What role does sensing play in reducing potholes?

In the distant past, the “eye in the sky” was a radio report on local traffic, especially during rush hour, provided by a reporter/observer and based on their observations from a helicopter or low-flying aircraft. For real-time radio reports, sensing was not necessary. Evolving into TV reporting and planning before departing for work (long before Google Maps), cameras were added to the process. More recently, the eye in the sky has become associated with drones with various payload sensors to provide surveillance for police and even military operations.

Now, a very down-to-earth eye can provide critical information and a response to something drivers encounter during any commute – even when they are the only ones on the road. Using advanced imaging technology, such as high-resolution cameras and LiDAR sensors, the ARRES Eye system detects surface problems on roads, and with GPS, it accurately locates where they are. Developed by Robotiz3d, the Autonomous Road Repair System (ARRES) Eye is the first step towards autonomous robots for automatically detecting and repairing various road problems.

Once a problem is detected, today’s process involves identifying the pothole’s exact location, assessing its severity, and prioritizing its repair. The collected data is logged into a central database for management, allowing monitoring of a large area.

As part of a robot as a service (RAAS) offering, Robotiz3d maintains all the hardware and software, minimizing the up-front costs of implementing the service. The system can survey and analyze road surface conditions without human intervention. Installed on existing working or work-related vehicles, such as buses, vans, and more, the system can perform its function in parallel with the normal function of the host vehicle.

Developed by tech company Robotiz3d and academics at the University of Liverpool, the ARRES Eye performs several functions, including:

• Provide highly accurate data on the defect and its location
• Provide depth information and volumetrics
• Collect data when traveling up to 60mph
• Scan one lane at a time with a field of view (FoV) up to 3.0m
• Collect highly accurate road defect data to enable informed, efficient decisions
• Operate both day and night in any weather conditions

The system automatically identifies road defects, such as potholes and cracks, and distinguishes them from other discontinuities, such as manhole covers. With its vision sensing capabilities, the system classifies the types of defects from potholes, including the width, length, and depth measurements in centimeters. It provides a rating from minor to moderate to severe. The exact process occurs for detecting cracks using the same criteria provided. With this data, the needed repairs and the appropriate priority assigned for implementing them can be categorized.

For Robotiz3d, the next step is to automate the repair process. The ARRES Prevent combines the ARRES Eye with artificial intelligence (AI) in an unmanned robotic vehicle with all the required equipment to fix potholes and cracks when they are observed. This vehicle is already in trial mode. However, the ultimate pothole-fixing goal is a robust machine designed for more extensive repairs. With the ARRES Ultra, Robotiz3d plans to address larger surface cracks and fully-grown potholes. But it all starts with the ARRES Eye to sense the problems.

References

All images: https://www.robotiz3d.com/