SafeOverPass: An Edge-Based Low-Clearance Overpass Warning System

摘要

Preventing accidents on the roads and increasing safety measures are essential to reducing traffic jams and saving lives. One of the major road accidents in the United States involves tall vehicles and overpasses. Although there are commercial truck overpass warning systems in the market, the majority of these systems include a certain percentage of overpasses that exist on predetermined truck routes and not city streets. These systems do not incorporate machine learning models that use historical driving route data to predict the next route segment a tall vehicle will be adopting. In addition, these systems require regular updates and maintenance and eventually run out of storage space. In this work, we propose SafeOverPass as a low-clearance warning system that leverages edge computing and machine learning to provide essential warning mechanism to tall vehicle drivers. Our results show that SafeOverPass can provide the driver with early low-clearance warning to prevent accidents without any hardware or software complexity for the user.