Logic-Driven Traffic Big Data Analytics: Methodology and Applications for Planning

Description

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. Foreword by Tien Fang Fwa Foreword by Feng Xiao Preface Acknowledgments Contents About the Authors 1 Logic-Driven Traffic Big Data Analytics: An Introduction 1 Integrated Theory of Urban Land Use and Transportation 1.1 Introduction of Concepts Related to Transportation and Land Use 1.2 Mechanism of Interaction Between Urban Transportation and Land Use 1.3 Aim of Integrating the Development of Urban Land Use and Transportation 2 Empirical Analysis of the Interactive Relationship Between Urban Land Use and Transportation Systems 2.1 Transit-Oriented Development Mode: Stockholm, Sweden 2.2 Hand-Shaped City Planning Mode: Copenhagen, Denmark 2.3 Urban Sprawl Development Mode: New York, United States 2.4 Tide Transportation Development Mode: Dalian, China 3 Models and Methods of Integrating Urban Land Use and Transportation 3.1 Spatial Econometrics 3.2 Spatial Statistical Analysis Methods 3.3 Multivariate Statistical Analysis Methods 3.4 Methods for Evaluating Policy Effectiveness 4 Summary of Contents References 2 A Spatio-temporal Distribution Model for Determining Origin–Destination Demand from Multisource Data 1 Introduction 2 Literature Review 2.1 Research on the Application of Topic Models in Transportation 2.2 Research on the Built Environment 3 Discovery of Activities in a Region 3.1 Map Segmentation 3.2 Topic Model 4 Spatio-temporal Distribution Mode of OD Demand 4.1 Extraction of the Basic Factors of Urban Built Environment Attributes 4.2 Model Selection 4.3 SAR Modeling 4.4 Analysis 5 Conclusion References 3 Spatiotemporal Evolution of Ridesourcing Markets Under the New Restriction Policy: A Case Study in Shanghai 1 Introduction 2 Data and Methods 2.1 Data Description and Pre-process 2.2 Two-Level Growth Model 2.3 Modeling Variables 3 Results and Discussions 3.1 Descriptive Results 3.2 Analytic Results 4 Conclusions References 4 A Regression Discontinuity-Based Approach for Evaluating the Effect of Exclusive Bus Lanes on Average Vehicle Speeds 1 Introduction 2 Literature Review 2.1 Exclusive Bus Lane 2.2 Regression Discontinuity 3 Methodology 3.1 Introduction to RD and Description of Variables 3.2 RD Model 4 Case Study 4.1 Study Region 4.2 Data Collection 4.3 Analysis Process 5 Results and Analysis 5.1 Bus Regression Results 5.2 Taxi Regression Results 6 Conclusion References 5 Analyzing Spatiotemporal Congestion Pattern on Urban Roads Based on Taxi GPS Data 1 Introduction 2 Data Preparation 2.1 Data Collection 2.2 Data Processing 3 Clustering of Road Segments 3.1 Fuzzy C-means Clustering 3.2 Clustering Result 4 Spatial Analysis of Road Segments 4.1 Geographical Detector 4.2 MORAN’s I 4.3 Spatial Regression of Road Segments 5 Conclusion and Recommendations References 6 Travel Time Estimation Based on Built Environment Attributes and Low-Frequency Floating Car Data 1 Introduction 2 Description of a Floating Car System 2.1 Composition of a Floating Car System 2.2 Advantages of Floating Car Systems 3 Methodology 3.1 Relationship Between the Number of Reports Sent by a Floating Car and Travel Time 3.2 Relationship Between Travel Time and the Built Environment Attributes 3.3 Distribution of Travel Time 4 Case Study 4.1 Study Area 4.2 Correction of Floating Car Data 4.3 Parameter Selection and Estimation 4.4 Analysis of Results 4.5 Test of Parameter Values 4.6 Calculation of Travel Time 5 Conclusion References 7 Exploring the Spatially Heterogeneous Effects of Urban Built Environment on Road Travel Time Variability 1 Introduction 2 Literature Review 2.1 Urban Built Environment and Travel Behaviour 2.2 Research on Spatial Heterogeneity 2.3 Research on Road Travel Time 3 Case Study 3.1 Selected Study Region 3.2 Data Collection 3.3 Descriptive Statistics of Variables 4 Model Formulation 4.1 Global Regression Model 4.2 GWR Model 5 Results and Analysis 5.1 Results and Analysis of the Global Regression Model 5.2 Estimated Results and Analysis of the GWR Model 6 Method Application and Policy Implications 7 Conclusions References 8 Taxi Driver Speeding: Who, When, Where and How? A Comparative Study Between Shanghai and New York 1 Introduction 2 Methodology 2.1 Overview of the DREI Method 2.2 Data 2.3 Measure and Variables 3 Result Analysis 3.1 Comparisons of Taxi Speeding in Shanghai and NYC: Who Is Speeding? 3.2 Analysis of Driver Characteristics on Speeding Frequency: Who Speeds the Most? 3.3 GLM Analysis of Determinant Factors: When, Where, and How? 4 Discussion References 9 Effects of Congestion on Drivers’ Speed Choice: Assessing the Mediating Role of State Aggressiveness Based on Taxi Floating Car Data 1 Introduction 1.1 State-Trait Theory 1.2 Aim and Objective 2 Statistical Methods 2.1 Data Description 2.2 Driver Type Classification 2.3 Mediation Analysis 2.4 Moderated Mediation Analysis 3 Model Implementation and Validation 3.1 Model Implementation 3.2 Model Validation 4 Discussion 5 Conclusions References 10 Analysis of the Spatio-temporal Distribution of Traffic Accidents Based on Urban Built Environment Attributes and Microblog Data 1 Introduction 2 Literature Review 2.1 Research on Methods for Accident Detection 2.2 Research on the Law of Accidents 3 Methodology 3.1 Selection of Study Region 3.2 Data Collection 3.3 GWR Model 4 Results and Analysis 4.1 OLS Model Results and Analysis 4.2 GWR Model Results and Analysis 5 Conclusion References 11 Taxi Hailing Choice Behavior and Economic Benefit Analysis of Emission Reduction Based on Multi-mode Travel Big Data 1 Introduction 2 Data and Taxi Choice Models 2.1 Data and Attributes 2.2 Binary-Nomial (BNL) Model and Related Attributes 2.3 Metro-Taxi BNL Choice Model 2.4 Mobike-Taxi Choice Model 3 Development of Localized Emission Model 4 Emission Reduction Schemes and Assessment 5 Conclusions References 12 Assessing Built Environment and Land Use Strategies from the Perspective of Urban Traffic Emissions: An Empirical Analysis Based on Massive Didi Online Car-Hailing Data 1 Introduction 2 Materials and Data 2.1 Didi Service GPS Data 2.2 Data Processing 2.3 Traffic Volume Estimation 2.4 Calculation of NOx Line Source Emission 3 Result Analysis and Discussion 3.1 Clustering Analysis Based on Road Segment Emission Factors 3.2 Spatiotemporal Characteristics of Emission Pattern 3.3 Correlations Between Atmospheric Concentration (NO2) and Line Source Emission 4 Conclusions References