 1 person for data reduction

48. N C R S T INFRASTRUCTURE Field Data Collection (cost) Also required 5 days x 1 person (ISU student):  Mission planning (select locations, select points)  integrate data into GIS  Accompany field crew Total cost:  $1500 engineering services  $600 for ISU student effort  $2100 total

49. N C R S T INFRASTRUCTURE RS Data Collection Cost Cost $6000 for 2 miles of orthophotos (estimate from commercial source) Iowa DOT estimates $100 per mile for photos + in-house costs to ortho-rectify

50. N C R S T INFRASTRUCTURE RS Data Collection Cost Required 1 day x 1 person (ISU student) for 2 miles:  Obtain existing photos from DOT  Set up photos in ArcView  Select points and set up database Estimated Cost w/ Aerial Services for 2 miles (50 points)  $6000 for photos from commercial service  $150 for ISU student effort  $6150 total Actual Cost to project team for 2 miles (50 points)  $0 for photos (already available at DOT, 6-inch)  $150 for ISU student effort  $150 total

51. N C R S T INFRASTRUCTURE Video Log Cost not yet estimated

52. N C R S T INFRASTRUCTURE Costs GPSAerialVideo Log $2,100 $150 to $6,150 Cost not yet available

53. N C R S T INFRASTRUCTURE Advantages/Disadvantages to Data Collection Methods

54. N C R S T INFRASTRUCTURE Field Data Collection Advantages Centimeter accuracy or better Can do visual inspection 3-D data (x,y,z) Easily integrated with GIS

55. N C R S T INFRASTRUCTURE Field Data Collection Disadvantages Missed data entails new trip Data collectors on/near busy roads Difficult to collect certain data  Horizontal curvature  Roadway width

56. N C R S T INFRASTRUCTURE Video-Log Van GPS Video

57. N C R S T INFRASTRUCTURE Video-Log Van Advantages  Rapid collection of data  Multiple types of data collected  DOT’s may already have in-house Disadvantages  Missed data entails new trip  Data collection on-road may interfere w/ traffic  Data difficult to use or share among agencies  Not easily integrated with GIS  Cannot collect  elevation data  Horizontal curvature

58. N C R S T INFRASTRUCTURE RS Data Collection Advantages Multiple uses of data Data can be shared among state, local, etc. barring institutional and license agreements with data providers Data can be collected fairly rapidly Can “go” back to data Can collect most inventory elements (depending on resolution) Can get elevation data with certain types Easily integrated with GIS

59. N C R S T INFRASTRUCTURE RS Data Collection Disadvantages Costly for initial data collection May not be able to detect certain features Difficult to establish elevation Photo source: http://www.horizonsinc.com/page7.html

60. N C R S T INFRASTRUCTURE Interim Conclusions Positional accuracy of both 2-foot and 6-inch may be adequate for most inventory data elements Percent recognition is limiting factor for 2-foot Assume applicable to 1 meter as well

61. N C R S T INFRASTRUCTURE Year 1 Deliverables 3 abstracts submitted -- GIS-T, April Washington DC/ 2 accepted 2 abstracts submitted to student paper contest/ 2 accepted 1 abstract submitted -- Second International Symposium on Maintenance and Rehabilitation of Pavements and Technological Control, July, Auburn, Alabama/ 1 accepted

62. Year 2

63. N C R S T INFRASTRUCTURE Projects NCSRT-I/Iowa DOT  Task 0: write cookbooks and participate in international efforts (host late spring meeting?)  Task 1: track Iowa DOT experience with LIDAR for road design  Task 2: evaluate LIDAR/IFSAR vs photogrammetry for ongoing preliminary design

64. N C R S T INFRASTRUCTURE Projects (cont.) Midwest Transportation Consortium/Iowa DOT  Obtain LIDAR/IFSAR products and Satellite/aerial digital Imagery  Task 1: impact of as built road environment and off system characteristics (clutter, site distance and other road features) on aging population  Task 2: pavement “distortions” and drainage impact on pavement performance  Task 3: watershed/terrain modeling for flood flow prediction/impact on surety of bridges and culverts

65. N C R S T INFRASTRUCTURE Project Alternates Identification of highway features related to high crash locations (curve identification and measurement of radius/superelevation, etc.) Hybrid machine/manual update of R/W centerline

66. N C R S T INFRASTRUCTURE Alt. Project #1 ID curves and measure Inputs: cartography, GPS van tracks, USGS DOQQ, satellite Methods: segment bearing, segment length, officer ID, visual ID, closed form series expansion for radius calculation from chord Use: attribute database using LRS, correlate crash history with curve metrics

67. N C R S T INFRASTRUCTURE Alt. Project #2 Start with existing centerline Obtain statewide imagery (sample only for this project, e.g., county) Filter to ID “potential roads” Buffer existing centerline and remove proximate “potential roads”, leaving “potential new roads”

68. N C R S T INFRASTRUCTURE Alt. Project #2 Start with existing centerline Obtain statewide imagery (sample only for this project, e.g., county) Filter to ID “potential roads” Buffer existing centerline and remove proximate “potential roads”, leaving “potential new roads”

69. N C R S T INFRASTRUCTURE Alt. Project #2 Start with existing centerline Obtain statewide imagery (sample only for this project, e.g., county) Filter to ID “potential roads” Buffer existing centerline and remove proximate “potential roads”, leaving “potential new roads”

70. N C R S T INFRASTRUCTURE Alt. Project #2 Start with existing centerline Obtain statewide imagery (sample only for this project, e.g., county) Filter to ID “potential roads” Buffer existing centerline and remove proximate “potential roads”, leaving “potential new roads”

71. N C R S T INFRASTRUCTURE Alt. Project #2 Update centerline and populate only those attributes Benefits: uses best of machine and human, eliminates need to conflate entire database, focuses only on changes

72. N C R S T INFRASTRUCTURE Questions/Suggestions?