CHAPTER 5

Summary and Recommendations for Future Research

NCHRP Project 08-119 involved three phases of research to develop tools, methods, and guidelines to assist transportation agencies in improving data sharing, integration, and management practices in support of better planning and operations decisions. Phase I of the research resulted in detailed operations and planning use cases that could benefit from improved data sharing, integration, and management practices, as evidenced through a comprehensive review of the literature and standards and interviews with a wide range of stakeholders. These findings are documented in the Phase I Summary available on the NCHRP 08-119 project page on the TRB website (https://apps.trb.org/cmsfeed/TRBNetProjectDisplay.asp?ProjectID=4543) and within the NCHRP 08-119 web-based resource library on NOCoE’s website (https://data.transportationops.org/), which was the primary output of Phase II of the project.

Phase III of the project resulted in 11 stand-alone research products selected by the project panel to address some of the challenges and needs identified in Phase I. Each of these research products is provided in a separate chapter in Part II of this report. Each chapter contains recommendations for agencies with respect to improving data sharing, integration, or management practices, depending on the specific topic of the chapter. Additionally, there are recommendations for future research that would build on the research conducted for this project as well as the research products developed.

Recommendations for Future Research

Recommendations Based on Data Application Areas and Use Cases

The recommendations for future research discussed in the following sections are based on various data application areas and use cases from this research.

Waze for Cities Data

Opportunities exist to increase data sharing between Waze and departments of transportation (DOTs) (e.g., DOTs could provide alternate routes/detours to Waze to avoid excessive or inappropriate vehicles on local or neighborhood roads) and to better align the Waze for Cities data with agency needs for traffic management (e.g., enhanced features that would provide more detailed data from users, such as partial road closures or specific lane blockages). Development of a Waze interface for use in traffic management centers is another future opportunity.

Data to Support Traffic Incident Management Use Cases

Traffic incident management (TIM) data are used more often for research, planning, and highway design, and users require more TIM-relevant data and more specific data (e.g., lane

closures, number of lanes in a given location). The ability to better leverage the many different existing and emerging TIM-relevant data sources, both public and private, could improve TIM practices and the impacts of incidents on mobility and safety. There are needs to

• Continue to research new and innovative technologies and approaches for collecting, sharing, managing, and using incident data, as the data and computing technology continue to innovate rapidly.
• Gather responder partners (transportation, law enforcement, fire and rescue, emergency management services, and towing and rescue) to explore opportunities, strategies, and approaches to break down silos associated with the collection, sharing, and use of data; foster the use and integration of existing data (e.g., state traffic records, computer-aided dispatch data, automatic vehicle location data); and work to overcome privacy/sensitivity issues associated with this data.
• Address the various data standards, specifications, and formats used across response disciplines. This research could include conducting comprehensive data inventories, identifying commonalities and differences in the data, addressing data quality issues, creating data quality processes and targets, and establishing ways to harmonize the data to improve data sharing and integration.
• Develop and deliver TIM data training workshops for DOTs and TIM operations.

Sensitive Shared Mobility Data

Research is needed into the state of the practice on specific technical protection controls and methods in use for protecting sensitive (both private and proprietary) data collected by public agencies to manage shared mobility services. For example, how and to what extent is encryption being used? What data are encrypted, and are the data encrypted when at rest, when being transferred, or both? What is the current state of the practice and what are current effective practices for aggregating data to protect sensitive information (e.g., bin sizes, acceptable values of k for k-anonymization)? Differential privacy is a relatively new technique for protecting privacy. Research on whether and how it is being used to protect sensitive mobility data and effective practices would be informative.

Smart Work Zone Data

It is recommended that the state of the practice with respect to smart work zone devices and associated data be revisited in 3 to 4 years, to include what progress has been made, what technologies are being deployed, how the data are being used, and what barriers limit deployment and use of smart work zone equipment and the Work Zone Data Exchange (WZDx) specification. Additionally, recommendations are needed for accelerating the deployment of smart work zone devices and the WZDx to achieve as broad a geographic coverage as possible and distribution of real-time work zone information to vehicles, whether it be through coordination with automakers and/or third party technology/mobile app vendors.

Integrated Corridor Management Data

• There is a need to review memorandums of understanding (MOUs) for integrated corridor management (ICM) to manage data sharing between partner agencies, including establishing best practices and developing templates to guide the agencies in drafting their own MOUs.
• There is a need to explore possible new sources of data, both near real-time and static, to inform ICM systems (e.g., third-party location-based services, fleet data), including implications, opportunities, and scenarios for using these data sources.

Connected Vehicle Data

Rapid technology development and deployment is a challenge, as new technologies may change data flows, data types, and use cases. Continuing research to support new, emerging technologies is important to keep pace with technology development. Additionally,

• Future research could focus on the use of vehicle probe and cellular-vehicle-to-everything (C-V2X) data and their relevant use cases. Expanding the use of probe data provides the highest chance of receiving real-time, high-resolution, high-accuracy data for transportation system management and operations. The penetration rate of connected vehicles (CVs) with onboard units (OBUs) will continue to grow, but not to the penetration rates of probe data. Focusing on C-V2X communications follows the momentum of industry development.
• Transportation operators may be more interested in seeing practical applications of CV data, for example to validate field sensor measurements or extend the capabilities of an ITS network through the real-time analysis of CV data. Further research could focus on developing use case–specific analysis methodologies to help support a broader understanding and proof of using CV data in this way.

Recommendations to Expand Products Developed by the Research Team

In addition to the written products that constitute Part II of this report, the team developed two web-based tools and a freight data interoperability framework. Following are recommended next steps and opportunities to continue the development of these products or expand them to increase their scope and value.

Freight Data Decision Tree

Opportunities to expand this tool to include other use cases include the following:

• Incorporating datasets on other modes of transport (e.g., waterway, rail, air, pipeline).
• Developing a comparison table between multiple datasets to illustrate disparity between the datasets.
• Incorporating a limited number of data schema crosswalks to address the disparities between datasets. These crosswalks would map the elements in one data schema to the equivalent element in another data schema.
• Showing discrepancies in results for different data vendors for the same analysis.

Freight Interoperability Framework

Potential next steps for the freight interoperability framework include developing a complete web-based application using the methodologies developed from this study and enhancing the recommendations provided through further testing of additional use cases.

LinkerAT Application

Considerations for next steps for LinkerAT include the following:

• Technical support (educational, operational) to agencies using LinkerAT, which could include
  • Support for code defects and, with the GeoJSON platform, ensuring correct data handling and integration with LinkerAT;
  • Specifically addressing the custom state coding required; and
  • Orientation and training documents and sessions, along with tutorials in the specific implementation steps and pathways required for product application.
• In using the product, agencies will likely encounter ways to make improvements (both in processing logic and interface), which would create a need for version enumeration and management. Furthermore, multiple versions of the application could be in use, so effective tracking of version updates and differences would also be important and might require expansion of the deployment platform and practices.
• There may be an opportunity to apply the LinkerAT cross-indexing model/process to a range of similar problems. Some investigation of the feasibility and expected complexity and cost of

• such adaption would be needed. Depending on the elements of the problem under consideration, expansion of the code database for support of additional and optional models also would be needed. This could also lead to application-specific documentation and related support products and activities.

The Benefit of Collaboration

Additionally, from a global standpoint, transportation agencies could benefit greatly from more opportunities to actively collaborate with other transportation and partner agencies, as well as with private-sector partners, to keep pace with the rapidly evolving technology and data space. Collaboration should include conversations about data sharing, standards, data quality, and the sharing of code so that applications could more easily be implemented without duplication of effort. While examples of such communities exist, research is needed to identify the specific topics that could benefit the most from this type of collaboration (i.e., what is of interest), recommend methods for establishing and promoting community participation, and lay out effective community support structures and practices to foster success.