Detection of Lane and Speed Breaker.pptx

1. Detection of Lane and Speed Breaker Warning System for
Autonomous Vehicles using Machine Learning Algorithm
Group No :
Student name : exam number :
Student name : exam number :
Student name : exam number :
Student name : exam number :
2023-2024
Under Guidance of
Prof.

2. CONTENTS
1. Introduction
2. Motivation
3. Problem Definition
4. Literature Survey
5. Software Requirements Specification
6. Hardware Requirements Specification
7. Scope
8. Architecture
9. Conclusion
10. References
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Detection of Lane and Speed Breaker Warning System for Autonomous Vehicles using Machine Learning Algorithm

3. Detection of Lane and Speed Breaker Warning System for Autonomous Vehicles using Machine Learning Algorithm
3
INTRODUCTION
• The "Detection of Lane and Speed Breaker Warning System for Autonomous Vehicles
using Machine Learning Algorithm" is a critical component of autonomous driving
systems.
• This system is designed to enhance the safety and efficiency of autonomous vehicles
by detecting and responding to lane markings and speed breakers on the road.
• In this introduction, we will provide an overview of the key components, goals, and
benefits of such a system.
• By leveraging advanced machine learning techniques and sensor data, it enhances the
vehicle's ability to navigate complex road conditions while prioritizing safety and
passenger comfort.

4. Detection of Lane and Speed Breaker Warning System for Autonomous Vehicles using Machine Learning Algorithm 4
MOTIVATION
The development of a lane and speed breaker warning system using machine learning
algorithms is motivated by the need to enhance the safety, adaptability, and comfort of
autonomous vehicles. It addresses critical challenges faced by self-driving cars in
navigating diverse road conditions and contributes to the overall acceptance and success
of autonomous driving technology.

5. .roject Title Goes here 5
PROBLEM DEFINITION
To identify the presence and location of speed breakers or road humps on the road. Speed
breakers are elevated road segments designed to slow down vehicle speed. The system
should be capable of distinguishing speed breakers from other road objects and provide
accurate information about their position and size. This information can be used to adjust
the vehicle's speed or trigger appropriate suspension control to ensure a smooth and safe
ride.

6. LITERATURE SURVEY
Project Title Goes here 6
SR.NO. Topic Name Author Description
1. Speed Breaker Detection
and Mapping using IoT
Rahul
Ramakrishnan,
Chetna Sharma
•With increasing road accidents due to improper and
non-standard speed breakers.
•It is the need of the hour to address this issue
appropriately and they are posing to be more of a
danger.
2. Real Time Detection of
Roadside Speed Breakers
and Obstacles upto Knee-
level
Prottoy Saha,
Muhammad Sheikh
Sadi
•Navigation Guide refers to frameworks that helps
people with vision misfortune to navigate safely.
•The proposed device detects speed breakers on the
street and knee level around individuals
3. Pothole and Speed Breaker
Detection Using
Smartphone Cameras and
Convolutional Neural
Networks
Zahid Hasan,
Samsoon Nahar
Shampa
•Poor road conditions are one of the major causes for
road accidents.
•In this paper we propose a method where we use the
Tensor flow pre-trained model to detect the potholes,
deep ridges and speed breakers

7. SOFTWARE & HARDWARE REQUIREMENTS
Project Title Goes here 7
Software Requirements Specification
Coding Language : Python
Operating System : Windows 10
Hardware Requirements Specification
Processor : Pentium-IV
RAM : 512 MB(min)
Hard Disk : 40 GB
Key Board : Standard Windows Keyboard
Mouse : Two or Three Button Mouse
Monitor : LCD/LED

8. SCOPE
Project Title Goes here 8
• Clearly define the objectives and requirements of the lane and speed breaker detection system.
• Collect a diverse dataset of road scenarios, including various lane types and speed breaker designs.
• Develop machine learning algorithms and models.
• Implement real-time data processing to continuously analyze sensor data and detect lanes and speed
breakers.
• Develop a warning system that communicates with the autonomous vehicle's control system.
• Conduct extensive testing in controlled environments and on actual roads to validate the system's
accuracy and reliability.
• Implement safety measures and redundancy mechanisms to handle system failures or false
positives/negatives.

9. Project Title Goes here 9

10. 10
Conclusion
In conclusion, the development of a lane and speed breaker warning system for
autonomous vehicles using machine learning algorithms is a critical step toward
enhancing their safety and reliability. These systems can help vehicles navigate roads
more effectively and reduce the risk of accidents.

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References
• L. Zhang, F. Jiang, B. Kong, J. Yang, and C. Wang, ‘‘Real-time lane detection by using biologically
inspired attention mechanism to learn contextual information,’’ Cogn. Comput., vol. 13, pp. 1333–
1344, Sep. 2021, doi: 10.1007/s12559-021-09935-5.
• R. Zhang, Y. Wu, W. Gou, and J. Chen, ‘‘RS-lane: A robust lane detection method based on ResNeSt
and self-attention distillation for challenging traffic situations,’’ J. Adv. Transp., vol. 2021, pp. 1–12,
Aug. 2021.
• J. Li, F. Jiang, J. Yang, B. Kong, M. Gogate, K. Dashtipour, and A. Hussain, ‘‘Lane-DeepLab: Lane
semantic segmentation in automatic driving scenarios for high-definition maps,’’ Neurocomputing,
vol. 465, pp. 15–25, Nov. 2021, doi: 10.1016/j.neucom.2021.08.105.
• D. Kavitha and S. Ravikumar, ‘‘Designing an IoT based autonomous vehicle meant for detecting
speed bumps and lanes on roads,’’ J. Ambient Intell. Hum. Comput., vol. 12, no. 7, pp. 7417–7426,
Jul. 2021, doi: 10.1007/s12652-020-02419-8.

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