\u003cp\u003e\u003ci\u003eData-Driven Solutions to Transportation Problems \u003c/i\u003eexplores 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.\u003c/p\u003e\u003cul\u003e \u003cli\u003eSynthesizes the newest developments in data-driven transportation science\u003c/li\u003e \u003cli\u003eIncludes case studies and examples in each chapter that illustrate the application of methodologies and technologies employed\u003c/li\u003e \u003cli\u003eUseful for both theoretical and technically-oriented researchers\u003c/li\u003e\u003c/ul\u003e
nl
en