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THE POTHOLE PATROL Using a Mobile Sensor Network for Road Surface Monitoring http://nms.csail.mit.edu/papers/p2-mobisys-2008.pdf Timothy Werner
Problem Potholes are everywhere Hard to find Car damage Lawsuits against the state Insurance claims
Test Deployment Attached to seven taxis in Boston for 10 days Covered nearly 2500 distinct kilometers Nearly 10000km total
Test Deployment - Accelerometer Placement Attached to car’s dashboard (glove compartment) Accurate Unobtrusive
Test Deployment – Training Data Trained for type of anomaly Crosswalks and Expansion Joint Railroad Crossing Pothole Manhole Stopping Turning
Pothole Detection Algorithm Speed High-pass z-peak xz-ratio Speed vs z ratio
Pothole Detection Algorithm Blacklisting Speed bumps Bridges Etc False Negatives – absence of reports does not mean a smooth road Drivers naturally try to avoid pot holes Roads are wide
Evaluation Tested on three data sets Carefully labeled data Loosely labeled data The taxis driving around Boston
Evaluation - Goals Detect a low number of anomalies on smooth roads Missing potholes is okay
Evaluation Classification accuracy on hand-labeled data Performance improvement using loosely labeled training data Performance on loosely labeled roads Spot-checks on uncontrolled data
Evaluation - Performance
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