Data-driven urban planning and transportation optimization
Table Of Contents
<p>1. Introduction<br> 1.1 Urban Planning and Transportation Challenges<br> 1.2 Objectives and Scope of the Project<br>2. Data Collection and Analysis<br> 2.1 Urban Mobility Data Sources and Integration<br> 2.2 Data Preprocessing and Quality Assurance<br>3. Traffic Flow Modeling and Simulation<br> 3.1 Traffic Dynamics and Congestion Patterns<br> 3.2 Simulation Models for Traffic Optimization<br>4. Public Transit Planning and Optimization<br> 4.1 Demand Forecasting and Route Optimization<br> 4.2 Multi-modal Integration and Interconnectivity<br>5. Infrastructure Design and Resource Allocation<br> 5.1 Data-driven Urban Infrastructure Planning<br> 5.2 Sustainable and Resilient Urban Development<br></p>
Thesis Abstract
<p> This project aims to leverage data-driven approaches to optimize urban planning and transportation systems. The project will utilize data analytics, simulation models, and optimization algorithms to improve traffic flow, public transit efficiency, and urban infrastructure design. By analyzing large-scale urban data, the project seeks to inform evidence-based decision-making for sustainable and resilient urban development. <br></p>Thesis Overview
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