For this product, the research team will ascertain the potential value of CV data to transportation agencies via a detailed assessment of various CV datasets obtained from both public and private sources. Many resources are already available that describe the immediate, individual vehicle safety applications, such as emergency brake light warning and red-light violation warning. This product will not revisit these materials; rather, it will focus on using the CV data for managing roadways and planning future operations.
Open in full window: Big Data in Freight Transportation Planning and Operations
For NCHRP 08-119, the team is developing a series of four guidance documents that will compile and present the challenges, lessons learned, steps taken, and recommended actions when integrating and using crowdsourced data. Each of these four documents, developed sequentially, will focus on a different type of crowdsourced data. It will also center on many real-time and archived uses of that data, either independently or through integration with other data.
Network conflation is a continuing necessity and difficult task for agencies using geo-referenced maps and databases. Conflation is the process of identifying common points and references to reconcile two or more geo-datasets across overlapping areas. Because of differences in scales, resolutions, and accuracy or conventions, data referring to the same location often do not have the same geographic reference and cannot be combined easily. This leads to defining “near enough” criteria to expect two references to represent the same feature.
Multiple agencies have or are beginning to make use of smart work zone data to enhance their work zone data and to integrate these data with their WZDx data feeds. Agencies like the Iowa Department of Transportation and the Kentucky Transportation Cabinet already have case studies on integrating smart work zone data. As part of the NCHRP 08-119 project, the team will develop detailed case studies, lessons learned, and associated recommendations resulting from the efforts of IDOT, KYTC, and several WZDx Demonstration project awardees.
As part of NCHRP 08-119, the team will develop a series of short documents detailing the outputs and lessons learned from developing TIM big data use cases and associated data pipelines. This product will consist of the following stand-alone documents:
As part of NCHRP 08-119, efforts are underway to develop a series of resources that will help practitioners integrate big data with other datasets to address freight transportation planning, operations challenges, and needs. Specifically, four resources are currently under development:
As part of NCHRP 08-119, the team will develop a pilot to demonstrate how to improve the collection and integration of transit ITS data into an ICM system to better inform traveler modal decisions. Data from transit systems, such as passenger counts and occupancy (automated passenger counting (APC) systems), can supplement automatic vehicle location (AVL) and schedule adherence data. This will better inform and potentially influence modal shift from personal vehicle use.
As part of the NCHRP 08-119 project, a Data Sharing Resources Guide for Shared Mobility Data was developed. This guide provides an overview of key issues facing the management of shared mobility data, detailed guidance on the resources (standards, policies, model documents, organizations, etc.) that are available, and a detailed assessment of the information or other support that each resource provides.