Applications of new data sources in integrated transport planning and public transport operations (Softcopy is also available)
Jacob, Amal John (PUT21032)
Applications of new data sources in integrated transport planning and public transport operations (Softcopy is also available) - 2023 - xvii,85p.
Table of contents
Undertaking i
Certificate iii
Acknowledgments v
Abstract vii
Table of contents ix
List of figures xiii
List of tables xvi
Chapter : 1 Introduction 1
1.1 Background 1
1.2 Aim and Objectives 1
1.3 Problem Statement 2
1.4 Research Design and Methodology 2
1.5 Scope 4
1.6 Limitations 4
Chapter : 2 Literature Study 5
2.1 Types of Data Sources 5
2.2 Manual Survey (Traditional Data Sources) 6
2.2.1 Challenges of Manual Survey 7
2.3 ITMS and IOT 7
2.3.1 ITMS (Public Transportation) 8
2.3.2 IOT Devices 11
2.4 Crowdsourced Data 14
2.4.1 Google Maps API 15
2.4.2 Telecom Data 16
2.4.3 Social Media Data 18
2.4.4 Data from other Applications 19
2.5 Open-Source Data 19
2.6 Big Data 21
2.6.1 Tools for BigData Analysis 22
2.7 Literature Analysis 23
2.7.1 Alternatives for Household Survey 23
2.7.2 Alternatives for PT System Study 24
2.7.3 Alternatives for Other Surveys 24
Chapter : 3 Case Studies 26
3.1 Traffic Video Analytics 27
3.1.1 Traffic surveillance cameras 27
3.1.2 Types of surveillance cameras 28
3.1.3 Technical Methods for video analytics 29
3.1.4 Background subtraction Method 30
3.1.5 Steps for Background subtraction Method 30
3.2 Video Analytics through Data from Sky: 30
3.2.1 Process of analysing the video 31
3.2.2 Tools in DataFromSky Viewer Software 31
3.2.3 Analysis through DataFromSky 33
3.2.4 Applications of Video Analytics 35
3.3 Mobile Network big data in Colombo 36
3.4 Drone Survey 39
3.5 OSM Map Extraction 40
3.5.1 BBBike (OSM Extractor) 41
Chapter : 4 General Transit Feed Specification 42
4.1 What is GTFS? 43
4.2 Applications of GTFS Data in India 44
4.2.1 Need of model framework for analysing GTFS data 45
4.2.2 Why R Programming? 45
4.3 Model framework for analysing GTFS data. 46
4.3.1 Basic Overview of the city transit system 46
4.3.2 Interactive maps showing transit routes. 47
4.3.3 Interactive maps showing transit bus stops with no of routes and daily bus trips. 49
4.3.4 Average speed 52
4.3.5 Calculating average headway for each route 54
4.3.6 Number of trips per hour for each line 55
4.3.7 Network Analysis 56
4.3.8 Transit centrality measures 57
4.3.9 Validation of the framework 58
4.3.10 Conclusion 59
Chapter : 5 Challenges and Future research directions 61
5.1 Challenges for GTFS Implementation in India: 61
5.2 Future Research Directions for GTFS Data Analysis: 62
5.3 Conclusion 62
Chapter : 6 Bibliography 64
Chapter : 7 Appendix 69
P TH-2740 / JAC
Applications of new data sources in integrated transport planning and public transport operations (Softcopy is also available) - 2023 - xvii,85p.
Table of contents
Undertaking i
Certificate iii
Acknowledgments v
Abstract vii
Table of contents ix
List of figures xiii
List of tables xvi
Chapter : 1 Introduction 1
1.1 Background 1
1.2 Aim and Objectives 1
1.3 Problem Statement 2
1.4 Research Design and Methodology 2
1.5 Scope 4
1.6 Limitations 4
Chapter : 2 Literature Study 5
2.1 Types of Data Sources 5
2.2 Manual Survey (Traditional Data Sources) 6
2.2.1 Challenges of Manual Survey 7
2.3 ITMS and IOT 7
2.3.1 ITMS (Public Transportation) 8
2.3.2 IOT Devices 11
2.4 Crowdsourced Data 14
2.4.1 Google Maps API 15
2.4.2 Telecom Data 16
2.4.3 Social Media Data 18
2.4.4 Data from other Applications 19
2.5 Open-Source Data 19
2.6 Big Data 21
2.6.1 Tools for BigData Analysis 22
2.7 Literature Analysis 23
2.7.1 Alternatives for Household Survey 23
2.7.2 Alternatives for PT System Study 24
2.7.3 Alternatives for Other Surveys 24
Chapter : 3 Case Studies 26
3.1 Traffic Video Analytics 27
3.1.1 Traffic surveillance cameras 27
3.1.2 Types of surveillance cameras 28
3.1.3 Technical Methods for video analytics 29
3.1.4 Background subtraction Method 30
3.1.5 Steps for Background subtraction Method 30
3.2 Video Analytics through Data from Sky: 30
3.2.1 Process of analysing the video 31
3.2.2 Tools in DataFromSky Viewer Software 31
3.2.3 Analysis through DataFromSky 33
3.2.4 Applications of Video Analytics 35
3.3 Mobile Network big data in Colombo 36
3.4 Drone Survey 39
3.5 OSM Map Extraction 40
3.5.1 BBBike (OSM Extractor) 41
Chapter : 4 General Transit Feed Specification 42
4.1 What is GTFS? 43
4.2 Applications of GTFS Data in India 44
4.2.1 Need of model framework for analysing GTFS data 45
4.2.2 Why R Programming? 45
4.3 Model framework for analysing GTFS data. 46
4.3.1 Basic Overview of the city transit system 46
4.3.2 Interactive maps showing transit routes. 47
4.3.3 Interactive maps showing transit bus stops with no of routes and daily bus trips. 49
4.3.4 Average speed 52
4.3.5 Calculating average headway for each route 54
4.3.6 Number of trips per hour for each line 55
4.3.7 Network Analysis 56
4.3.8 Transit centrality measures 57
4.3.9 Validation of the framework 58
4.3.10 Conclusion 59
Chapter : 5 Challenges and Future research directions 61
5.1 Challenges for GTFS Implementation in India: 61
5.2 Future Research Directions for GTFS Data Analysis: 62
5.3 Conclusion 62
Chapter : 6 Bibliography 64
Chapter : 7 Appendix 69
P TH-2740 / JAC