交通問題のデータサイエンス Data-Driven Solutions to Transportation Problems

Wang, Yinhai/ Zeng, Ziqiang

Elsevier Science Publishing Co Inc（2018/12発売）

• 製本 Paperback:紙装版/ペーパーバック版／ページ数 299 p.
• 言語 ENG
• 商品コード 9780128170267
• DDC分類 629.04

Full Description

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.

Contents

1. Overview of Data-driven Transportation Science2. Data-driven Energy Efficient Driving Control in Connected Vehicle Environment3. Machine Learning and Computer Vision-Enabled Traffic Sensing Data Analysis and Quality Enhancement4. Data Driven Approaches for Estimating Travel Time Reliability5. Urban Travel Behavior Study Based on Data Fusion Model6. Urban Travel Mobility Exploring with Large-Scale Trajectory Data7. Public Transportation Big Data Mining and Analysis8. Data Driven Gating Control for Network Based on Macroscopic Fundamental Diagram9. Simulation-Based Optimization for Network Modeling with Heterogeneous Data10. Network Modeling and Resilience Analysis of Air Transportation: A Data-Driven, Open-Source Approach