CHAPTER 4: CONCLUSION

4.1 SUMMARY OF FINDINGS

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. A matching exercise was conducted comparing data elements in the Federal government reporting systems with three current ITS data dictionaries and the National ITS Architecture. The results showed there was 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. For crash data, current systems are populated almost entirely from police accident reports (PARs). It has been observed that data quality has suffered because of the excessive demands placed on police at a crash scene - data collection often takes a lower priority than attending to victims and traffic control. However, as coordinated incident response becomes more widespread - and electronic messages are transferred between parties - much of the data that eventually ends up on PARs can be collected automatically.

Use of ITS-generated traffic data in air quality modeling has the potential to greatly improve emissions estimates. The travel activity input requirements of EPA's MOBILE6 model are more detailed than in previous versions of the model. 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 non-capacity 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. It is true that some ITS technologies are capable of tracking travel patterns, but to date this has not been the focus of ITS standards efforts.

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.

4.2 RECOMMENDATIONS FOR IMPROVING ITS DATA INTEGRATION

Consideration should be given to sharing control of ITS roadway detectors between TMC and traditional travel monitoring personnel. Both parties would benefit under such an arrangement. Travel monitoring personnel would get the benefit of additional data. TMC personnel would benefit from the improved maintenance and calibration of field equipment. (Traditional data collectors have accumulated a wealth of knowledge on these matters.) It might be possible to structure the arrangement so that only "strategic" detectors are subject to joint control - maintaining detector stations every ½ mile might overwhelm travel monitoring personnel and the data at that resolution may not be necessary for every traditional application.

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.