State and other government planning agencies explore big data sources to facilitate better freight transportation planning and operations decision-making. However, limited funds, differing planning horizons, proprietary information, insufficient human resources, and misinformation about available data have resulted in challenges related to the acquisition, integration, and use of freight-related big data. The freight data decision tree is an interactive tool developed to illustrate how agencies can integrate and use big data sources to address freight planning and operational use cases.
Previous research has highlighted the need for an interoperable freight data architecture to help strengthen multimodal freight data collection efforts; enable interoperability between multiple systems; and aid with data accuracy verification, validation, gap identification, and integration for seamless exchange of information. While attempts have been made to address differences in freight data sources, as well as data collection, querying, and fusion methodologies, most studies address specific data sources or aim to address a specific use case. The Freight Data Interoperability Framework is a simplified, generic, and robust freight data querying methodology that data enthusiasts can leverage to encourage the implementation of an interoperable freight data architecture.
Crowdsourcing is the practice of addressing a need or problem by using technologies to enlist the services of many people. In the context of transportation, travelers generate crowdsourced data both passively and actively (e.g., using mobile navigation apps). Crowdsourcing can offer low-cost, high-quality operations data (e.g., traffic speeds, slowdowns, events, crashes) and improved situational awareness without the need for costly traffic monitoring technologies. This guide provides a practical understanding of how state and local transportation agencies can access and use the Waze for Cities data.
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 sometimes accuracy or conventions, data referring to the same location often do not have the same geographic reference and are challenging to combine. This leads to defining “near enough” criteria to expect two references to represent the same feature. The use of “near enough criteria,” while allowing several corresponding features to be merged effectively, is not perfect. LinkerAT is a prototype, open-source software tool for transportation agencies and their partners to conflate two different roadway network data sources.
Public agencies have a need to obtain data from shared mobility providers. Some of these data may be sensitive because they could reveal either personal details of users of the services or proprietary data, including trade secrets of the service providers. By implementing appropriate policies and procedures, agencies can appropriately protect sensitive data while using the appropriate data to meet their goals and objectives. Building on the information in the Shared Mobility Data: A Resource Guide, the purpose of the guide on Managing Sensitive Shared Mobility Data is to inform public agency managers and staff on issues relating to the protection of sensitive information that agencies may gather as part of their shared mobility programs.
The capabilities of data management systems have changed significantly since the roll out of the USDOT pilot ICM initiative in 2006. As such, this document is meant to provide an update on trends in effective data management principles and practices and use of data for ICMs to help inform transportation practitioners on key areas in the conceptualization, planning, and design of ICMs.
Shared mobility is the shared use of vehicles to provides travelers with short-term access to a travel mode on an as-needed basis. Its scope includes micromobility services such as bikesharing and electric scooter services, as well as carsharing, micro-transit, paratransit, Transportation Network Companies (TNCs), and traditional ride-hailing (taxi) services. Shared mobility services have grown rapidly within the last few years. Just as some cities were taken by surprise by TNCs and struggled to put in place regulatory frameworks, the same has occurred with dockless bikes and scooters in many localities. There is a clear need for public agencies to have data to better understand how all these services fit into the overall transportation network. The purpose of this guide is to provide public sector agencies with curated reference material to help plan for, manage, and use shared mobility data.
Crowdsourcing is the practice of addressing a need or problem by using technologies to enlist the services of many people. In the context of transportation, travelers generate crowdsourced data both passively and actively (e.g., using mobile navigation apps). Crowdsourcing can offer low-cost, high-quality operations data (e.g., traffic speeds, slowdowns, events, crashes) and improved situational awareness without the need for costly traffic monitoring technologies. This guide provides a practical understanding of how state and local transportation agencies can access and use the Waze for Cities data.
Roadway work zones can create hazardous conditions for motorists, pedestrians, and highway workers, and better, more accurate, and more timely data can reduce the risks of driving in work zones. Collecting, consolidating, and distributing this information, however, has been an ongoing challenge. The objective of Federal Highway Administration’s (FHWA) Work Zone Data Exchange (WXDx) initiative was to develop and promote the use of a common specification to collect and share data on work zone activities. This report presents case studies from five agencies on their past, on-going, and planned use of smart work zone technologies as a source of data for their WZDx feeds. The intended audience for this report includes state, regional, and local agencies seeking to use smart work zone technologies, as well as those looking to establish a WZDx feed and those integrating real-time data with other data sources, such as work zone planning and tracking systems. This report will assist agencies by highlighting recent and ongoing efforts by peer agencies; summarizing their challenges, lessons learned, and recommendations; and providing additional resources.
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.