VIETNAM NATIONAL UNIVERSITY HO CHI MINH CITY HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY -------------------- HUỲNH LÊ PHÚ TRUNG A COMPUTATIONAL FRAMEWORK TO GENERATE SIDEWALK AND ROAD NETWORK REPRESENTATIONS FROM PRIMITIVE GEOSPATIAL INFORMATION TOWARD CONFLICTLESS PASSAGE AND TRAFFIC SAFETY Major: Engineering Physics Major code: 8520401 MASTER’S THESIS HO CHI MINH CITY, January 2024 THIS THESIS IS COMPLETED AT HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY – VNU-HCM Supervisor 1: PhD. Pham Tan Thi Supervisor 2: Prof. Hiroaki Wagatsuma Examiner 1: Assoc. Cao Thanh Tinh Examiner 2: PhD.
Nguyen Trung Hau This master’s thesis is defended at HCM City University of Technology, VNU- HCM City on January 28th, 2024 Master’s Thesis Committee: 1. Huynh Quang Linh 2. Nguyen Xuan Thanh Tram 3. Cao Thanh Tinh 4.
Nguyen Trung Hau 5. Phan Bach Thang Approval of the Chair of Master’s Thesis Committee and Dean of Faculty of Applied Physics after the thesis being corrected (If any). CHAIR OF THESIS COMMITTEE DEAN OF FACULTY OF APPLIED SCIENCE VIETNAM NATIONAL UNIVERSITY - HO CHI MINH CITY SOCIALIST REPUBLIC OF VIETNAM HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY Independence – Freedom - Happiness THE TASK SHEET OF MASTER’S THESIS Full name: Huỳnh Lê Phú Trung Student ID: 1970503 Date of birth: January 15, 1997 Place of birth: Tiền Giang Major: Engineering Physics Major ID: 8520401 I. THESIS TITLE (In Vietnamese): Một hệ thống tính toán xây dựng mạng lưới vỉa hè và đường bộ từ thông tin không gian địa lý nguyên thủy hướng tới lối đi thông thoáng và an toàn giao thông II.
THESIS TITLE (In English): A Computational Framework to Generate Sidewalk and Road Network Representations from Primitive Geospatial Information Toward Conflictless Passage and Traffic Safety III. TASKS AND CONTENTS: • Reconstruction of the sidewalk network. • Reconstruction of the road network to assist the finding of conflict areas between vehicles and sidewalk passengers. • Detection of conflict areas as a consistent extension of the road network.
THESIS START DAY: February 2023 V. THESIS COMPLETION DAY: December 2023 VI. SUPERVISOR Supervisor 1: PhD. Pham Tan Thi Supervisor 2: Prof.
Hiroaki Wagatsuma Ho Chi Minh City, …………………… SUPERVISOR HEAD OF DEPARTMENT Hiroaki Wagatsuma DEAN OF FACULTY OF APPLIED SCIENCE Acknowledgments I would like to express my deepest thanks to my supervisors, PhD. Pham Tan Thi and Professor Hiroaki Wagatsuma for their guidance, good advices, great support and even challenges. I have learned a lot from them that is very valuable for both my knowledge and personal growth. I would not complete this thesis without their immense support.
They always guilds me to the right direction. In addition, I would like to send my thanks to all members of Wagatsuma laboratory for their support and for the great time I have been there. i Abstract According to the Geospatial Information Authority of Japan (GSI), which is the national organization responsible for surveying and mapping the national land of Japan, various geospatial information has been prepared by different public/private organizations and those were provided depending on individual purposes. Since geospatial representations respectively have a certain degree of accuracy and quality, those are beneficial, while there exist differences in descriptions and measurements.
For the solution of such inconsistencies, GSI have organized the standard description of the geospatial information called “basic map information (BMI),” and maintained by collecting update information of those organizations on road and building constructions. Due to the circumstances, BMI is an authentic data and compositive data simultaneously, which is not always suitable for routing information of moving entities. In other words, edges of building, road and sidewalk are very accurate in the sense of combinations of primitive lines in BMI; however, a single building, connected road and consistent sidewalk are represented in multiple lines and there are no guarantees to link together depending on the meaningful unit semantically. In the aim to solve the problem, a computational framework was proposed in this study as an effective integration of methods in geometric computation.
Model-free approaches ignoring geometric properties are not effective in the sense of computational costs. On the other hand, too much empirical and heuristic approaches may provide a specialized solution, but it does not provide general perspectives and contribute less to a new discovery in science and advancements in engineering fields. Therefore, a general scheme was introduced to form individual solutions in the form of an algorithm of computation, which are provided by an integration of matrix operations and methods in geometric computation. The proposed methods were evaluated in missions of reconstructions of sidewalk and road networks and applied to the detection of conflict areas vehicles and sidewalk passengers such as pedestrians and wheelchairs.
ii Tóm tắt Theo như Cơ quan Thông tin Không gian Địa lý Nhật Bản (GSI), là tổ chức chịu trách nhiệm khảo sát và lập bản đồ quốc gia Nhật Bản, nhiều thông tin không gian địa lý khác nhau đã được các tổ chức công hoặc tư nhân khác nhau chuẩn bị và chúng được cung cấp tùy theo mục đích cá nhân. Vì các sự biểu diễn trong không gian địa lý có mức độ chính xác và chất lượng nhất định nên mặc dù bên cạnh các lợi ích thì vẫn tồn tại những khác biệt trong mô tả và đo lường. Để giải quyết những mâu thuẫn như vậy, GSI đã thiết lập một sự mô tả tiêu chuẩn về thông tin không gian địa lý được gọi là “thông tin bản đồ cơ bản (BMI)” và được duy trì bằng cách thu thập thông tin cập nhật của các tổ chức về đường bộ và công trình xây dựng. Mặc dù BMI là dữ liệu tổng hợp được xác thực, không phải lúc nào cũng phù hợp để sử dụng trong thông tin định tuyến của các thực thể chuyển động.
Nói cách khác, các cạnh của tòa nhà, đường và vỉa hè rất chính xác theo nghĩa kết hợp các đường nguyên thủy trong dữ liệu BMI, tuy nhiên một tòa nhà riêng biệt, những đường được kết nối và các vỉa hè được thể hiện bằng nhiều đường và không có gì đảm bảo tính liên kết với nhau thể hiện ý nghĩa về mặt ngữ nghĩa. Với mục đích giải quyết vấn đề, một khung tính toán đã được đề xuất trong nghiên cứu này, là sự tích hợp một cách hiệu quả của các phương pháp trong hình học tính toán. Các phương pháp tiếp cận không có mô hình bỏ qua các đặc tính hình học sẽ không hiệu quả về mặt chi phí tính toán. Mặt khác, quá nhiều phương pháp tiếp cận theo kinh nghiệm có thể cung cấp một giải pháp chuyên biệt, không cung cấp những giải pháp tổng quát và ít đóng góp cho những khám phá mới về khoa học và những tiến bộ trong lĩnh vực kỹ thuật.
Do đó, một sơ đồ được đề xuất trong nghiên cứu này, hình thành các giải pháp riêng lẻ dưới dạng thuật toán, được cung cấp bằng cách tích hợp các phép toán ma trận và các phương pháp trong hình học tính toán. Phương pháp đề xuất đã được đánh giá trong các nhiệm vụ tái thiết mạng lưới vỉa hè và đường bộ, và áp dụng để phát hiện các khu vực xung đột giữa các phương tiện và đối tượng di chuyển trên vỉa hè như người đi bộ và xe lăn. iii The Commitment I commit that this thesis “A Computational Framework to Generate Sidewalk and Road Network Representations from Primitive Geospatial Information Toward Conflictless Passage and Traffic Safety” is my research with support from my supervisors, PhD. Pham Tan Thi and Professor Hiroaki Wagatsuma.
The research content and results have never been published in any previous research works. Thesis author Huynh Le Phu Trung iv Content Acknowledgments. iii The Commitment. iv List of Figures.
vii List of Tables .x Table of Abbreviations. xi Chapter 1 Introduction .2 Related Past Works .4 Chapter 2 Basement Technologies .1 Geographic Information System (GIS) .1 GIS data types .2 Coordinate System in GIS .1 OpenStreetMap data format .2 Sidewalk information in OSM .3 Basic Map Information from GSI .1 How to download map data for GSI .2 BMI data format .15 Chapter 3 Methods for Sidewalk Data Management .1 Sidewalk Network Reconstruction .1 Problems in BMI data to describe sidewalks .2 Proposed Method 1: Node connection algorithm to integrate consistent segments in the sidewalk data.3 Proposed Method 2: Flipping algorithm to represent a consistent sidewalk .4 New data structure to represent sidewalks in a consistent way .2 Sidewalk Area Reconstruction .1 Extraction of road edge data .2 Geometric computation for target edge detection .3 Road network reconstruction .4 Conflict area identification .39 Chapter 4 Results and Discussion .1 Sidewalk network reconstruction .1 Integration of sidewalk data to represent a consistent path .2 Comparison of proposed methods .2 Sidewalk area reconstruction .1 Extraction of road edge extraction .2 Geometric computation for target edge detection .3 Road network reconstruction .1 Geometric computation for parallel line detection .2 Validation of road network reconstruction .4 Conflict area identification .66 vi List of Figures Figure 2. Geographic coordinate system (left) and Projected coordinate system (right) in GIS. OpenStreetMap data of an area of Kitakyushu, Japan.
OpenStreetMap with sidewalk data. Three types of data from GSI. Select the area for download. Select the data for dowload.
All data of basic items. BMI data displayed in QGIS. XML format of BMI data. Data structure of line segments for sidewalk representation in BMI data.
Sidewalk is represented by separated line segments. The flowchart of node connection algorithm. Sidewalks connect each other through end points. Sidewalk data of original BMI is displayed in MATLAB.
List of end points. Connectivity matrix of line segments in BMI sidewalk. Connectivity between two line segments. Direction in line segments of BMI sidewalk.
Flipping direction for the consistent line. Connection types of line segments in BMI data. The new data structure for sidewalks. The image of sidewalk and road edge data (photos partially from Google Map).
The idea for sidewalk area reconstruction. The concept of geometric computation for route maps. The sidewalk polygon reconstruction model. The target of sidewalk area reconstruction.
Problems in sidewalk area reconstruction. Conditions to extract the target part for sidewalk area reconstruction. The design of algorithm for sidewalk area reconstruction. The road network reconstruction model.
The design of algorithm for the road network reconstruction. Scenario 1 of overlapping of sidewalk and vehicle path (photos from Google Map and Street View). Scenario 2 of overlapping of sidewalk and vehicle path (photos from Google Map and Street View). Scenario 3 of overlapping of sidewalk and vehicle path (photos from Google Map and Street View).
Scenario 4 of overlapping of sidewalk and vehicle path (photos from Google Map and Street View). The idea for conflict management. The design of algorithm for conflict area detection. The part 1 of map of original BMI data.
The part 1 of map after applying proposed method. The part 2 of map of original BMI data. The part 2 of map after applying proposed method. Comparison of computational cost of two proposed methods.
The result of road edge data extraction. Sidewalk area reconstruction result for part 1 of the map. Sidewalk area reconstruction result for part 2 of the map. Sidewalk area reconstruction result for part 3 of the map .10 Sidewalk area reconstruction result for part 4 of the map.
Sidewalk area reconstruction result for part 5 of the map. Sidewalk area reconstruction result for part 6 of the map. Sidewalk area reconstruction result for the whole map. Road network reconstruction result for part 1 of the map .
