Acoustic detection of rear approaching vehicles for cyclists

 

Table Of Contents


Chapter ONE

INTRODUCTION

  • 1.1Introduction
  • 1.2Background of Study
  • 1.3Problem Statement
  • 1.4Objective of Study
  • 1.5Limitation of Study
  • 1.6Scope of Study
  • 1.7Significance of Study
  • 1.8Structure of the Research
  • 1.9Definition of Terms

Chapter TWO

LITERATURE REVIEW

  • 2.1Overview of Acoustic Detection
  • 2.2History of Acoustic Detection Technologies
  • 2.3Acoustic Signals and their Properties
  • 2.4Applications of Acoustic Detection in Road Safety
  • 2.5Challenges in Acoustic Detection for Cyclists
  • 2.6Innovations in Acoustic Detection Systems
  • 2.7Comparative Analysis of Acoustic and Visual Detection
  • 2.8Acoustic Detection Devices in the Market
  • 2.9Impact of Acoustic Detection on Cyclist Safety
  • 2.10Future Trends in Acoustic Detection Technology

Chapter THREE

RESEARCH METHODOLOGY

  • 3.1Research Methodology Overview
  • 3.2Research Design and Approach
  • 3.3Sampling Methods and Participant Selection
  • 3.4Data Collection Techniques
  • 3.5Data Analysis and Interpretation
  • 3.6Ethical Considerations in Research
  • 3.7Validity and Reliability of Research Findings
  • 3.8Tools and Software Used for Analysis

Chapter FOUR

DATA PRESENTATION AND ANALYSIS

  • 4.1Overview of Research Findings
  • 4.2Analysis of Acoustic Signals for Vehicle Detection
  • 4.3Impact of Background Noise on Detection Accuracy
  • 4.4Comparison of Different Acoustic Detection Models
  • 4.5Evaluation of Acoustic Detection Performance Metrics
  • 4.6Discussion on Real-world Implementation Challenges
  • 4.7Recommendations for Improving Acoustic Detection Systems
  • 4.8Future Research Directions

Chapter FIVE

SUMMARY, CONCLUSION AND RECOMMENDATIONS

  • 5.1Conclusion and Summary of Findings
  • 5.2Recap of Research Objectives and Contributions
  • 5.3Implications of Research for Cyclist Safety
  • 5.4Practical Applications of Acoustic Detection Technology
  • 5.5Reflection on Research Process and Limitations
  • 5.6Recommendations for Future Studies
  • 5.7Closing Remarks and Final Thoughts

Project Abstract

<p> </p><p>The project aims to detect rear approaching vehicles for cyclist with a low power consumption. Study focuses on acoustic features of the sound of rear approaching vehicles and examines the useful indicators to detect the vehicles.</p><p>The project includes more then one correlation and reveals their success rates for as many as samples possible. The project is given as a proposal for increasing the safety of cyclists riding on the country roads.</p><p>It can be sometimes hazardous for bike riders to ride either on the same road with the cars or on the suburban road.Thus, an alerting system which will be mounted on the bicycle is required.</p><p>The aim of the project is to find most suitable sensor which can generate the alert early enough that cyclist can take an action before the vehicle reaches up.Since the sensor will be used for bicycles, power consumption and the size of the sensor should be rather small.</p><p>Audio detection was chosen from among all the possible detection types.In order to distinguish the sound from an approaching vehicle among all environmental noises,many samples were collected and analyzed.Classifying and comparing the sounds; the most interesting features of the vehicle approaches were found out as; frequency shifts and amplitude increment in power spectrum, regularity/irregularity changes within the sound, mass point shifts and loudness level increment.</p><p>Four different methods were used regarding correlations.Samples were filtered to obtain better results.Considering all the cases, there is a threshold was set for all methods in order not to confuse them with environmental noises or risk less cases.Specifying a threshold value has also its disadvantages,because making alert generation more reliable is inversely proportional with success ratio.The most of the methods given in this report have the approximate success ratio of 70% for each method is quite sufficient, considering those methods can be fused together to have more accurate sensor.</p><p>My work is a proof that many different types of sound correlations can be used to determine if there is a vehicle approaching or not.Methods that pointed out in this report can be used to build up a fine alerting system to increases the awareness of cyclists.</p> <br><p></p>

Project Overview

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