NIRA and Renovo Partner to Address Road Roughness Conditions


A self driving car concept. / Photo by: smoothgroover22 via Flickr


Signs of falling apart in roadways, such as faded markers, are common in many cities worldwide and it affects the performance of self-driving cars. Two companies, NIRA and Renovo, have made a partnership to solve the challenges of road roughness monitoring.

Automated mobility OS maker, Renovo, and automotive systems company, Nira Dynamics, are going to integrate two of their technologies to mitigate issues caused by road roughness in autonomous vehicles. The NIRA Road Surface Information software and the Renovo AWare OS are involved in the partnership.

“NIRA Dynamics is a leading creator of road surface information technology and is an important addition to the AWare ecosystem. Not only does NIRA Dynamics RSI help automated driving systems perform better in adverse and emergency situations by having more precise grip information, but it also provides a new revenue stream to automated mobility fleet operators running Aware,” said Chris Heiser, CEO and co-founder at Renovo.

The RSI software uses advanced sensor fusion to gather information about road surface and notifies the driver of any changes, including road bumps and potholes. Unlike with other available systems, the sensor fusion powered by a machine learning utilizes signals from existing automotive grade sensors, like wheel speed, to produce the necessary data.

Meanwhile, the AWare OS features automated mobility technologies including a self-driving AI, mapping support, remote operation, and monitoring control for drivers. The platform can simultaneously handle hundreds of sensors that generate several terabytes of data per hour while retaining its optimal performance under different road conditions.

Once RSI is integrated, it will use the existing sensors from the Renovo platform and at the same time, the AWare OS will ensure the smooth data transmission in RSI. The cooperative effort of both platforms is expected to improve how systems handle adverse situations in crumbling roads and assist road contractors in determining roads that need immediate maintenance.