Traffic Accident Prediction Model using Deep Learning

[alo7lika]

Pull Request for Traffic Accident Prediction Model 🛣️

Requesting to submit a pull request to the Traffic Accident Prediction Model repository.

---

Issue Title

Please enter the title of the issue related to your pull request.
Traffic Accident Prediction Model using Deep Learning

• I have provided the issue title.

---

Info about the Related Issue

What's the goal of the project?
The aim of the project is to predict the likelihood of traffic accidents using historical data such as accident records, weather conditions, traffic volume, and road characteristics, helping local authorities implement targeted safety measures and improve traffic management strategies.

• I have described the aim of the project.

---

Name

Please mention your name.
Alolika Bhowmik

• I have provided my name.

---

GitHub ID

Please mention your GitHub ID.
alo7lika

• I have provided my GitHub ID.

---

Email ID

Please mention your email ID for further communication.
[email protected]

• I have provided my email ID.

---

Identify Yourself

Mention in which program you are contributing (e.g., WoB, GSSOC, SSOC, SWOC).
*Enter your participant role here.*GSSOC ext 24

• I have mentioned my participant role.

---

Closes

Enter the issue number that will be closed through this PR.
*Closes: #568 *

• I have provided the issue number.

---

Describe the Add-ons or Changes You've Made

Give a clear description of what you have added or modified.
I have added an improved evaluation method for the model by implementing new accuracy metrics and visualizations. The changes include updating the model's evaluation function, adding precision-recall curves, and modifying the code to output these visualizations during testing.

• I have described my changes.

---

Type of Change

Select the type of change:

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Code style update (formatting, local variables)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

---

How Has This Been Tested?

Describe how your changes have been tested.
The changes have been tested by running the model with the updated evaluation method on the validation dataset. Unit tests were created to check for precision, recall, and F1-score calculations. Additionally, visualizations were generated to verify that the output matches expected behavior.

• I have described my testing process.

---

Checklist

Please confirm the following:

• My code follows the guidelines of this project.
• I have performed a self-review of my own code.
• I have commented my code, particularly wherever it was hard to understand.
• I have made corresponding changes to the documentation.
• My changes generate no new warnings.
• I have added tests that prove my fix is effective or that my feature works.
• Any dependent changes have been merged and published in downstream modules.

[github-actions]

👋 Thank you for opening this pull request! We're excited to review your contribution. Please give us a moment, and we'll get back to you shortly!

Feel free to join our community on Discord to discuss more!

[alo7lika]

@UTSAVS26 task has been completed.
Please review it.
Thank you!

[alo7lika]

@shaansuraj @TheChaoticor kindly review it.