Within these pages, readers will find information on new data sources for transportation planning, their associated challenges, and incorporating these data into the planning process.
Today, transportation planners are faced with an enormous range of available data and of methods and models to predict or analyze transportation activity. Finding and applying the right models to the given problem and informing those models with appropriate data has become an increasingly challenging process. While there is a demand for data and methods that allow more finely grained forecasts and models, this need must be balanced against the broad scale outputs and products that are necessary. The ability to accurately model detailed data must be balanced against the need to identify broader trends and a range of likely scenarios. This will evaluate the resiliency of plans and transportation performance goals in relation to potential social and environmental volatility.
The rise of new data sources and determining how best to incorporate them into the transportation planning process is a major area of research and consideration. At the same time, the desire to integrate private and third party datasets into the regional and community planning process is associated with a number of challenges. The following list contains a number of specific challenges associated with evolving travel behavior (considering such influences as new modes and TNCs) and integrating new data resources into the planning process:
08-119 Research Products:
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.
This report reviews recent advances in harnessing big data to understand travel behavior and inform travel demand models. Analyzes the existing data-mining methods that enable these collected mobility traces to inform transport demand models.
This paper introduces big datasets, concepts, knowledge, and methods used in traditional transportation planning as well as modern data science.
This paper presents guidelines for transportation planners and travel modelers on how to (1) evaluate the extent to which cell phone location data and associated products accurately depict travel, (2) identify whether and how these extensive data resources can be used to improve understanding of travel characteristics and the ability to model travel patterns and behavior more effectively, and (3) support practitioners’ evaluation of the strengths and weak
Integrating Shared Mobility into Multimodal Transportation Planning: Improving Regional Performance to Meet Public Goals
This paper synthesizes noteworthy practices (e.g. data access and sharing, integrating shared mobility into modeling and forecasting, etc.), identifies challenges and opportunities, and provides recommendations for future research needed.
A follow-up report to Integrating Shared Mobility into Multimodal Transportation Planning: Improving Regional Performance to Meet Public Goals provides three in-depth case studies of how MPOs and their partners are interacting with shared mobility companies to integrate these new options into regional multimodal transportation networks, improving system performance and supporting regional goals.
Emerging Big Data Sources for Public Transport Planning: A Systematic Review on Current State of Art and Future Research Directions
A systematic review of 47 contemporary research papers related to the use of novel data sources in public transportation planning. There is particular focus on assessing the usability, strengths, and weaknesses of different emerging big data sources.
All Public Roads Geospatial Representation Study: All Roads Network of Linear Referenced Data (ARNOLD) Reference Manual
This document provides practical guidance and a handy Reference Manual to assist state DOTs in moving forward to meet the new Highway Performance Monitoring System (HPMS) requirements for the submittal of complete, all roads inventories and linear-referenced networks for every state and territory. This requirement is known as ARNOLD – the All Road Network of Linear Referenced Data.
A guideline to help transportation agencies improve their roadway and traffic data inventories, allowing extraction of such characteristics as connectivity of network elements. MIRE provides a platform for a common base to build travel model networks.
The HPMS is a national level highway information system that includes data on the extent, condition, performance, use, and operating characteristics of the Nation's highways. In general, the HPMS contains administrative and extent of system information on all public roads, while information on other characteristics is represented in HPMS as a mix of universe and sample data for arterial and collector functional systems.
Examines a proposed common framework for exchange of transportation data in eXtensible Markup Language, known as TransXML. The framework is designed to be used for developing, validating, disseminating, and extending current and future schemas.
GTFS defines a common format for public transportation schedules and associated geographic information. GTFS "feeds" let public transit agencies publish their transit data and developers write applications that consume the data in an interoperable way. The initial and main benefit of this standard included a free online trip planner available to the public to look up transit information and plan transit trips.
The scope of this committee includes research and technology transfer activities pertaining to statewide transportation planning data and information systems for all modes of transportation. A primary concern is the capability of information systems to integrate various transportation related data sources into a strategic multimodal information database for statewide transportation planning. The committee serves as a forum for discussion of current planning data activities.
This committee is interested in the design, collection, analysis, and reporting of transportation supply and demand data needed to support urban and metropolitan transportation planning efforts. In particular, the committee is interested in developing the data requirements of new and innovative techniques for measuring and monitoring the performance of metropolitan transportation systems and in evaluating changes in demographic and urban travel characteristics.