Drivora: Distributed Universal Advanced Driver Assistance System
Team
- E/21/050, Bandara H.B.C.T., e21050@eng.pdn.ac.lk
- E/21/052, Bandara H.M.P.D., e21052@eng.pdn.ac.lk
- E/21/077, Darshana K.M.S., e21077@eng.pdn.ac.lk
- E/21/269, Nirmal A.P.S., e21269@eng.pdn.ac.lk
Table of Contents
- Introduction
- Solution Architecture
- Hardware & Software Designs
- Testing
- Detailed budget
- Conclusion
- Links
Introduction
Drivora is a Distributed Retrofit Safety System designed to modernize legacy vehicles that lack contemporary safety technology. It serves as a four-unit hardware suite communicating over a robust CAN-Bus backbone to create a “Safety Shield” around the vehicle. By combining radar-based distance sensing, inertial motion tracking, and computer vision, it provides real-time audio-visual alerts to help prevent collisions and rollovers. This system specifically targets owners of older passenger vehicles and commercial vehicle operators who face massive blind spots and stability risks.
Solution Architecture
The system utilizes a decentralized architecture with four discrete units linked via a vehicle-wide communication backbone.
- Unit A (Front Radar Array): Positioned at the front bumper to monitor forward collision risks and relative velocity.
- Unit B (Rear Safety Hub): Centrally located within the chassis with three distributed probes at the bumper corners and center for blind-spot monitoring and reverse safety.
- Unit C (COG & Dynamics Unit): Mounted at the vehicle’s geometric center to track orientation, lateral G-forces, and vibration signatures.
- Unit D (Windshield Hub): Attached to the upper windshield to handle AI-vision processing and manage the user interface via a smartphone.
Hardware and Software Designs
Drivora integrates high-performance microcontrollers and specialized sensors to deliver its safety features.
Hardware Architecture
- Central Processor: An ESP32-S3 with 8MB PSRAM for high-speed image processing and smartphone data streaming.
- Distributed Controllers: ESP32-C3 SuperMini modules acting as localized controllers for edge units.
- Sensing Suite: Dual 24GHz CDM324 Doppler radars for front detection and waterproof JSN-SR04T ultrasonic sensors for rear/side coverage.
- Stability Tracking: A high-precision BNO055 9-axis IMU with internal fusion for real-time Center of Gravity (COG) and tilt monitoring.
Software Features
- Collision Detection: Algorithms calculate Time-to-Collision (TTC) using Doppler shift data from the front radar array.
- Lane Departure Warning: A computer vision pipeline identifying road markings to detect unintentional drifting.
- Stability Scoring: Processing tilt and G-force data to identify rollover risks in high-profile vehicles.
- Maintenance Diagnostics: Frequency analysis of chassis oscillations to identify worn-out shock absorbers.
Testing
Comprehensive testing ensures the system’s reliability in a high-vibration automotive environment.
- Sensor Validation: Evaluating the detection range and accuracy of both the Doppler radar and ultrasonic arrays at various vehicle speeds.
- Vision Accuracy: Testing the ESP32-S3’s ability to identify lane markings under diverse lighting conditions through the windshield.
- Network Integrity: Verifying that the CAN-Bus backbone maintains data synchronization between the four units without latency issues.
- HMI Performance: Testing the reliability of the Bluetooth connection and the real-time responsiveness of the smartphone-based dashboard.
Detailed budget
| Item | Quantity | Unit Cost (LKR) | Total (LKR) |
|---|---|---|---|
| ESP32-S3 (Main Hub) | 1 | 2,100 | 2,100 |
| ESP32-C3 SuperMini | 3 | 800 | 2,400 |
| CDM324 Radar | 2 | 1,500 | 3,000 |
| JSN-SR04T Waterproof Ultrasonic | 3 | 1,266 | 3,800 |
| BNO055 (IMU) | 1 | 2,500 | 2,500 |
| OV2640 Camera | 1 | 1,200 | 1,200 |
| CAN Transceivers (SN65HVD230) | 4 | 500 | 2,000 |
| XL4015 5A Buck Converter | 1 | 540 | 540 |
| Cigarette Plug Adapter | 1 | 170 | 170 |
| Misc (Enclosures / Wires / Switches) | - | - | 7,000 |
| Total | 24,710 (Approx.) |
Conclusion
Drivora provides a comprehensive and affordable safety modernization path for legacy and commercial vehicles. By leveraging a distributed multi-unit architecture and low-cost edge computing, the system achieves complex features like Forward Collision Warning and Stability Monitoring. Future work will focus on refining the experimental Overtake Warning System and enhancing the cloud-based telematics platform for long-term vehicle health tracking.