With increased connectivity between vehicles, sensors, systems, and mobile devices, unexpected and unparalleled amounts of data are being added to the transportation domain at a rapid rate. Within these pages, readers will find information related to the integration and management of data from connected vehicles and devices. 

Connected vehicle technologies aim to tackle some of the biggest challenges facing the surface transportation industry in the areas of safety, mobility, and environment. Connected vehicles could dramatically reduce the number of fatalities and serious injuries caused by crashes on roads and highways. Anonymous signals in connected vehicles will help generate new data about how, when, and where vehicles travel. Connected vehicle technologies will generate real-time data that drivers and transportation managers can use to make green transportation choices. 1

Data from connected vehicles have tremendous potential to offer new insights. This has the ability to identify unique solutions for delivering services and will fundamentally alter the transportation sector. However, the volume and speed at which these data are generated, processed, stored, and sought for analysis are unprecedented. They are too large, too varied in nature, and will change too quickly to be handled by the traditional database management systems of most transportation agencies. Instead, modern, flexible, and scalable “big data” methods to manage these data need to be adopted by transportation agencies if the data are to be used to facilitate better decision-making.

08-119 Research Product:

Using Connected Vehicle Data for Transportation System Management

Connected Vehicle (CV) data have multiple use cases for transportation planning, safety management, and operations. This document is a primer on establishing uses of CV data for these purposes. The scope of the primer includes an overview of CV systems that produce data, the expectation of that data, methodologies for using that data, and planning, safety and operations use cases. This document discusses these topics in the context of two types of transportation management: vehicular system management and pedestrian system management.

Additional Resources:

Connected Vehicle Pilot Deployment Program Phase 2, Data Management Plan – Wyoming

This resource presents the Data Management Plan (DMP), which describes the data that will be collected and how the data will be managed throughout the Wyoming CV Pilot. The DMP will also define a framework for sharing the data with USDOT, the Research Data Exchange and the Independent Evaluator.

Connected Vehicle Pilot Deployment Program Phase 2, Data Management Plan - New York City

This resource represents a data management plan that delineates all of the data types and data treatment throughout the New York City Connected Vehicle Pilot Deployment (NYC CVPD). This plan includes an identification of the New York City connected vehicle pilot privacy-related data, its security treatment and the necessary filtering, anonymization and obfuscation requirements needed for distributing the data for Independent Evaluator (IE), USDOT and researcher use.

Integrating Emerging Data Sources into Operational Practice: State of the Practice Review

This report provides agencies responsible for Transportation Systems Management and Operations (TSM&O) with an introduction to successful Big Data tools and technologies that can be used to aggregate, store, and analyze new forms of traveler-related data that may be useful for operations.

NCHRP 08-116 Framework for Managing Data from Emerging Transportation Technologies to Support Decision-Making

This NCHRP report identified over 70 CAV projects across the Untied States. In a survey of a subset of these projects, responses were rather incomplete on topics including data management, data openness, data sensitivity, and data retention. Interviews were conducted with 11 state and local transportation agencies and a stakeholder workshop was conducted with 15 state and local agencies.

Integrating Emerging Data Sources into Operational Practice: Opportunities for Integration of Emerging Data for Traffic Management and TMCs

The purpose of this report is to 1) Identify how big data tools and technologies can be used in traffic management systems or TMCs; 2) Develop potential use cases for integrating big data technology and tools into traffic management systems or TMCs; 3) Assess how connected vehicle and traveler related data could be used to enhance the operation of traffic management systems or TMCs; 4) Analyze how the sharing of data with other TMCs, systems, connected vehicles and travelers; and agency business proce

Integrating Emerging Data Sources into Operational Practice: Capabilities and Limitations of Devices to Collect, Compile, Save, and Share Messages from CAVs and Connected Travelers

This report describes requirements, technical issues, technologies, and practices that will be necessary to collect, process, store, use and share large volumes of messages from road side equipment (RSE) to the traffic management centers (TMCs). These recommendations could find their way into data sharing standards for connected and automated vehicles (CAV) that could better define practices.

USDOT Connected Vehicle Pilot Projects

In 2015, the USDOT awarded cooperative agreements to three pilot sites to implement a suite of connected vehicle applications and technologies. One of the key goals of the CV Pilot program is to produce and provide Open Data from the pilots to the public in a quick and useful manner. This will enable research into the effectiveness of emerging ITS technologies, preliminary development of third-party applications, and harmonization of data across similar collections.

CV Pilot Deployment Program Driving Towards Deployment: Lessons Learned from the Design/Build/Test Phase 

This program describes the sensitivities with the types and amount of data that need to be collected. Additionally discusses the need for a data governance framework that provides a metadata standard and outlines how data will be collected, managed, and archived.