Project
| # | Title | Team Members | TA | Documents | Sponsor |
|---|---|---|---|---|---|
| 36 | RoadSense: Road Condition Detection and Pothole Mapping System |
Adam Moine D'Angelo Manzo Jovan Kular |
Shengkun Cui | ||
| # RoadSense: Road Condition Detection and Pothole Mapping System Team Members: - D’Angelo Manzo (dmanz2) - Adam Moine (moine2) # Problem Describe the problem you want to solve and motivate the need. Road damage like potholes, bad pavement, and large joints on the road can be really difficult to report and keep track of consistently. For someone just driving over it with their car, they aren’t able to gauge just how bad the road is. This isn’t just for roads that cars drive on, its for roads that include bike lanes. These bike lanes accommodate scooters, bikes, skateboards, and other EV devices. From experience, these road conditions, especially for bike lanes, can be dangerous and cause accidents if not careful. It could also cause irreparable damage to these devices, which could cost a lot of money. The main problem is, people who ride on these roads have no idea whether they are safe for the mode of transport they decide to use. # Solution Our solution would be a small sensor system that can be mounted on a car or bike to measure the motion caused by the roads surface. This system would use acceleration, rotation, vibration, speed of vehicle, and gps to identify road events. The system should be able to separate a pothole or rough pavement from normal events like braking, turning, or going over a speed bump. The sensor unit we would build would be mounted to any vehicle, and would use a software application to analyze the recorded data. During a trip, it will measure 3 axis acceleration and angular velocity. It will also provide information from a sensor that measures the frequency of road vibrations as well. The gps data will provide the location and speed. Finally, we would use a microcontroller to compile all the measured data and store it. # Solution Components ## Motion and Orientation Sensing Subsystem This subsystem measures the motion of the vehicle caused by the road surface. The part we would use is a Bosch BMI 270 six axis IMU. It would provide 3 axis acceleration and velocity information. It would be mounted directly on the main pcb. The accelerometer and gyroscope data will be used together to estimate the sensor orientation so the software can calculate vertical acceleration even when the enclosure isn’t perfectly level. ## Vibration Signal Subsystem This subsystem will measure high frequency vibrations caused by potholes and rough pavement. We would use a piezoelectric vibration element to detect the vibrations and covert them into an electrical signal. We would also use an MCP6002 operational amplifier along with resisters and capacitors to amplify, filter, and adjust the signal so it can be safely read by the microcontroller. The conditional signal will be recorded with stm32f411ceu6 adc along with imu and gps data. ## Location and data logging subsystem This subsystem would record the location, speed,and sensor data collected during the trip. A u-blox MAX M10S GNSS receiver will provide the vehicles gps location and speed. The STM 32F411CEU6 microcontroller will conllect the gps data along with measurements from the imu and vibration sensor and add timestamps to the data. ##power subsystem This subsystem would provide power to the sensors and the microcontroller. THe system will receive power from a low voltage usb source using an ap2112k-3.3 voltage regulator. Capacitors will be placed near the components to help keep the power supply stable. There would also be input protection to help protect the circuit from unstable or incorrect input power. # Criterion For Success 1. The system will sample and record data from the IMU, vibration sensor, and gps all at the same time, at a rate of 100 samples per second for the imu. 2. The system will record at least 30 minutes of continuous data to a storage device without losing or corrupting data. 3. The system will detect at least 90 percent of potholes that provide a vertical acceleration. 4. The system will distinguish between speed bumps and potholes with at least a 80 percent accuracy. 5. The system will distinguish between rough road sections from smooth ones with a 90 percent accuracy. 6. Each road event that is detected will induce its time, location, speed, event type, and severity. 7. The mapping software will display the recorded trip and detect road events on a map, including their locations and severity. 8. When the same road defect is detected, the software will provide a caution signal for future trips. |
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