Logic-Driven Traffic Big Data Analytics [electronic resource] : Methodology and Applications for Planning / by Shaopeng Zhong, Daniel (Jian) Sun.

Logic driven traffic big data analytics: An introduction -- Statistical models and methods -- Spatial-temporal distribution model for travel origin-destination based on multi-source data -- Analyzing spatiotemporal congestion pattern on urban roads based on taxi GPS data -- A ride-sourcing group prediction model based on convolutional neural network.

This book starts from the relationship between urban built environment and travel behavior and focuses on analyzing the origin of traffic phenomena behind the data through multi-source traffic big data, which makes the book unique and different from the previous data-driven traffic big data analysis literature. This book focuses on understanding, estimating, predicting, and optimizing mobility patterns. Readers can find multi-source traffic big data processing methods, related statistical analysis models, and practical case applications from this book. This book bridges the gap between traffic big data, statistical analysis models, and mobility pattern analysis with a systematic investigation of traffic big data's impact on mobility patterns and urban planning.