Upcoming TCRP research project should benefit GTFS-ride efforts

[John Levin]

During the most recent GTFS-ride Consortium webinar, I presented about the TIDES Project (Transit ITS Data Exchange Specification).  The presentation and webinar recording are available here: https://www.gtfs-ride.org/consortium/meetings.html 

I am happy to report that TCRP recently announced that they will fund a research project along these very same lines.    The full TCRP announcement is here: http://onlinepubs.trb.org/onlinepubs/tcrp/docs/finalannouncement2019.pdf   The funded project G-18 is summarized below.

I think this project will ultimately provide benefits to GTFS-ride and agencies that want to publish their data in the GTFS-ride format.  One goal of the research project is to help develop the data pipelines necessary to get data from source systems into standard formats, and to address data quality and data aggregation needs along the way. This research will also need to address the data matching challenges, such as how to link data to GTFS schedules, that have been identified in earlier posts.  

Stay tuned for more information.  Feel free to also follow the TIDES Project group for updates.  https://groups.google.com/forum/#!forum/tidesproject 

John Levin

Metro Transit

Minneapolis-St. Paul

■ Project G-18 Improving Access and Management of Transit ITS Data

Research Field: Administration

Allocation: $350,000

TCRP Staff:Lawrence Goldstein

 

Archived data from bus and rail intelligent transportation systems (ITS) is an extremely valuable resource for transit service planning and management. Vehicle location and passenger activity data from automatic vehicle location (AVL), automatic passenger counter (APC), and automatic fare collection (AFC) systems are used to provide essential insight into transit operations and to inform decision making to increase the efficiency, productivity, and safety of transit service. These data sets are also key elements in the big data analytics activities needed to link transit and other modes within the broader shared mobility service sector.

 

There are, however, significant challenges for transit agencies in accessing and using this data. Many agencies can’t get to the data at all or don’t understand the data they have. Data validation and quality control, integration and matching across various data sets, and aggregating data are all difficult, as is developing the types of reports, tools, and analytics that really inform decision makers. Even when transit agencies, researchers and consultants do address these challenges, they have difficulty sharing their work with their peers in the industry because the same types of data are managed very differently among transit agencies. The result is that transit ITS data is rarely used to its full benefit.

 

Creating a common approach to accessing and managing archived transit ITS data would facilitate the development and exchange of data management practices, of advanced reports and tools, and of new analytical techniques among transit agencies. Without this assistance, this effort would be too complex, too time-consuming, too costly, or even out of reach. A common definition of data structures for transit ITS data is needed.

 

The objective of this research is to develop a common approach to accessing and managing archived transit ITS data that:

• Can be connected to data from many different existing systems,
• Addresses current data access, data quality, and data integration challenges
• Is flexible to meet differing needs of transit agencies and other users of transit ITS data,
• Will be continually improved, and shared across the industry, and
• Facilitates exchange of reports, tools, and analytical techniques based on transit