6.0 Conclusions and Recommendations
Satisfying data quality and data accuracy requirements is a key step in the implementation of real-time information programs. Data quality is a key factor in the effectiveness of congestion management and traveler information system applications that rely on data from various sources. This white paper identified the data quality measures that should be considered within ITS applications and how they can be applied to existing systems. The study initially provided an overview of previous studies followed by a discussion of data quality issues associated with public and private sectors, providing specifications for data quality measures for sample real-time travel information applications, and finally identifying the needs of a real-time ITS program.
The paper examined the quality of traffic data in existing real-time ATIS applications for both the public and private sector. For instance, the 511 Deployment Coalition employed the accuracy, timeliness, reliability, consistency of presentation, and relevancy of information as important parameters to enhance data quality and consistency across various systems. However, in many cases the algorithms used by the private sector are not made public, presumably to promote a competitive advantage, and thus verification and validation of these systems is extremely limited.
Six primary interfaces and their associated applications were defined in the Interim Guidance on Information Sharing Specifications and Data Exchange Formats report. The study summarized sample applications related to real-time ATISs and their data requirements. Real-time ATIS applications require various traffic-related parameters. Each application requires a unique set of traffic-related parameters, different levels of data flow, and database management. This paper provides recommended data quality measures for three widely utilized traffic-related parameters, travel time, speed, and weather information. These recommendations were defined for each of the six data quality measures, accuracy, completeness, validity, timeliness, coverage, and accessibility.
ITS technologies are evolving fast and new data collection technologies are being deployed. In addition, data collection methods are frequently updated within ITS applications. The growing deployments of ITS projects require extensive evaluation of data quality and more extensive validation of these applications is recommended. Moreover, the development of data quality standards for different applications as well as data collection equipment will become an important aspect of real-time ATIS applications. The proposed standardization could increase the quality and accuracy of the data collected, decrease the effort needed to transfer data, and increase the reliability of field equipment.
