Multi-sensor clusters enable precise assessment of road conditions. (Photo: XenomatiX)
The success of higher levels of vehicular autonomy will depend on two types of roadway corridor digital twins: pre-mapped and augmented on the fly. No matter how well the corridors are pre-mapped, there will always be the need for the vehicle to be self-aware — not only of the proximity of other vehicles and pedestrians, but also of changes to fixed features. New vehicles are being provisioned with multi-sensor clusters, including GNSS, cameras, lidar, sonic and more. This provides an opportunity to more precisely assess the condition of the road surface, which affects the performance of vehicle suspension systems, tires, fuel efficiency and general wear and tear.
“Imagine that your car navigation map system included roadway conditions,” said Karsten Bronowski, sales and business development manager for XenomatiX, “a global view where roads are color-coded based on their surface types and roughness. And all of this is mapped by systems like ours or added to the mobile systems mapping all the roads.
“Our product actually came out of the automotive world, and we still have customers that use it as a reference system for active suspensions, for mass-spring damping systems,” Bronowski said. For these applications, the sensors were mounted facing forward for a preview mode. “We have worked with the Belgian Road Research Center and others with applications to readily provide the international roughness index.”
XenomatiX was formed in 2013, focused on developing true solid-state lidar. “The idea was to get the motor out of lidar,” said Bronowski. “You have moving parts, you have wear and tear, the effects of vibration, problems with long-term reliability and with controlling temperature. With true solid-state lidar, you eliminate these issues.” Micro-electromechanical systems (MEMS) lidar systems still have moving, opto-mechanical components. Bronowski said that the solid-state systems feature a CMOS-based detector generating high-density point clouds in all weather conditions, and a multi-beam laser projector generating a high-resolution grid of points.
The dual lidar sensor system gets its orientation and positioning from additional components, including GNSS and IMU. The system that Bronowski showed at Intergeo 2022 had Septentrio AsteRx-U3 GNSS/IMU units supporting dual antennas for heading. However, they are using other means to improve both relative and absolute positioning: “How we do this is one of our secrets. For one of our customers in Japan mapping local highways, we proved to have excellent compensation, even tracking precisely through a 4-kilometer-long tunnel.”
XenomatiX has developed software to analyze data for many applications, automate feature recognition, and even validate other data. For instance, one customer in the United States is a big player in the satellite imaging sector that wants to match that data with pavement markings the XenomatiX system picks up.
While there is a needed calibration step and the requirement to align the detector for the dedicated measurement vehicle, sensor systems such as this can be put on just about any type of vehicle — on- or off-road. The driver does not need to intervene much, and the processing is done on a standard PC or laptop. “The customer does not care about the systems, just the data that comes from it,” Bronowski said.
