The National Academies

NCHRP 20-102(14) [Final]

Data Management Strategies for CV/AV Applications for Operations
[ NCHRP 20-102 (Impacts of Connected Vehicles and Automated Vehicles on State and Local Transportation Agencies--Task-Order Support) ]

  Project Data
Comments: NCHRP Project 08-119 has been expanded in scope and budget to include this project

This project is combined with NCHRP Project 08-119 Data Integration, Sharing, and Management for Transportation Planning and Traffic Operations

As owners and operators of transportation infrastructure, state and local agencies maintain databases of relevant information. Currently, this includes crash records, design “as built” plan sets, traffic signal timing parameters, construction schedules, and many more. CV/AV applications need certain information about the environment and infrastructure in a variety of time scales. Signal timing status is obviously needed in real time, traffic sign placements might be updated daily, and the next month’s construction projects might be updated weekly. Some AV developers are currently storing detailed digital 3-D maps for reference during automated driving. Perhaps such an asset of a public agency could be valuable to many applications, but this requires maintenance. Some agencies provide access to various sets of information electronically, others are available through records requests, and yet others are not available at all. Agencies vary widely in their ability to provide access to certain information now and in the future. There is a need to identify the information that is necessary for agencies to maintain to plan, enable, and enhance CV/AV applications; develop standard formats and standard systems where they would be helpful and do not already exist; and provide guidance for agencies on how to implement strategies for collecting, updating, maintaining, and disseminating the information.

Similarly, a variety of information about travel conditions can be collected by CV/AV enabled vehicles and can be shared with agencies to enhance their operations. Agencies currently struggle to collect good information about origin-destination flows, traffic volumes, travel delays, pavement surface quality, crash and anomaly location, and location of work zones, among others. There is a need to identify standards for collection of this information, how it is communicated to agencies, stored, maintained, updated, and eventually used to enhance transportation planning, operations, and maintenance. 

The Safety Pilot Model Deployment and the upcoming additional CV pilot deployments will continue to contribute valuable information on the design and implementation of management systems for dissemination of agency-owned data and ingestion of CV/AV generated information for agency operations. The scalability of these systems needs to be estimated in this research as the penetration level of CV/AV technology advances from several thousand vehicles to several millions. Similarly, each CV pilot deployment will only deploy a small subset of the 50+ envisioned applications. Scalability of the back-end system to eventually accommodate up to 50 applications will also need to be explored in this research.
The objective of this research was to develop guidance on operational data management strategies for typical agencies. This research will be coordinated with Task 13 that is looking at the planning realm.

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