Special Issue "Transportation Data"

A special issue of Data (ISSN 2306-5729).

Deadline for manuscript submissions: closed (30 November 2017).

Special Issue Editor

Prof. Dr. Shlomo Bekhor
E-Mail Website
Guest Editor
Faculty of Civil and Environmental Engineering Technion - Israel Institute of Technology Haifa 32000, Israel
Interests: Transportation Planning; Network Optimization; Demand Modeling; Behavioral Models; Intelligent Transport Systems

Special Issue Information

Dear Colleagues,

Transportation analysis and travel demand forecasting are heavily dependent on reliable transportation data, which provide inputs to estimate and calibrate the mathematical models that represent decisions people make related to travel. Most models need several data sources from different surveys. Examples are household surveys, intercept surveys, traffic and person counts, land use data, etc.

In recent years, big data provides new ways of gathering novel information about transport infrastructure from passenger and vehicle movements and allows for a shift from passive approaches to active crowd-sourcing with innovative transport solutions.

We would like to invite you to submit articles addressing the process of transportation data collection, acquisition, processing, and management, so that these data will be (re)used by other scholars and add value to the preliminary published results from them. Of particular interest are big data applications in transportation.

Prof. Dr. Shlomo Bekhor
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Data is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (1 paper)

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Research

Open AccessArticle
Congestion Quantification Using the National Performance Management Research Data Set
Data 2017, 2(4), 39; https://doi.org/10.3390/data2040039 - 25 Nov 2017
Cited by 1
Abstract
Monitoring of transportation system performance is a key element of any transportation operation and planning strategy. Estimation of dependable performance measures relies on analysis of large amounts of traffic data, which are often expensive and difficult to gather. National databases can assist in [...] Read more.
Monitoring of transportation system performance is a key element of any transportation operation and planning strategy. Estimation of dependable performance measures relies on analysis of large amounts of traffic data, which are often expensive and difficult to gather. National databases can assist in this regard, but challenges still remain with respect to data management, accuracy, storage, and use for performance monitoring. In an effort to address such challenges, this paper showcases a process that utilizes the National Performance Management Research Data Set (NPMRDS) for generating performance measures for congestion monitoring applications in the Birmingham region. The capabilities of the relational database management system (RDBMS) are employed to manage the large amounts of NPMRDS data. Powerful visual maps are developed using GIS software and used to illustrate congestion location, extent and severity. Travel time reliability indices are calculated and utilized to quantify congestion, and congestion intensity measures are developed and employed to rank and prioritize congested segments in the study area. The process for managing and using big traffic data described in the Birmingham case study is a great example that can be replicated by small and mid-size Metropolitan Planning Organizations to generate performance-based measures and monitor congestion in their jurisdictions. Full article
(This article belongs to the Special Issue Transportation Data)
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