Skip to content

DriveScore TripBook: Enhancing Your Driving Experience through Data-Driven Insights

License

Notifications You must be signed in to change notification settings

SEA-ME/ME_Digital-Trip-Book

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

6 Commits
 
 
 
 

Repository files navigation

ME Project - Digital Trip Book


Introduction

V2X Data Capture and Replay for Comprehensive Vehicle Trip Analysis. This project is a research project based on V2X (Vehicle-to-Everything) technology where you want to record digital signals within a vehicle during a fixed trip. It is a fascinating and ambitious project that involves aspects of data acquisition, signal processing, communication protocols, and possibly machine learning for replay.


Project Goals & Objectives

Here's a structured approach to guide you through the process:

  1. Real-time Data Capture:

    • Develop a system to capture digital signals produced/transmitted across the V2X network within a vehicle.
    • Is logging a good idea? Explore the correct methodology.
    • What data should be considered for recording? sensor readings, communication messages, control signals ?
    • How should these data be recorded? Recording every single bit is going to cost you a universe, may be Claude Shannon can help you?
    • Define the parameters of a fixed trip, including route, duration, and specific scenarios (e.g., intersections, highway driving). Implement a mechanism to record data only during the fixed trip to avoid unnecessary data storage.
    • Design a structured database or file format to store the captured data efficiently. Consider compression techniques to minimize storage requirements.
    • And security? Implement encryption and authentication protocols to protect sensitive information.
  2. Replay System:

    • Develop a replay system capable of reconstructing the vehicle's behavior based on the recorded data. Ensure synchronization of various signals for an accurate and realistic playback.
    • Create a user interface for visualizing the recorded data, allowing users to analyze the vehicle's behavior during the trip.
    • Implement tools for extracting insights, identifying patterns, and troubleshooting issues.

Project Timeline

A tentative project timeline for the Digital Trip Book project would include the following phases:

  1. Planning and Preparation (2-3 weeks)
  2. System Architecture and Design (2-3 weeks)
  3. Development and Integration (4-6 weeks)
  4. Testing and Debugging (2-3 weeks)
  5. Pilot / Proof of Concept Deployment (2-3 weeks)

Note that the timeline may vary depending on the complexity of the project, the availability of resources, and the expertise of the development team. However, the timeline provides a general idea of the phases and timeline involved in implementing a Digital Trip Book project.

Submission

Submit the following artifacts to GitHub:

  1. Documentations:
    • A nice proposal of V2X communication standards. Would be in the form of thesis / research paper.
    • Entire system architecture, data structures, and algorithms used.
    • A comprehensive report detailing the methodology, challenges faced, and solutions implemented.
  2. Proof of Concept:
    • The source code.
    • Test Cases demonstrating the reliability and accuracy of the system.
  3. Presentation:
    • A presentation summarizing the project, including an overview of the system architecture, technical specifications, user interface, and test results.

References

Here are some open source references that could be useful in developing a DriveScore TripBook project:

  1. CAN Bus: The CAN Bus is a common automotive communication protocol used to exchange data between control units within a vehicle. A popular open source implementation of the CAN Bus is the SocketCAN project, which provides a set of Linux kernel drivers and user-space libraries for accessing CAN devices. (https://github.com/linux-can/can-utils)
  2. Machine Learning Algorithms: Machine learning algorithms can be used to analyze and interpret driver behavior data, in order to calculate a driving score. The scikit-learn library is a widely used open source machine learning library in Python, providing a number of algorithms and tools for data analysis and modeling. (https://github.com/scikit-learn/scikit-learn)
  3. User Interface Design: A user-friendly and visually appealing user interface is critical for the success of the DriveScore TripBook project. Bootstrap is a popular open source front-end framework for building responsive and mobile-first websites and applications. (https://github.com/twbs/bootstrap)
  4. Digital Trip Book: The digital trip book system can be developed using a variety of open source technologies, including web frameworks like Ruby on Rails or Django, and database systems like MySQL or PostgreSQL. A popular open source digital trip book implementation is the OpenTripPlanner project, which provides a comprehensive platform for trip planning and itinerary management. (https://github.com/opentripplanner/OpenTripPlanner)

These open source references can serve as starting points for developing a DriveScore TripBook project, and can be combined and customized as needed to meet the specific requirements of the project.

About

DriveScore TripBook: Enhancing Your Driving Experience through Data-Driven Insights

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published