IT'S all in there: NJDOT manages highway maintenance.
THE DATA COLLECTION CHALLENGE
In 2001, NJDOT's Division of Operations Support purchased a highway maintenance management system (HMMS) to assist in planning, budgeting, and managing nearly all maintenance-related information. The core HMMS software, developed by Booz/Allen/Hamilton (McLean, Virginia), will also aid NJDOT in developing the advanced asset management reporting necessary for compliance with GASB Statement No. 34. Before the HMMS could be fully utilized, however, location, description, and condition data on highway attributes from guiderail to drainage inlets had to be collected and entered. But gathering detailed data on New Jersey's 36,000 miles of roadway--or even just the 2,325 miles directly under NJDOT's jurisdiction--was cost prohibitive. The solution to the maintenance and asset management group's data collection challenge was to build on a straight line diagram system (SLD) already in use by a different division of NJDOT.
STRAIGHT LINE DIAGRAMS
SLDs are one-dimensional "stick drawings" of roadway segments annotated with highway geometry measurements and roadway features. Their simple format clearly displays large amounts of attribute data at once-- much more than would be readable on a traditional two-dimensional map. For years, NJDOT had relied on manual SLDs hand-drawn on mylar, but updating and distributing the book of diagrams was expensive and inefficient. In 1996, the Bureau of Transportation Data Development, part of the Division of Traffic Engineering and Safety under the Assistant Commissioner for Operations, embarked on a project to create electronic SLDs that were flexible, complete, and more easily updated than the paper diagrams.
A HYBRID GIS
NJDOT contracted with the Princeton office of Michael Baker Jr., Inc., a unit of Pittsburgh-based Michael Baker Corporation, to develop the automated SLD system. The system, funded by the Federal Highway Administration (FHWA) and completed in 1997, is essentially a hybrid GIS. The first step of the project was to enhance NJDOT's existing GIS, transforming the roadways into "smart" lines so that the GIS could be linked to other databases. Then, using the original paper SLDs and other separate sources, the Baker team gathered highway attribute data such as functional classification, jurisdiction, speed limit, number of lanes, lane width and type, and interchanges.
The linear-referenced data was imported into a Microsoft SQL Server data warehouse. The data warehouse is linked to both the GIS and a custom SLD application that automatically generates SLDs, displaying the one-dimensional diagrams along with a GIS view to help users get their bearings. Baker also developed an interface to allow users to easily query the system without being SQL experts, and even to display query results in table rather than map form if preferred. As users have adjusted to consulting a computer screen instead of the old roadway information "Bibles," the SLD system has become widely used and is continually enhanced.
BUILDING ON THE SLD FRAMEWORK
As the maintenance and asset management group began to explore practical ways to collect highway maintenance data, the well-developed SLD system caught its attention. Even though the system did not contain the maintenance information that the Division of Operations Support required, it did house the highway geometry data needed as a framework. Also, during the SLD project, NJDOT and Baker had refined cost-effective data collection techniques. The Division of Operations Support determined that developing an effective HMMS would be feasible if it built on the existing SLD system and engaged Baker for maintenance data collection. Data on highway maintenance features would be referenced so that it could be stored in the SLD data warehouse and accessed by either the SLD system or the HMMS as needed. Integrating data would allow the most cost-effective data collection, eliminate duplicate data, and provide each group with the precise information it needed.
DATA COLLECTION TECHNIQUES
Field crews began collecting HMMS data on the 660 miles of NJDOT roadways and 335 miles of ramps in the northern region of the state in October 2001--aformidable task. Two-person teams, a driver and a data recorder, work from a vehicle equipped with a distance measuring instrument (DMI), a GPS receiver, and a laptop running Baker's GeoLink[R] 6.1 for Windows software, which links attribute data to GPS coordinates. The teams slowly drive assigned routes identifying features that would require maintenance, such as guiderail or inlets. The data recorder presses a button to tag the location of a particular feature, and the software receives and logs the GPS coordinates for that point. The GPS coordinates are saved for later use in precisely mapping ramps and other mainline roadway geometry changes. The coordinates are adjusted using real-time differential correction, meaning that signals from GPS satellites are calibrated against signals from a series of land-based GPS stations, adjusting the coordinates within a n accuracy of one meter. GeoLink prompts the data collector for details on the highway feature, such as its type and which side of the road it is on. The data collector also rates the feature's condition as good, fair, or poor.
For most highway work, data on the exact linear location of a feature is even more valuable than GPS coordinates. The roadway itself is easily located and crews simply need to know how far down the highway to travel to find a particular noise wall or curb. Existing mileposts give a general indication of location, but are not intended to be exact. Instead, the data recorder tracks linear distance with a DMI, essentially a highly precise and flexible odometer. The DMI also assists in adjusting the exact start and end points of a route, as well as the linear measurements of points along the route, since curves in a roadway make the distance traveled in opposing lanes slightly different.
Although data collection is as automated as possible and most work can be done from the vehicle, the process is time-consuming. Each roadway segment requires three passes, since it would be impractical to correctly log and rate every one of the 18 possible types of maintenance features in one pass from a moving vehicle. Instead, data collection teams focus on certain similar types of elements during each pass.
On the first pass, they look for guiderail, curbs, fences, noise walls, sidewalks, and impact attenuators (crash barriers). The second time through, teams capture data on inlets, manholes, headwalls, outfalls, basins, ditches, and channels. Pass three includes delineators (reflectors), shoulders, and island pavements. On divided or particularly busy highways, crews must make three passes each direction to collect all maintenance data. In addition to mainline roadways, the teams are collecting data on ramps, which were not previously part of the SLD system. Ramps require four passes, since teams must also record roadway geometry details.
For the safety of the data collection crews performing a mobile operation along busy roadways, a NIDOT crash truck follows behind the Baker vehicle. Coordination with local NJDOT maintenance crews, heavy traffic, and travel time to data collection sites can all cause delays. It typically takes a two person team a full day to collect data on 10 miles of roadway. Initial HMMS data collection for the entire state-- 2,325 miles of roadway and 885 miles of ramp--is expected to be complete by September 2003.
On any project with multiple data collectors, consistency is a concern. Before the actual HMMS data collection began, Baker and NJDOT developed a manual to guide data collection, particularly the condition rating. However, because the project team kept the ratings simple--good, fair, and poor--it eliminated most of the gray area and achieved a high level of consistency among data collectors.
The data collection manual is fairly comprehensive, although occasionally there may be an item, such as a rarely-used end treatment for guiderail, that does not fit any of the established categories. In such a case, crews take a digital photo of the feature and GeoLink tags the photo to the feature's exact location. The photo can then be analyzed and the feature properly categorized by team members back at the office.
In the field, the software captures data into a Microsoft Access database. At the end of the week, data collection crews compress the week's data using WinZip [R], then upload the file to a secure project Web site. Staff in the office pull the new data down and run it through a program that checks for anomalies, requiring validation of any field data that does not correlate with known source data. Once the data is "clean," it is merged into the SLD SQL Server database.
The team had to make a few adjustments to display maintenance features on the straight line diagrams. The original SLDs depicted three miles of roadway per page. To make more space available to display features, the team changed the scale to display just one and a half miles per page. Baker also created custom stencil objects in Microsoft Visio to expand the legend and graphical features displayed on the SLD.
Transforming the data into a format that was usable by the HMMS system was a more complex task, mainly because of the differences in the way states number and identify roadways. For example, in certain states, when a route crosses a county line, the milepost numbering starts over again at zero. In New Jersey, however, the miles are counted continuously from the beginning to the end of the route, no matter where the county lines fall. Since the core HMMS software was created to accommodate the first type of route numbering, Baker had to artificially segment the New Jersey data according to county lines.
New Jersey's standard route identifier (SRI) system presented another challenge. Mainline routes are assigned a ten-digit SRI, and each ramp is referred to by the mainline number plus another seven digits that distinguish the ramp. Many states, however, use shorter alpha-numeric codes to identify their highways, and ramps are rarely assigned a unique number. The HMMS did not readily accommodate New Jersey's numbering system, so Baker had to write programs to translate the New Jersey SRIs into a format that the HMMS could import.
SLD FEATURE INVENTORY AND HMMS AT WORK
Feature inventory data is uploaded to the database as it is collected and validated, so NJDOT can begin to use the HMMS even before statewide data collection is finished. When complete, the HMMS will be used by nearly all levels of staff, from the assistant commissioner in charge of maintenance operations to the regional crew supervisors. Annual planning and budgeting will be faster and more accurate, due to the availability of valid roadway feature information and real-time cost tracking. Managers can determine, for example, how many linear feet of guiderail are in poor condition and will require replacement in the next fiscal year. Then, using work activity standards that automatically calculate the unit cost per linear foot of replacing guiderail based on planned labor, equipment, and material, managers can develop a reasonable indication of funding requirements.
Crew supervisors will post daily work reports on the system, which aids senior management and also provides detailed historical information to each crew supervisor. This detail in report history is especially valuable since in New Jersey, field supervisors are encouraged to treat their individual areas as their own businesses. The HMMS tracks labor, equipment, and materials costs; budget balances; work orders; signalized intersection inspections; and even fleet inventory along with actual roadway information. The system uses automated interfaces to upload and download source data from the departmental employee, financial, and fleet management systems. Since all maintenance-related information is kept in one system, there is less paperwork, fewer data entry errors, and it is easier to keep data updated and consistent.
COMING SOON: STATEWHDE SLDS
Systems such as NJDOT's SLD and HMMS lend themselves to continual enhancement, mainly through the steady addition of new data. NJDOT is building the SLD system in a hierarchical manner, having collected data on state highways first, then toll authority roadways, then the 500-series county roads, and then the 600-series and any other roadways eligible for federal funds. These major highways form a 12,000-mile network throughout the state. In April, NJDOT assigned three contracts to collect SLD data on the rest of the roadways in the state, an additional 25,000 miles. As part of these contracts, local roads will each be assigned an SRI number, will be mapped and put into the DOT's GIS, and will eventually display most of the same features now available for the state's major routes. Within two years, NJDOT expects to have every public roadway mapped and logged into its system.
The addition of local roadways is important even though NJDOT is not directly responsible for their maintenance. Each year, NJDOT must report the state's total roadway miles to the FHWA as part of the basis for federal highway funds. Like most states, NJDOT had a good handle on the highways under its own jurisdiction, but local entities could not always keep up with changes in their total roadway network.
Determining total statewide roadway miles was a reasonable estimate rather than a precise measure. With all public roadways entered into the SLD system, reporting will be simple and exact. Mapping all roadways will also assist in reporting to other agencies. In the event of a disaster, for example, the Federal Emergency Management Agency allocates disaster recovery funding based in part on the miles of roadway affected, making accurate reporting essential.
In addition to federal authorities, NJDOT makes its roadway information available to county and local governments. A metropolitan planning organization, for example, can start with the NJDOT roadway geometry framework and then concentrate its own data collection on the additional detailed information needed for local planning or maintenance purposes.
Public access to the NJDOT road-way inventory is generally encouraged, especially since the original SLD effort was largely funded by the FHWA and is a matter of public record. While the public cannot directly access and manipulate the SLD system, static maps showing basic roadway geometry data are available on NJDOT's Web site. As data collection for the HMMS project continues, most feature data will be made available to the public in some form. Within NJDOT, read-only access is quite broad to encourage the use of the SLD system. The authority to update data is more limited to protect data integrity.
FUTURE HMMS ENHANCEMENTS
The HMMS will also be enhanced through the steady addition of data. While Baker completes data collection on the first 18 types of maintenance features, the maintenance and asset management group will gather internal source data to populate another 35 tables with features such as bridges, fiber optics, variable message signs, rest areas, maintenance facilities, dams, specialized lighting, and weather information sensors. Links to additional graphical elements, such as drawings or digital field photos, are also planned. For example, it would be useful to field crews and engineers to click on a section of the SLD and view the drainage system, showing pipe sizes and types, inlet and pipe locations, and even to view a video of the interior of the pipe.
The system has the potential to benefit many other NJDOT divisions by integrating data. Accident data, for example, could be referenced using the same SRI and mile point system, and then integrated into the SLD data warehouse. Accident and feature data could then be easily cross-referenced, with relational queries comparing accident locations to guiderail location and condition, for example. Such an enhancement is more of a coordination challenge than a technical challenge, since accident information is obtained from local police departments and tracked by a separate bureau of NJDOT.
The ambitious scope of the HMMS project makes maintaining the data an enormous project itself. For now, the maintenance and asset management group's plan is to conduct a review every six months of features that change frequently. Many of the other system updates, particularly on the condition of the features, will be semi-automated as crew supervisors fill out daily work reports.
KEYS TO SUCCESS
While the commitment of the immediate project team has been essential to the success of NJDOT's HMMS project, the system's value has been considerably enhanced by the early and frequent involvement of end users and field experts. Focus groups within NJDOT's permits group helped determine that the HMMS system's prototype permits module design would require customization before it would suit NJDOT's business processes.
While data collection and integration can be daunting obstacles to any maintenance and asset management system effort, an even more complex obstacle can be territorial divisions within organizations. NJDOT's HMMS is moving forward due to cooperation between two bureaus that, a year ago, rarely worked together. As maintenance management systems become more common, the organizations that build the most valuable and well-used systems will be those that understand the power of integrating data and encourage a culture of cooperation.
Mr. Callahan manages NJDOT's Bureau of Project Support and Engineering and is leading the HMMS effort. He may be reached at Jeff. Callahan@dot.state.nj.us. Mr. Carl is Section Chief of NJDOT's Roadway Systems Section, and has led the development of the SLD system since 1996. He may be reached at Jim. Carl@dot.state.nj.us. Mr Weaver is Project Manager Michael Baker Jr., Inc., for the HMMS data collection and integration project. He may be reached at email@example.com.
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|Title Annotation:||New Jersey Department of Transportation|
|Author:||Callahan, Jeffrey J.; Carl, Jim; Weaver, Kirk A.|
|Article Type:||Cover Story|
|Date:||Sep 1, 2002|
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