ABSTRACT
Road speed limit violations have been classified among the major causes of road accidents in developing countries including Kenya. As much as there have been many technological solutions that have been developed to curb vehicle speeding, still cases of road speed limit violations that lead to road accidents continue to rise. However, research has shown that drivers are more responsible on observing road speed limits when they are aware of being monitored. Thus to curb the vehicle speeding problem, a solution for real-time monitoring and identification of driver details could help.
The objective of this project was to design and develop a prototype for an in-vehicle Radio Frequency Identification (RFID) and Global Positioning System (GPS)-based device that can be used for real-time monitoring and identification of drivers violating road speed limits. Thereafter the RFID and GPS functionalities of the prototype were tested and analysed.
Prototyping methodology was used in the system development. The developed prototype comprises of the following critical parts: an embedded system that was deployed in a test vehicle and a web application for remote real-time monitoring and identification of drivers. The development of the solution was done using readily available off-the-shelf electronic components that were integrated by C programming using the Arduino Integrated Development Environment (Arduino IDE). The web application was done using python programming and PostgreSQL database. An experimental approach was used to collect data by fixing the developed prototype in a vehicle and driving it along the identified test locations. The data (GPS coordinates, RFID identities and Vehicle Speed) was sent to a remote server for analysis to ascertain the proposed system’s functionality and reliability.
A total of 60 speed violation tests were done and an impressive 53 speed violation instants were successfully detected and updated on the web application within 3 seconds of violation detection. The instances of failure on speed violation updates were occasioned by poor GSM network connectivity in the areas where failure was detected. This could be rectified by including redundancy connectivity using a satellite module that would provide connectivity in case of poor GSM connectivity. This can also be solved by integrating the embedded solution with an internal storage that will store violation data wherever there’s poor GSM connectivity then transmit the data to the remote server when better GSM connectivity is restored.
Keywords: GPS Module, GSM Module, RFID reader, Electrically Erasable Programmable Read-Only Memory (EEPROM), Embedded Intelligent System (EIS), Radar Technology, LiDAR Technology
TABLE OF CONTENTS
DECLARATION ii
ABSTRACT iii
ACKNOWLEDGEMENT v
ACRONYMS x
CHAPTER 1: INTRODUCTION
1.1. Background of the Study 1
1.2. Problem Statement 2
1.3. General Objective 3
1.4. Specific Objectives 3
1.5. Significance of the Research 3
CHAPTER 2: LITERATURE REVIEW
2.1. Introduction 5
2.2. Vehicle Speeding Problems 5
2.3. Speeding Detection Technologies 6
2.3.1. Radar Technology 6
2.3.2. LIDAR Technology 6
2.3.3. Image processing 6
2.3.4. Global Positioning System (GPS) with Accelerometers 7
2.4. Personal Details Identification Technologies 7
2.4.1. Facial Recognition 7
2.4.2. Fingerprint Recognition 7
2.4.3. Radio Frequency Identification (RFID) 8
2.4.4. Smart Cards 8
2.5. Technological Solutions Used to Curb Vehicle Speeding in Kenya 9
2.5.1. Speed Governors 9
2.5.2. Speed Guns 10
2.6. Related Works on Vehicle Speed Monitoring 10
2.6.1. Pay-As-You-Drive Vehicle Insurance System 10
2.6.2. Traffic Radar Verification System 11
2.6.3. Cruise Control with GPS and Radar System 11
2.6.4. In-vehicle Intelligent Speed Advisory System 12
2.6.5. Embedded System for Automatic Traffic Violation Monitoring and Alerting 13
2.6.6. GPS-Based Solution for Speed Limit Indicator 13
2.7. Research Gap Analysis 14
2.8. Model of the Proposed System 15
CHAPTER 3: METHODOLOGY
3.1. Introduction 17
3.2. System Development Methodology 17
3.3. Requirements Gathering and Analysis 18
3.3.1. System Specification 18
3.4. System Design 19
3.4.1. Hardware Design 20
3.4.2. Embedded System Software Design 21
3.4.3. Web Application Design 21
3.4.4. Embedded Hardware Implementation 27
3.4.5. Embedded Software Implementation 32
3.4.6. Web Application Implementation 32
3.5. System Testing 33
3.5.1. Embedded Device Testing 34
3.5.2. Web Application Testing 36
3.6. Ethical Considerations 37
CHAPTER 4: RESULTS AND DISCUSSION
4.1. Embedded Device Testing Results 38
4.1.1. Testing the RFID Functionality of the Embedded Device 38
4.1.2. Testing the GPS Functionality of the Embedded Device 39
4.2. Web Application Testing Results 40
4.2.1. Ability to Log into the Administration Panel using Authorised Credentials
40
4.2.2. Ability to Log into the Maps monitoring/ Client Interface using Authorised Credentials 41
4.2.3. Ability to add Speed Limits along Different Road Sections 42
4.2.4. Ability of the Web Application to Update Speed Violations Details 43
4.2.5. Evaluation of the ability of the Web Application to Receive and Update Speed Limit Detection Data 43
4.3. Explanation of Results on Table 4.3 44
CHAPTER 5: CONCLUSION AND FURTHER WORK
5.1. Achievement of Research Objectives 45
5.1.1. Gathering System Requirements 45
5.1.2. Designing and Developing an RFID and GPS-based Embedded Device for Speed Violation Detection 45
5.1.3. Designing and Developing a Web Application for Speed Violation Updates.
45
5.1.4. Testing the functionalities of the RFID and GPS-based Speed Violation Detection System 46
5.2. Research Contribution 46
5.3. Conclusion 46
5.4. Recommendations for Further Work 46
REFERENCES 48
APPENDIX I: PROJECT SCHEDULE 52
APPENDIX II: PROJECT COST ESTIMATES 52
APPENDIX III: CODE SNIPPETS 53
LIST OF FIGURES
FIGURE 2.5: SPEED GOVERNOR. AFRIKA (2018) 9
FIGURE 2.6: A TRAFFIC OFFICER USING A SPEED GUN. MWANGI (2018) 10
FIGURE 2.7: INTELLIGENT SPEED CONTROL SYSTEM. BOUKHARI (2018) 12
FIGURE 2.8: IN-VEHICLE INTELLIGENT SPEED ADVISORY SYSTEM. BATEN ET AL (2009) 12
FIGURE 2.9: AUTOMATIC TRAFFIC VIOLATION MONITORING AND ALERTING EMBEDDED SYSTEM. RAMYA ET AL. (2012) 13
FIGURE 3: GPS BASED SPEED LIMITER. KHAN ET AL. (2009) 14
FIGURE 3.1: MODEL OF PROPOSED SYSTEM 15
FIGURE 3.2: SYSTEM DEVELOPMENT METHODOLOGY. AMAN ET AL. (2018) 17
FIGURE 3.3: SYSTEM ARCHITECTURE 19
FIGURE 3.4: HARDWARE DESIGN 20
FIGURE 3.5 EMBEDDED SYSTEM SOFTWARE DESIGN 21
FIGURE 3.6: CONTEXT DIAGRAM 23
FIGURE 3.7: DATA FLOW DIAGRAM 24
FIGURE 3.8: ENTITY RELATIONSHIP 25
FIGURE 3.9: ADD SPEED LIMIT 26
FIGURE 4.0: ADD DRIVER DETAILS 27
FIGURE 4.1: ATMEGA 328P. OEMSECRETS (2021) 28
FIGURE 4.2: BEITIAN BN-180 GPS MODULE. AMAZON (2021) 28
FIGURE 4.3: SIM800L GSM MODULE. MAKEPRO (2021) 29
FIGURE 4.4: LM2596S DC TO DC VOLTAGE STEP DOWN MODULE. XCLUMA (2021) 29
FIGURE 4.5: SWITCHING RELAY. EBAY (2021) 30
FIGURE 4.6: HARDWARE DESIGN AND SIMULATION ON PROTEUS SOFTWARE 31
FIGURE 4.7: FINE-TUNED CIRCUIT DESIGN USING PROTEUS SOFTWARE 32
FIGURE 4.8: EMBEDDED DEVICE TESTING 34
FIGURE 4.9: LOCATION 1 OF THE SYSTEM TESTING 35
FIGURE 5.0: LOCATION 2 OF THE SYSTEM TESTING 36
FIGURE 5.1: LOGIN INTO THE ADMINISTRATION PANEL 40
FIGURE 5.2: ADMINISTRATION LANDING PAGE 41
FIGURE 5.4: ADDING SPEED LIMITS ALONG ROAD SECTIONS 43
FIGURE 5.6: MAPS MODULE AND ALERTS NOTIFICATION TESTING 43
LIST OF ACRONYMS
EEPROM Electrically Erasable Programmable Read-Only Memory
EIS Embedded Intelligent System
GPRS General Packet Radio Service
GPS Global Positioning System
GSM Global Systems for Mobile Communication
IDE Integrated Development Environment
LiDAR Light Detection and Ranging
NTSA National Transport and Safety Authority
PCB Printed Circuit Board
PSV Public Service Vehicle
Radar Radio Detection and Ranging
RFID Radio Frequency Identification
WHO World Health Organisation
CHAPTER 1
INTRODUCTION
1.1. Background of the Study
Vehicle speeding has been classified as a major cause of road accidents, injuries and loss of lives. According to the World Health Organization (2021), 40% to 50% of drivers in the whole world drive above the speed limit, and research has shown that the higher the speed of a vehicle, the higher the risk of injury and death. Approximately 1.35million people globally lose their lives annually through road accidents. 93% of the live losses through road accidents happen in low and middle in-come countries and more than half of these deaths and injuries are among the most vulnerable road users; pedestrians, cyclists and motorcyclists (WHO, 2020). In Kenya, monthly deaths caused by road accidents increased by 26% from January 2015 to January 2020 while injuries increased by 46.5% over the same period. The trend is projected to continue unless action is taken to curb speeding on the Kenyan roads (Muguro et al., 2020).
The National Transport and Safety Authority (NTSA) has over the years tried to enforce the road speed limits by traffic officers physically being on the Kenyan roads but still cases of road accidents continue to rise each year (Kajilwa, 2016). This continuous increase of road accidents has been attributed to irresponsibility by the drivers who as much as they are aware of road speed limits and the presence of law enforcers’ on the roads, they only observe the speed limits in locations where they know traffic officers are present but knowingly break the speed limits in areas where they know no one is monitoring them (Yannis et al., 2013). In other cases of being caught speeding by traffic officers, the drivers always bribe their way out of the hands of the traffic officers (Transparency International, 2018). Some drivers on being stopped by traffic officers, they either speed away with the vehicle or run away on foot leaving behind their vehicle. This is attributed to the fact that there will be no evidence available to link the driver to the speed violations. Also, traffic officers are sometimes scared of impounding speeding vehicles because they belong to high ranking people in society (The Standard Media, 2017).
Over the years, several embedded intelligent systems (EIS) have been developed to curb vehicle speeding in several countries. These EIS solutions are using different technologies to curb speeding. Radar technology, Global Positioning System (GPS), Global Systems for Mobile Communication (GSM) and General Packet Radio Service (GPRS) technologies. These technologies are able to identify a speeding vehicle but they still have fallen short of identifying in real-time the details of drivers violating road speed limits (Jeddi et al., 2013).
1.2. Problem Statement
There lacks in Kenya an effective road speed limit monitoring system that can be used to enhance road safety by monitoring and identifying drivers violating speed limits in real-time. The National Transport and Safety Authority (NTSA) has put in place measures like speed governors with 80km/h speed limits but they have not been effective in real time identification and keeping records of the drivers violating speed limits. The speed governors have also not been effective in ensuring drivers observe speed limits in places with speed limits of below 80km/h. NTSA has also used Light Detection and Ranging (LIDAR) speed guns to monitor and identify speeding vehicles but these speed guns are only limited to identifying one vehicle at a time and are only effective to certain areas of the roads where traffic officers are physically present on the road. These two solutions, speed governor and speed gun, are also not able to identify the details of the specific driver driving a vehicle at a particular time with real-time remote monitoring. The systems also put much focus on identifying the vehicle rather than the driver who is solely responsible for speeding.
Sometimes drivers run away and leave vehicles behind when stopped by traffic officers for speeding. Vehicles like Public Service Vehicles (PSVs) are driven by many drivers in a particular day and thus it becomes difficult for traffic officers to identify which driver was driving the PSV at a certain time when it was stopped for speeding.
Thus, to ensure responsibility among drivers in observing road speed limits and curb road accidents, there’s need to implement a system that is able to identify in real-time the details of drivers violating road speed limits.
1.3. General Objective
To design and develop an in-vehicle RFID and GPS Based system that can be used to monitor and identify drivers violating road speed limits.
1.4. Specific Objectives
a) To gather and analyse system requirements.
b) To design and develop a GPS and RFID based embedded device for speed violation detection.
c) To design and develop a web application for monitoring and recording speed violations
d) To test the functionalities of the GPS and RFID based speed detection system.
1.5. Significance of the Research
The study aimed at providing a better understanding about various embedded solutions used in monitoring and identifying road speed limit violators. The findings of this research would help the National Transport and Safety Authority (NTSA) and other stakeholders in the transport sector to put in place an effective road safety enforcement system that will help to identify drivers breaking road speed limits in real time and thus reduce road accidents caused by speeding.
This project would also help to bridge the technology gap in existing road safety enhancement solutions and architectures. It hopefully could also add new information to existing research on enhancing road safety through technology.
Implementation of an effective road safety solution could be a boost to Kenya’s Gross Domestic Product (GDP) which has often been affected by the government spending millions of Kenya Shillings in treating victims of road accidents and losing productive human resource to injuries and deaths caused by road accidents.
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