EXECUTIVE SUMMARY

BACKGROUND

Intelligent Transportation Systems (ITS) generate massive amounts of performance and condition data that characterize how the transportation system is operating in real-time or near real-time. These data are used primarily by transportation agencies to implement operation and travel management strategies such as ramp metering, incident management, signal control, provision of traveler information, and commercial vehicle operations.

The increasing deployment of ITS and amount and variety of ITS-generated data offer great potential for longer-term transportation management purposes involving such tools as transportation trends, analysis, and predictive models. ITS-generated data are of the same basic nature as the data traditionally used in these applications, but ITS-generated data are typically collected at much higher levels of geographic and temporal resolution. These increased levels of resolution can not only provide data for existing applications but also will enable the development of more sophisticated applications.

As ITS matures, there is a growing recognition by the transportation profession that the data generated by ITS can be used for multiple purposes beyond ITS-related control strategies. Recognizing this potential, the Federal Highway Administration embarked on a concentrated effort to advance the state of the practice in archiving ITS-generated data for future uses. The first activity was the addition of the Archived Data User Service (ADUS) to the National ITS Architecture in September 1999. During the process of incorporating ADUS into the Architecture, stakeholders identified a series of applications to which ITS-generated data are relevant, including:

• Transportation Planning - congestion management, corridor studies, long-range plan development (especially input to travel demand forecasting models)
• Traffic Operations - evaluation of control strategies, sort-range planning of operational strategies
• Transit Operations and Planning - routing and scheduling
• Air Quality Analysis - inputs to emissions models
• Safety Planning - crash verification and exposure estimation.

In addition to these applications, the Architecture paid particular attention to the ability of ITS to supply data to traditional transportation information systems, which are used to support all of the functions mentioned above.

The overall objective of this study is to determine the potential of ITS to supply data to traditional transportation data systems by examining data element definitions from both realms in detail. Specifically, data elements in terms of both their basic definition and their valid values are examined to identify two types of matches:

• "Direct" matches - in which there is a 1:1 correspondence between an ITS data element and its traditional counterpart or the traditional data element can be directly derived from the ITS data element.
• "Near" matches - in which the data element definitions are close but not exact, and some form of degree of translation is required in order to derive the traditional data element from its ITS counterpart.

The main purpose of this exercise is to identify data elements that need to be reconciled ("harmonized") by the data owners. In addition to pointing out the specifics of the required harmonization, a discussion of how ITS data can improve the timeliness of data submittals and overall quality of traditional data systems is included.

STUDY APPROACH

The approach taken was to obtain data dictionaries for ITS and traditional sources and match data elements one-by-one, looking for commonalities. The main ITS sources considered for this study were:

• National ITS Architecture (NA) data dictionary is included as part of the "logical architecture."
• Traffic Management Data Dictionary (TMDD) developed by the Institute of Transportation Engineers (ITE).
• P1512 Incident Management Data Dictionary (P1512) being developed by the Institute of Electrical and Electronics Engineers (IEEE).
• Advanced Traveler Information System (ATIS) Data Dictionary being developed by the Society of Automotive Engineers (SAE).
• Commercial Vehicle Information Exchange Window (CVIEW) developed as part of the Commercial Vehicle Information Systems and Networks (CVISN) by the Federal Motor Carrier Safety Administration (FMCSA).
• National Transportation Communications for ITS Protocol (NTCIP) object definitions for Data Collection and Monitoring (DCM) devices developed by the working group.

The traditional transportation data systems examined were those maintained by the U.S. Department of Transportation (USDOT). Data dictionaries for the following government reporting systems were obtained:

• Highway Performance Monitoring System (HPMS)
• Traffic Monitoring Guide (TMG)
• Highway Safety Information System (HSIS)
• National Bridge Inventory (NBI)
• National Transit Database (NTD)
• Fatality Analysis Reporting System (FARS)
• General Estimates System (GES)
• Motor Carrier Management Information System (MCMIS)
• National Governors' Association (NGA) Truck Crash Data Elements
• Hazardous Materials Incident Reporting System (HMIRS)
• Grade Crossing Inventory System (GCIS)
• Transportation Surveys
  • Nationwide Personal Transportation Survey (NPTS)
  • Vehicle Inventory and Use Survey (VIUS)
  • American Travel Survey (ATS)
• EPA Air Quality Models

All data dictionaries were transferred into an Excel spreadsheet and a macro procedure was developed for identifying matches and near matches. However, it became clear that the procedure was not capturing all of the possible matches - too many matches were going undetected. Therefore, it was decided to perform the matching manually, which proved to be very time consuming.

SUMMARY OF FINDINGS

The following are the main findings from the study.

ITS has the potential to supply data to traditional government reporting systems, though the number of data elements that can be matched is relatively small. The results of the matching exercise showed some commonality in overall data definitions, but the majority of data in government reporting systems have no counterpart in the current ITS realm. This means that existing data collection programs can be enhanced, but not replaced, by ITS sources. The strength of current ITS data for government reporting uses is in characterizing roadway conditions (throughput and speeds) and in providing details on crashes. However, government-reporting systems require much more information beyond these data types.

Inconsistencies in definitions and valid values limit the potential of ITS to provide data to government reporting systems. The matching exercise revealed that about half of the common data elements can be translated directly from ITS sources to government reporting systems. The other half of common data elements have discrepancies that either must have translation schemes developed (some of these may compromise data quality) or the data elements must be harmonized between the two realms.

Several key ITS data types cover a broad range of government reporting systems and can improve the quality and timeliness of data reported to these systems. ITS-generated traffic data and information collected at crash scenes can provide a valuable supplement - and often a replacement to - existing data collection efforts. ITS traffic data, because of its ubiquitous coverage, can greatly enhance government reporting systems requiring traffic summaries. This can be in terms of replacing short count estimates with continuous counts and in the development of more reliable adjustment factors.

Use of ITS-generated traffic data in air quality modeling has the potential to greatly improve emissions estimates. The continuous nature of ITS-generated traffic data can provide much more refined estimates of VMT. Further, direct speed estimates from ITS sources are greatly preferred to modeled speeds for a number of reasons, especially since the effects of queuing and noncapacity factors (incidents, weather, fluctuations in demand, and work zones) are directly measured.

Transportation surveys - aimed at capturing household travel and the operating characteristics of trucks - are not well matched to ITS data sources. The structure of the current ITS data dictionaries is more suited to capturing system characteristics and providing traveler services and assistance rather than capturing individual travel behavior.

Much of the potential of ITS data for archived purposes lies beyond their ability to provide data to government reporting systems. Use of ITS-generated data in government reporting systems is but one of many applications that will benefit from data archival.

RECOMMENDATIONS FOR IMPROVING ITS DATA INTEGRATION

Consideration should be given to sharing control of ITS roadway detectors between Traffic Management Center (TMC) and traditional travel monitoring personnel. Travel monitoring personnel would get the benefit of additional data. TMC personnel would benefit from the improved maintenance and calibration of field equipment.

ITS standards developers need to involve traditional personnel in future activities. The three data dictionaries reviewed in this project are either complete or nearing completion. However, standards are continuously revised and it is recommended that developers reach out to the traditional transportation community so that revisions account for their concerns. In the interim, owners of traditional government reporting systems may want to develop "cross-walks" for converting ITS-generated data for their systems.