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This document outlines the user stories, priorities, and acceptance criteria for the Real-time Autonomous Safety Detector, covering pothole and speed bump detection under various conditions.
| ID | Title | User Story (IEEE Format) | Priority | Acceptance Criteria |
|---|---|---|---|---|
| P1 | Pothole Detection – Morning | As a driver commuting in the morning, I want the system to detect potholes ahead so that I can reduce speed smoothly. | High | • System detects potholes in clear conditions • Driver is alerted early enough to reduce speed safely • False positives are minimized • Pothole is logged with GPS, time, and severity for reporting |
| P2 | Pothole Detection – Night | As a driver traveling at night, I want the system to detect potholes in low visibility so that I can avoid sudden swerves. | High | • System functions reliably under low-light conditions • LiDAR + camera fusion enables accurate detection • Driver receives a timely alert • Pothole is logged with GPS, time, and severity |
| P3 | Pothole Detection – Extreme Weather conditions | As a driver in heavy rain, I want potholes detected despite water or dust so that I can prevent accidents. | Medium | • Detection accuracy remains acceptable in rain/dust • Alerts are delivered to the driver in real time • Pothole is logged with GPS, time, and severity |
| S1 | Speed Bump Detection – Morning | As a driver commuting in the morning, I want the system to detect speed bumps so that I can slow down safely. | High | • System detects speed bumps under normal visibility • Driver is prompted to reduce speed before crossing • Alerts are consistent and reliable |
| S2 | Speed Bump Detection – Night | As a driver at night, I want the system to recognize even unmarked bumps so that I am warned early. | High | • System identifies both marked and unmarked bumps at night • Driver receives a clear and timely warning • Detection accuracy remains high |
| S3 | Speed Bump Detection – Extreme Weather conditions | As a driver in fog or storms, I want bumps detected or supplemented by previous logs so that I can ensure safety. | Medium | • System detects bumps despite reduced visibility • False positives minimized • Detection supplemented with historical data if visibility is too low • Driver alerted in time to act safely |
- Reliability: 24/7 operation, minimal downtime
- Usability: Alerts must be simple and non-distracting
- Scalability: Can handle multiple anomalies in a single trip
- Maintainability: Detection models are easy to update
To make the requirements measurable and testable (aligned with IEEE standards):
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Performance Constraints:
- Alerts must be issued within 1 second
- Logging must occur within < 5 seconds delay
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Accuracy Thresholds:
- ≥ 90% detection rate in normal conditions
- ≥ 80% detection rate in extreme weather
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Safety Considerations:
- No false negatives for severe potholes
- Alerts must always provide sufficient reaction time
This backlog ensures that the system:
- Works across time (day/night) and environmental conditions (clear, rain, dust)
- Provides timely, accurate alerts for driver safety
- Maintains reliability and scalability for real-world road conditions