Data-driven solutions to transportation problems / edited by Yinhai Wang, Ziqiang Zeng.
| Other author | Wang, Yinhai. |
| Other author | Zeng, Ziqiang (Assistant professor) |
| Format | Electronic |
| Publication Info | Amsterdam, Netherlands ; Cambridge, MA, United States : Elsevier, [2019] |
| Description | xxvi, 273 pages: illustrations, maps ; 23 cm |
| Supplemental Content | Full text available from eBook - Social Sciences 2018 |
| Subjects |
| Contents | 1. Overview of data-driven solutions -- 2. Data-driven energy efficient driving control in connected vehicle environment -- 3. Machine learning and computer vision-enabled traffic sensing data analysis and quality enhancement -- 4. Data-driven approaches for estimating travel time reliability -- 5. Urban travel behavior study based on data fusion model -- 6. Urban travel mobility exploring with large-scale trajectory data -- 7. Public transportation big data mining and analysis -- 8. Simulation-based optimization for network modeling with heterogeneous data -- 9. Network modelling and resilience analysis of air transportation : a data-driven, open-source approach -- 10. Health assessment of electric multiple units. |
| Abstract | Data-Driven Solutions to Transportation Problems explores the fundamental principle of analyzing different types of transportation-related data using methodologies such as the data fusion model, the big data mining approach, computer vision-enabled traffic sensing data analysis, and machine learning. The book examines the state-of-the-art in data-enabled methodologies, technologies and applications in transportation. Readers will learn how to solve problems relating to energy efficiency under connected vehicle environments, urban travel behavior, trajectory data-based travel pattern identification, public transportation analysis, traffic signal control efficiency, optimizing traffic networks network, and much more. |
| Bibliography note | Includes bibliographical references and index. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Genre/form | Electronic books. |
| LCCN | 2020304698 |
| ISBN | 9780128170267 (paperback) |
| ISBN | 0128170263 (paperback) |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | Access Content Online | ✔ Available |