Assessfy Capstone Lab Advanced 6 milestones 100 marks

Development of Low-Cost ADAS Lane-Departure and Collision-Warning Prototype Using Camer...

Branch: Automobile Engineering Type: Industry-applied final-year Major Project Standard: Mumbai University Rev-2019 'C' Scheme (Major Project I + II) Group: up to 4 students Assessment: 6 review-based milestones (100 marks)

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About this project

Development of Low-Cost ADAS Lane-Departure and Collision-Warning Prototype Using Camera and Radar Sensors

Objective: To design and implement a cost-effective prototype for lane-departure and forward collision-warning assistance system using camera and radar integration for Indian road vehicles.

Road accidents and driver inattention are major safety concerns on Indian highways and urban roads, affecting millions annually and leading to significant fatalities and injuries, especially in entry-level and mid-segment vehicles lacking advanced safety features.

This project proposes an industry-relevant engineering solution: a prototype Advanced Driver Assistance System (ADAS) that detects lane-departure and potential frontal collisions using a combined vision (camera) and radar sensor setup, processed via an embedded platform. The approach includes image processing for lane detection and radar-based object tracking, fusing sensor data to generate timely driver alerts.

The deliverables include a hardware prototype integrating a Raspberry Pi 4, automotive-grade camera (e.g., AR0231AT), 24GHz radar module (Infineon or equivalent), and warning interface. The system will be bench-tested and validated on a scaled vehicle platform, with a detailed design report, cost analysis, and live demonstration.

This solution advances affordable vehicle safety for Indian OEMs and aftermarket retrofits, supports road safety initiatives, and is scalable to commercial deployment in mass-market vehicles and public transport fleets.

Milestones

1. Synopsis & Problem Definition (Stage-I Review-1)

8 marks 24d

Formulate the problem statement, identify scope, objectives, and expected industry impact; reviewed via synopsis submission and oral discussion.

2. Literature / Market Survey & Requirement Analysis (Stage-I Review-2)

12 marks 28d

Conduct survey of existing ADAS solutions, market feasibility, and define hardware/software requirements; reviewed through survey report and group presentation.

3. System Design, Methodology & Cost Analysis (Stage-I close)

20 marks 40d

Develop detailed system architecture, select components, design algorithms, and perform cost analysis; reviewed via design document and cost justification.

4. Implementation / Fabrication of Working Model (Stage-II Review-1)

24 marks 40d

Assemble hardware, program embedded system, and integrate camera and radar processing modules; reviewed through demonstration of partial prototype and code walkthrough.

5. Testing, Results & Validation (Stage-II Review-2)

22 marks 36d

Test the prototype on bench/vehicle, collect and analyze data for detection accuracy and response time; reviewed by test report, result analysis, and validation against benchmarks.

6. Report, Paper & Demonstration / Oral Defense (Stage-II final Oral & Practical)

14 marks 32d

Prepare and submit final project report, technical paper, and demonstrate the working model with oral defense before examiner panel.

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Skills you'll learn

CapstoneFinal-year projectMajor projectAutomobile EngineeringEmbedded system integration (cameraradarmicrocontroller/processor)Computer vision and image processing for lane detectionSensor fusion algorithms and real-time data processingAutomotive electronics hardware design and prototypingSystem testing and validation on bench/vehicleCost analysis and requirement specificationTechnical documentation and teamwork/report writing

Tools used

Raspberry Pi 4 or NVIDIA Jetson NanoAutomotive camera module (e.g.ON Semiconductor AR0231AT)24GHz automotive radar sensor (e.g.Infineon Distance2Go or equivalent)OpenCV and Python for image processingCAN bus interface and wiringIS 14272:2011AIS-145 (ADAS standards)MATLAB/Simulink for algorithm prototyping

Prerequisites

Automobile Electronics and Electrical SystemsEmbedded Systems and MicrocontrollersAutomotive MechatronicsSignal Processing and Sensors

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