Big Data Solutions for Transportation
Collection, Analysis, and Implementation
- 1st Edition - December 1, 2019
- Imprint: Elsevier
- Author: Satish Ukkusuri
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 1 4 3 5 5 - 1
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 1 4 3 5 6 - 8
The expanded and evolving use of big data in transportation applications has largely outpaced the ability of transportation professionals to keep up with the latest te… Read more
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The expanded and evolving use of big data in transportation applications has largely outpaced the ability of transportation professionals to keep up with the latest technological developments. Big Data Solutions for Transportation: Collection, Analysis, and Implementation helps readers properly collect, and analyze big data for use in developing, testing, and deploying successful transportation solutions.
The book synthesizes state of the art uses for big data, identifying new research directions for future studies. Big Data Solutions for Transportation: Collection, Analysis, and Implementation covers the rapid advances in supply and demand transportation platforms, such as Uber and Lyft, as well as how to interpret and apply the vast amounts of data collected from cell phones, social media, taxi cabs and other transit systems.
Big Data Solutions for Transportation: Collection, Analysis, and Implementation
provides readers with an understanding of how communities can apply big data to the latest infrastructure systems, improving quality of life, and expanding economic competition on local, regional, and national scales. The book combines a multitude of perspectives, developing a unifying set of research challenges and methodologies likely to impact transportation infrastructure systems for many years to come.- Applies a multidisciplinary perspective to transportation big data science, and its practical applications
- Explains the rapid advances in the observability of transportation assets and platforms matching supply and demand (such as Uber and Lyft)
- Explains how data from cell phones, social media, taxi cabs, and other transit systems are harnessed to help design critical infrastructure systems that are economically competitive and improve quality of life
- Combines engineering, computer science, state and local government, social science, physics, and network science perspectives, developing a unifying set of research challenges and methodologies likely to impact transportation infrastructure systems
Academic researchers and upper-level undergraduate and graduate students in transportation, systems, networks, modeling, and data analytics. Transportation practitioners tasked with policy, infrastructure, smart cities, and systems. Transportation public officials such as those working in government departments of transportation, state departments of transportation, transportation planners, and policy directors, etc.
- Edition: 1
- Published: December 1, 2019
- Imprint: Elsevier
- Language: English
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Satish Ukkusuri
Satish Ukkusuri is a Professor in the Lyles School of Civil Engineering at Purdue University, teaching courses in transportation systems and freight and logistics planning. He is a member of the Transportation and Infrastructure group at Purdue, and leads the University’s Interdisciplinary Transportation Modeling and Analytics Lab. He is a member of the Transportation Research Board’s (TRB) Transportation Network Modeling, and Freight Transportation Planning and Logistics committees. Dr. Ukkusuri has published nearly 250 peer reviewed journal and conference papers in a wide variety of transportation topics. He is on the Editorial Advisory Board of Elsevier’s Transportation Research: Part B and Transportation Research: Part C journals, and is an area editor for the journal, Networks and Spatial Economics.
Affiliations and expertise
Professor, Lyles School of Civil Engineering, Purdue University