Technology Choices for Technology Choices for Data Collection and Data Collection and Condition Assessment Condition Assessment Leonard (Len) Schultz Leonard (Len) Schultz Transportation Engineer Manager Transportation Engineer Manager Highway Maintenance Division Highway Maintenance Division Maryland State Highway Administration Maryland State Highway Administration
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Technology Choices for Data Collection and Condition Assessment Leonard (Len) Schultz Transportation Engineer Manager Highway Maintenance Division Maryland.
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Technology Choices for Data Technology Choices for Data Collection and Condition Collection and Condition
AssessmentAssessment
Leonard (Len) Schultz Leonard (Len) Schultz Transportation Engineer ManagerTransportation Engineer ManagerHighway Maintenance DivisionHighway Maintenance DivisionMaryland State Highway AdministrationMaryland State Highway Administration
ASSET MANAGEMENT DATA COLLECTION GUIDE
DRAFT DOCUMENT Version: June 2004
Prepared by: J. W. Bryant, Jr., Ph. D., P. E., Virginia Transportation Research Council [email protected]. D. Larson, P. E., PMP, Virginia Department of Transportation [email protected]
Prepared by: J. W. Bryant, Jr., Ph. D., P. E., Virginia Transportation Research Council [email protected]. D. Larson, P. E., PMP, Virginia Department of Transportation [email protected]
In general the asset data collection requirements can be categorized into the following: (1) Location; (2) Physical Attributes; and (3) Condition. Locations are usually denoted by a “from – to” county-route-mile (CRM) for linear assets. Nonlinear assets are point specific and are denoted by either a single CRM or by use of landmark data. In all cases GPS coordinates and or physical landmarks can be used to acquire the location information for both linear and nonlinear assets.
The physical attributes collected will vary from asset to asset. Physical attributes are used to describe the asset in question. General attributes that are consistent across assets include: material type, size, and length.
Condition assessment is depended on the specified performance criteria for the asset.
Data for condition assessment can be broad for some assets requiring only Good, Bad or fair, while other assets may require a more detailed approach set forth by national or regional accepted practices or standards.
Table 2-1 presents the basic inventory attributes for transportation assets. Condition attributes vary greatly from asset to asset as to how they are reported; therefore they were excluded from Table 2-1.
Structures and Bridges: Overhead Sign Structures, Structural Culverts, Overall Bridge, Sound Barriers, and Retaining Walls
Special Facilities: Movable Bridges, Rest Areas, River and Mountain Tunnels, Weigh Stations, and Traffic monitoring Systems
Data CollectionData Collection
Data collection methods should be Data collection methods should be developed with developed with data at its core rather than data at its core rather than the applications they servethe applications they serve. Applications . Applications may go obsolete and be updated but the may go obsolete and be updated but the data collection and how it is structured data collection and how it is structured must be able to be migrated and must be able to be migrated and integrated to multiple/other systems. integrated to multiple/other systems. Therefore, the electronic collection, Therefore, the electronic collection, dissemination, and updating is critical.dissemination, and updating is critical.
What is it?What is it?
Sign Installation?Sign Installation?
Number of Signs?Number of Signs?
Type of Sign?Type of Sign?
Number of Posts?Number of Posts?
Type of Posts?Type of Posts?
All the above?All the above?
Each Installation or Location?Each Installation or Location?
Traffic Control DevicesTraffic Control Devices
Installation?
Signal Heads?
“In general the asset data collection requirement can be categorized into the following:
Locations are usually denoted by a “from – to” county-route-mile (CRM) for linear
assets. Nonlinear assets are point specific and are denoted by either a single CRM or by use of landmark data. In all cases GPS coordinates and or physical landmarks can be used to acquire the location information for both linear and nonlinear assets.
Physical Attributes collected will vary from asset to asset. Physical attributes are used to describe the asset in question. General attributes that are consistent across assets include: material type, size, and length. Condition assessment is depended on the specified performance criteria for the asset.
Condition Assessment can be broad for some assets requiring only Good, Bad or Fair, while other assets may require a more detailed approach set forth by national or regional accepted practices or standards. Table 2-1 presents the basic inventory attributes for transportation assets. Condition attributes vary greatly from asset to asset as to how they are reported; therefore they were excluded from Table 2-1.”
Dynamic SegmentationDynamic Segmentation Dynamic Segmentation is a term used to describe the
process of combining data from two or more perspectives by "dynamically" creating a third set of sections that represents the smallest common denominator sections between the first two sets.
Dynamic Segmentation is useful for performing, "show me" kind of reports on a roadway database. It is not, however, very useful for sharing data across many applications.
It is easy to illustrate Dynamic Segmentation by drawing two strip maps of a road both showing the set of sections from two different section perspectives
Dynamic SegmentationDynamic Segmentation
Milepoint 0.00 1.00 2.00 3.00 4.00
ADT 10,000 5,000
Number of Lanes 4 Lane 2 Lane
Guardrail 12,000' 500'
Mowable Acres 10 25
Maintenance Cost $100 $240
Results of DS
AADT 10,000 5,000
Number of Lanes 4 2
Guardrail 4,000 8,500
Mowable Acres 10 25
Maintenance Cost $100 $240
Data Collection MethodsEfforts to streamline asset data collection have been underway since the 1960’s. The general progression of transportation asset data collection is presented below:
Photo log: Originally collected form of the data (e.g. had to be viewed through sequential image access of film). Mainly occurred through 1960’s to 1980’s. Many DOT’s had this type of program though sometimes the activity got cut in times of economic pressure.
Video log: This data collection form data could be random accessed when placed on a laser disk. Mainly occurred 1980’s to some DOT’s at present (though most converting to digital).
Regular Resolution Digital images: (i.e., 640 by 480 resolution). These are typically placed on CD’s, DVD’s or a large network server. Mainly mid-1990’s to present.
High-resolution digital images: (i.e., 1300 by 1000 resolution). Mainly later 1990’s to present. Increasingly DOT’s are looking to place the image data on a large server and make available across a network (where sufficient bandwidth and speed exist). e.g., Minnesota DOT.
Mobile data collection
Involves the use of a vehicle that is equipped with a distance measuring device and or GPS capabilities, digital video camera’s, and the appropriate computer hardware to capture, store and process the data collected.
Satellite or Aerial Imagery
High resolution images that are acquired via satellite, or plane may also be used to reference the location information for transportation assets. The individual pixels corresponding to the assets in the picture are geo-referenced with respect to ground locations. Once the image is geo-referenced the location of the assets can be extracted, manually or via a software computer package.
Data Collection Tablets and On-board ComputersData Collection Tablets and On-board Computerswith User Defined Keyswith User Defined Keys
Collection Devices for the Collection Devices for the Appropriate AssetAppropriate Asset
Handheld Data CollectorsHandheld Data Collectors
• GPS
• Touch Entry
• Voice
• Digital Camera
Condition AssessmentsCondition Assessments
Reflectometer
Condition AssessmentCondition Assessment
ARAN Automated Road Analyzer by Roadware
Skid Truck
Condition AssessmentsCondition Assessments
Sharing the PainSharing the Pain Pavements: Flexible Pavements (HMA), PCC Pavements, Unpaved
Roads; Paved Shoulders, and Unpaved Shoulders
Roadsides: Vegetation and aesthetics, Trees, Shrubs and brush, Historic Markers, and Right-of-way Fence
Drainage Structures: Cross Pipes and Box Culverts, Entrance Pipes, Curb & Gutter, Paved Ditches, Unpaved Ditches, Edge Drains and Under-drains, Storm Water Ponds, and Drop Inlets
Knows maintenanceKnows maintenance Less familiar to technology Less familiar to technology Knows the roadwayKnows the roadway Cost to train Cost to train No cost to Collect No cost to Collect Impedes maintenance work Impedes maintenance work Ownership/ControlOwnership/Control Cost to upgrade Cost to upgrade
Outsourcing:Outsourcing:
Knows technologyKnows technology CostCost Maintains equipmentMaintains equipment CostCost Upgrades TechnologyUpgrades Technology CostCost Does not require state resourcesDoes not require state resources n/an/a
main - te - nance \ mant - nen (t)s\ n [ME, fr. mainteni]
1; the art of preserving, protecting, restoring o repairing property - previously viewed as an incidental operation; now considered integral to well managed entities. 2: the last and most critical element in the planning, design, and construction of a facility. 3: a planned and organized effort often performed under chaotic circumstances or impossible time limits, usually without ample resources (see miracles) 4: slang : a person or group of persons reputed to be able to complete any task regardless of the circumstance or conditions placed upon that person or group of persons.