Description
Integrating Activity-Based Models with Mobile Phone Data: Advances in Traffic Modeling and Multi-Agent Simulation analyzes the path from the observation to prediction using traffic big data. The book explores the refined identification method of individual travel chains in the diversified and complex urban travel environment, reconstructing the structure and algorithms of Activity-based Models or ABM based on the characteristics identified by mobile phone signaling data. Final sections develop an activity decision-making and microscopic behavior simulation platform. Users will find this to be a resource that supports urban and regional traffic management optimization and traffic planning using traffic big data.- Discusses highly debated issues in the fields of commodities, sustainable (ESG) finance, and sustainable development- Applies various levels of analysis and research methods, leading to both macro- and micro-level conclusions- Includes a highly detailed empirical analysis, utilizing a comprehensive database throughout the book, with information on all ETCs—regardless of their activity status- Utilizes the example of a market for exchange-traded commodities (ETCs), merging the academic and practical perspectives
Table of Contents
1. Introduction2. Review of Travel Characteristic Recognition and Activity-Based Modeling3. Technical Principles and Evaluation of 4G/5G Mobile Phone Signaling Data4. Accurate Travel Chain Identification Based on Mobile Phone Signaling Data5. ABMs Combined with Mobile Phone Signaling Data6. Activity Scheduling and Multi-Agent Micro-Simulation Platform7. Outlook
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