Name
Abstract | ||
|---|---|---|
This paper investigates an application of mobile sensing: detecting and reporting the surface conditions of roads. We describe a system and associated algorithms to monitor this important civil infrastructure using a collection of sensor-equipped vehicles. This system, which we call the Pothole Patrol (P2), uses the inherent mobility of the participating vehicles, opportunistically gathering data from vibration and GPS sensors, and processing the data to assess road surface conditions. We have deployed P2 on 7 taxis running in the Boston area. Using a simple machine-learning approach, we show that we are able to identify potholes and other severe road surface anomalies from accelerometer data. Via careful selection of training data and signal features, we have been able to build a detector that misidentifies good road segments as having potholes less than 0.2% of the time. We evaluate our system on data from thousands of kilometers of taxi drives, and show that it can successfully detect a number of real potholes in and around the Boston area. After clustering to further reduce spurious detections, manual inspection of reported potholes shows that over 90% contain road anomalies in need of repair. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1145/1378600.1378605 | MobiSys |
Keywords | Field | DocType |
pothole patrol,road surface monitoring,good road segment,boston area,road anomaly,surface condition,accelerometer data,training data,opportunistically gathering data,road surface condition,gps sensor,severe road surface anomaly,mobile sensor network,machine learning | Mobile sensing,Accelerometer,Computer science,Taxis,Real-time computing,Road surface,Global Positioning System,Cluster analysis,Wireless sensor network,Detector | Conference |
Citations | PageRank | References |
348 | 23.81 | 12 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jakob Eriksson | 1 | 1157 | 69.52 |
| Lewis Girod | 2 | 3105 | 404.33 |
| Bret Hull | 3 | 1243 | 91.11 |
| Ryan Newton | 4 | 802 | 70.80 |
| Samuel Madden | 5 | 16101 | 1176.38 |
| Hari Balakrishnan | 6 | 31665 | 3441.21 |