Masterarbeit, 2019
91 Seiten, Note: 3
1. CHAPTER I INTRODUCTION AND DISSERTATION BACKGROUND
1.1 Introduction
1.2 Background of the Study
1.3 Statement of the Problem
1.4 Aim of the research
1.5 Objectives of the Research
1.6 Research Questions
1.7 Scope of the Research
1.8 Significance of the Research
1.9 Overview of thesis
1.10 Summary
2. CHAPTER II LITERATURE REVIEW
2.1 Introduction
2.2 STMS Overview
2.3 Smart Traffic Application using various technologies
2.3.1 Using GPS
2.3.2 Using Image Processing
2.3.3 Using Power Line Communication (PLC)
2.3.4 Using Sensors and embedded system
2.3.5 Using Cloud Computing
2.4 Benefits of IoT Based Smart Traffic Management System
2.4.1 STMS Opportunities
2.5 Summary
3. CHAPTER III RESEARCH METHODOLOGY
3.1 Research Methodology
3.1.1 Research Strategy
3.2 Sampling methods And Sample Design
3.3 Data Collection Methods
3.4 Data Capturing and Data Editing
3.5 Design of the questionnaire question
3.6 Data Collection Limitations
3.7 Data Collection Assumptions
3.8 Research Timeframe
3.9 Ethics and Confidentiality
3.10 Summary
4. CHAPTER IV DATA ANALYSIS
4.1 Introduction
4.2 Respondent’s Background
4.3 Data analysis on the basis of vehicle owners:
4.3.1 Frequency analysis of gender:
4.3.2 Frequency analysis of age:
4.3.3 Frequency analysis of mode of transportation:
4.3.4 Frequency distribution of perception on existing traffic system:
4.3.5 Frequency distribution of satisfaction with current TMS:
4.3.6 Questions related to Scope of STMS:
4.3.7 Questions related to possible benefits of STMS:
4.3.8 Question related to Technical challenges of STMS:
4.4 Data Analysis on the basis of respondent category: Traffic Policemen
4.4.1 Frequency analysis of gender:
4.4.2 Frequency analysis of age:
4.4.3 Frequency distribution of Post
4.4.4 Frequency distribution of Experience
4.4.5 Questions related to the Scope of STMS adoption:
4.4.6 Questions related to the possible benefits of STMS adoption:
4.4.7 Questions related to the technical challenges of STMS adoption:
4.5 Summary
5. CHAPTER V CONCLUSION AND RECOMMENDATIONS
5.1 Findings
5.1.1 On the basis of data collection from vehicle owners:
5.1.2 On the basis of data collection from traffic policemen:
5.2 Discussion
5.2.1 Scope of STMS adoption
5.2.2 Possible benefits of STMS implementation
5.2.3 Technical challenges of STMS adoption
5.3 Conclusion
5.4 Recommendations
5.5 Future Work
The primary objective of this research is to evaluate the feasibility and future scope of adopting a Smart Traffic Management System (STMS) in Kathmandu, Nepal, by identifying existing technical challenges through quantitative analysis based on surveys of vehicle owners and traffic personnel.
1.2 Background of the Study
Intelligent traffic system comprises of various system including the system for communicating, controlling, analyzing and managing the traffic. The intelligent traffic system is used with the objective to gain traffic performance advantages. The traffic congestion is the major issue in the recent days and the most of the cities are facing problem because of traffic congestion. (Gautam Hoshing, 2017)
Intelligent traffic management system is necessary for the smart cities in the recent context. The intelligent traffic management system helps in controlling flow of the traffic and also helps in reducing the traffic congestion. Comparing the traditional traffic lights and the smart traffic lights, the smart traffic lights activate the lights whenever it is required according to what is happening in the roads. Few of the cities that have already adopted the intelligent traffic management system are Singapore and India. Furthermore, the use of the smart traffic management system helps in reducing the irritation of drivers and reducing the road rash cases. (Sabhijiit Singh Sandhu, 2015)
The application of the Smart traffic management system is collecting the data related to the traffic in the actual time to monitor the system for resolving the traffic related issues. The STMS helps in deducting the time that is spent while pausing in the traffic congestion and also minimize the fuel and budget. (Dr. Meenakshi Sundaram, 2017)
With the current scenario of people going through traffic congestion every single day leading to the waste of time and fuel, there should be a proper system that can help in minimizing the traffic problems and also reducing the traffic congestion. Hence, the implementation of smart traffic management system can help resolve the traffic problems. (Antonio J. Fernández-Ares, 2016)
CHAPTER I INTRODUCTION AND DISSERTATION BACKGROUND: Outlines the research context, problem statement regarding traffic congestion in Kathmandu, and research objectives.
CHAPTER II LITERATURE REVIEW: Analyzes existing research papers and studies regarding STMS, comparing various technologies and approaches used in traffic management.
CHAPTER III RESEARCH METHODOLOGY: Details the quantitative research approach, survey design, and data collection methods involving vehicle owners and traffic policemen.
CHAPTER IV DATA ANALYSIS: Presents the findings from the surveys, including demographic data and respondent perspectives on STMS benefits and challenges, analyzed via SPSS.
CHAPTER V CONCLUSION AND RECOMMENDATIONS: Synthesizes research findings and provides recommendations for integrating STMS in Kathmandu as part of smart city initiatives.
Smart Traffic Management System, STMS, Traffic congestion, Kathmandu, Nepal, Intelligent Transport System, IoT, Traffic safety, Data analysis, Quantitative research, Traffic police, Vehicle owners, Road infrastructure, Smart cities, Road accidents
The research focuses on exploring the future scope and technical challenges of adopting a Smart Traffic Management System (STMS) specifically within the urban context of Kathmandu, Nepal.
The central themes include the limitations of the existing manual traffic system, the potential benefits of digital STMS, and specific challenges like internet availability, budget, and government policy.
The goal is to determine the viability of STMS implementation by analyzing data collected from the city's key stakeholders: vehicle drivers and traffic police officers.
A quantitative methodology was used, utilizing web-based and manual surveys (questionnaires) to gather data from 315 vehicle owners and 53 traffic policemen.
It covers a detailed literature review of various traffic management technologies (GPS, sensors, AI), followed by a comprehensive data analysis section based on the conducted surveys.
Key terms include Smart Traffic Management System, Traffic congestion, Kathmandu, IoT, and Intelligent Transport System.
Police believe it is vital for identifying vehicle owners, accessing accurate records, reducing fraud, and streamlining the ticketing process, which is currently hindered by manual systems.
The study highlights that internet connectivity is a critical technical challenge, as the proposed STMS requires stable, consistent, and city-wide internet infrastructure to function correctly.
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