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Sensys: a Smartphone-Based Framework for ITS Applications

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Sensys: a Smartphone-Based Framework for ITS Applications Old Dominion University ODU Digital Commons Computer Science Theses & Dissertations Computer Science Fall 2017 SenSys: A Smartphone-Based Framework for ITS applications Abdulla Ahmed Alasaadi Old Dominion University, [email protected] Follow this and additional works at: https://digitalcommons.odu.edu/computerscience_etds Part of the Computer Sciences Commons Recommended Citation Alasaadi, Abdulla A.. "SenSys: A Smartphone-Based Framework for ITS applications" (2017). Doctor of Philosophy (PhD), Dissertation, Computer Science, Old Dominion University, DOI: 10.25777/6s3w-1646 https://digitalcommons.odu.edu/computerscience_etds/34 This Dissertation is brought to you for free and open access by the Computer Science at ODU Digital Commons. It has been accepted for inclusion in Computer Science Theses & Dissertations by an authorized administrator of ODU Digital Commons. For more information, please contact [email protected]. SENSYS: A SMARTPHONE-BASED FRAMEWORK FOR ITS APPLICATIONS by Abdulla Ahmed Alasaadi B.Sc. February 2003, University Of Bahrain, Bahrain M.Sc. 2005, Lancaster University, England A Dissertation Submitted to the Faculty of Old Dominion University in Partial Fulfillment of the Requirements for the Degree of DOCTOR OF PHILOSOPHY COMPUTER SCIENCE OLD DOMINION UNIVERSITY December 2017 Approved by: Tamer Nadeem (Director) Kurt Maly (Member) Michele Weigle (Member) Mecit Cetin (Member) ABSTRACT SENSYS: A SMARTPHONE-BASED FRAMEWORK FOR ITS APPLICATIONS Abdulla Ahmed Alasaadi Old Dominion University, 2018 Director: Dr. Tamer Nadeem Intelligent transportation systems (ITS) use different methods to collect and pro- cess traffic data. Conventional techniques suffer from different challenges, like the high installation and maintenance cost, connectivity and communication problems, and the limited set of data. The recent massive spread of smartphones among drivers encouraged the ITS community to use them to solve ITS challenges. Using smartphones in ITS is gaining an increasing interest among researchers and developers. Typically, the set of sensors that comes with smartphones is utilized to develop tools and services in order to enhance safety and driving experience. GPS, cameras, Bluetooth, inertial sensors and other embedded sensors are used to detect and analyze drivers' behavior and vehicles' motion. The use of smartphones made the data collection process easier because of their availability among drivers, the set of different sensors, the computation ability, and the low installation and maintenance cost. On the other hand, different smartphones sensors have diverse characteristics and accuracy and each one of them needs spe- cial fusion, processing, and filtration methods to generate more stable and accurate data. Using smartphones in ITS faces different challenges like inaccurate readings, weak GPS reception, noisy sensors and unaligned readings. These challenges waste researchers and developers time and effort, and they prevent them from building accurate ITS applications. This work proposes SenSys a smartphone framework that collects and processes traf- fic data and then analyzes and extracts vehicle dynamics and vehicle activities which can be used by developers and researchers to create their navigation, communica- tion, and safety ITS applications. SenSys framework fuses and filters smartphone's sensors readings which result in enhancing the accuracy of tracking and analyzing various vehicle dynamics such as vehicle's stops, lane changes, turn detection, and accurate vehicle speed calculation that, in turn, will enable development of new ITS applications and services. iv Copyright, 2018, by Abdulla Ahmed Alasaadi, All Rights Reserved. v ACKNOWLEDGMENTS Firstly, I would like to express my sincere gratitude to my advisor Dr. Tamer Nadeem for his continues support, guidance, patience, and motivation during my Ph.D study. My sincere thanks also goes to my thesis committee: Prof. Kurt Maly, Dr. Michele Weigle and Dr. Mecit Cetin, for their insightful comments and encourage- ment. Also, I want to show my gratitude to Prof. Hussain Abdulwahab who passed away last December for all his help, care, and guidance during my time at Old Dominion University. Last but not least, I would like to thank my family for supporting me in every way and throughout my Ph.D study and my life in general. vi TABLE OF CONTENTS Page LIST OF TABLES . xi LIST OF FIGURES . xv 1. INTRODUCTION . 1 1.1 INTELLIGENT TRANSPORTATION SYSTEMS . 2 1.2 SMARTPHONES IN ITS . 4 1.3 SENSYS FRAMEWORK . 5 1.4 CONTRIBUTION . 6 1.5 ROADMAP.................................................. 7 Chapter 2. LITERATURE REVIEW . 8 2.1 INTELLIGENT TRANSPORTATION SYSTEMS . 8 2.1.1 INDUCTIVE LOOP DETECTORS . 8 2.1.2 MAGNETOMETER . 8 2.1.3 PIEZOELECTRIC DETECTORS . 9 2.1.4 PNEUMATIC TUBES . 9 2.1.5 VIDEO IMAGE DETECTION SYSTEMS . 10 2.1.6 INFRARED AND LASER SENSORS . 11 2.1.7 RADAR SENSORS . 11 2.1.8 MICROWAVE SENSORS . 11 2.2 SMARTPHONES IN ITS . 11 2.2.1 INERTIAL SENSORS IN ITS . 13 3. SENSYS FRAMEWORK . 18 3.1 OVERVIEW . 18 3.2 DATA COLLECTION AND PREPARATION LAYER . 18 3.2.1 DATA COLLECTION . 18 3.2.2 DATA FILTERING AND PREPARATION MODULES . 25 3.3 VEHICLE DYNAMICS EXTRACTION LAYER . 25 3.3.1 BASIC LEVEL FEATURES . 26 3.3.2 ADVANCED LEVEL FEATURES . 27 3.4 APPLICATION PROGRAMMABLE INTERFACE (API) . 28 3.5 APPLICATIONS . 28 vii 4. DATA PREPARATION AND PRE-PROCESSING. 30 4.1 INTRODUCTION . 30 4.2 LOW PASS FILTER . 30 4.3 COMPLEMENTARY FILTER . 30 4.4 ACCELEROMETER BIAS . 31 4.5 COORDINATE ALIGNMENT (UNICOOR FRAMEWORK). 34 4.5.1 PHONE VERSUS VEHICLE COORDINATES. 36 4.5.2 IMPACT OF COORDINATES . 37 4.5.3 SYSTEM DESIGN . 38 4.5.4 COORDINATES ALIGNMENT. 39 4.5.5 EVALUATION . 44 4.5.6 ACCURACY ENHANCEMENT . 46 4.5.7 CONCLUSION . 50 5. EXTRACTING VEHICLES DYNAMICS . 52 5.1 INTRODUCTION . 52 5.2 BASIC VEHICLE DYNAMICS . 52 5.2.1 FORWARD MOTION . 52 5.2.2 VERTICAL MOTION . 53 5.2.3 LATERAL MOTION . 54 5.2.4 YAW RATE . 54 5.2.5 PITCH RATE . 54 5.2.6 ROLL RATE . 55 5.3 ADVANCE FEATURES EXTRACTION . 55 5.3.1 STOP DETECTION . 55 5.3.2 SPEED ESTIMATION . 57 5.3.3 TURN DETECTION . 57 5.3.4 LANE SWITCH DETECTION . 58 5.3.5 ROAD-BUMP DETECTION . 58 6. SENSYS APPLICATION PROGRAMMABLE INTERFACE (API) . 62 6.1 APPLICATION PROGRAMMING INTERFACE (API) . 62 6.1.1 DATA COLLECTION APIS . 62 6.1.2 VEHICLE DYNAMICS APIS . 66 6.1.3 APPLICATION ADD-ON APIS . 67 7. PARKING SPACE IDENTIFICATION SYSTEM(PARKZOOM) . 68 7.1 INTRODUCTION . 68 7.2 SYSTEM OVERVIEW . 69 7.3 TURN DETECTION . 72 7.4 FINDING THE PARKING SPOT . 73 7.4.1 EXPERIMENT . 74 7.4.2 ERROR CORRECTION . 75 7.4.3 RESULTS . 76 7.5 SYSTEM INTEGRATION AND RESULTS . 77 viii 7.6 RESULTS . 78 7.7 PARKZOOM API . 79 7.8 SUMMARY . 79 8. IN-LANE COMMUNICATION SYSTEM (INLANECOM) . 81 8.1 INTRODUCTION . 81 8.1.1 USE CASES . 82 8.1.2 INLANECOM FRAMEWORK OVERVIEW . 83 8.2 DATA PREPARATION . ..
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