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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.

We often hear the anecdote about an early lidar scanner that could take a shot every few seconds, yet it held a value proposition for certain applications. As the capabilities of successive mapping and surveying systems change rapidly, so does the conventional wisdom about which are best for various applications. Transportation corridor mapping — be it for improvements design, as-built surveys, asset management or digital twinning — has always been a balancing act between precision and efficient large-scale data capture.

“I remember 15 years ago, during my university time, the scanner was the size of a dining table,” said Andrei Gorb, segment manager for mobile mapping and unmanned aerial vehicle (UAV) systems, CHCNAV. At the top end of the mapping food chain were terrestrial scanners, targets, bore sighting, and registering point clouds mostly manually. As cumbersome and time-consuming as the legacy tools and methods were, these options still offered efficiency gains compared to conventional surveying with total stations. Then a decade ago, mobile-mapping systems began to change that paradigm. Departments of transportation found that mobile-mapping systems could meet their requirements for many design projects, and certainly for asset inventory and management. Unmanned aircraft systems (UAS) were not quite there yet.

The tech used depended on the application. “First, there was road maintenance, to understand the road condition,” Gorb said. “Previously, UAS did not meet the high requirements: centimeter in absolute and millimeter in relative. We now have mobile-mapping solutions, from us and other suppliers, that can be in the 8-9 mm absolute accuracy range on short road surfaces.” Yet for many transportation applications, the absolute accuracy may not be as important as the relative precision. This is where years of development in UAS has made the difference.

CHCNAV was not alone in recognizing that the gap was closing, and the company planned ahead. “Previously, UAS would fly for under an hour, and were mostly carrying cameras or early lidar, which was not suitable for highways,” Gorb said. “A few years of development, and we see it is practical to meet requirements with UAS flying between 50 and 100 meters — in Europe, many local regulations forbid flying above 120 meters anyhow.” Gorb attributes the advances to lidar sensors that UAS can carry. These sensors have become much better and less expensive. Plus, platforms like vertical-take-off-and-landing (VTOL) systems can stay in the air much longer.

The UAS boom of the past 10 years saw the dominance of consumer-prosumer market UAV platforms becoming quite commoditized, with certain vendors gaining majority market share. CHCNAV, instead, sought to develop enterprise solutions, for both mobile and UAS systems — large-platform rotor, fixed-wing and VTOL platforms. The company offers an amalgam of hardware and software, from Riegl scanner heads on some of their mobile-mapping systems to Honeywell inertial navigation systems (INS) for some of their UAS solutions.

Gorb echoes what we hear from many mapping practitioners, saying ground-control points are not as necessary in the densities required for legacy mobile and UAS mapping. He explained that everything from strip adjustments to processing of GNNS/IMU data has tightened both precision and accuracy. “We have a tactical-grade IMU in both our mobile mapping and UAS solutions, for a high-end trajectory,” Gorb said. “So, it means that we can get the same high-accuracy point cloud for highways from the ground and the air perspectives.”

To reduce its emissions, DPD Deutschland — a franchise of DPDgroup, one of the largest international parcel carriers in Europe — has asked Trimble Maps to help optimize its operations. DPD Deutschland’s parcel supply chain covers 80 franchise depots, 9,500 employees and more than 13,000 drivers, delivering about 2 million packages to businesses and consumers per day via a mixed fleet of vehicles, including electric ones.

DPDgroup has a vision to become the international standard in sustainable delivery by 2030. Per parcel, it has reduced its CO2 emissions by 18.8% since 2013 and is on track to reach a 30% reduction by 2030, according to Trimble.

One of DPD’s most popular service offerings, called Predict, allows parcel recipients to track the progress of their deliveries in real time, with an estimated one-hour delivery window and updated notifications along the way. Since 2014, Trimble Maps’ portfolio has helped calculate this one-hour delivery window and provided turn-by-turn navigation to DPD drivers, resulting in less overall travel time, more successful first-time deliveries and reduced emissions.

DPD was the first, and still is the only, parcel carrier in Germany that provides recipients with an estimated one-hour delivery window, the company says, calculating it for every parcel. The service is made possible in part by the integration of Trimble Maps’ route optimization and mapping web services platform, known internally as DPD Maps. Recipients can reschedule deliveries as needed for future days and times, or perhaps to a convenient drop-off location. This reduces emissions created by multiple return trips.

DPD Maps calculates an optimized route for drivers, who are then able to manually sort the stops and change the route to best fit their preferences. Once routes are locked in, Trimble’s commercial navigation application, CoPilot, provides drivers with real-time directions. Once a driver’s route is complete for the day, DPD can compare the actual route taken with the optimized route DPD Maps calculated in an easy-to-understand view that can be analyzed by the driver and the depot.

DPD Maps allows the company to visualize, share and discuss results with different stakeholders within the organization. The solution also allows drivers to plan out their day as they see fit, while giving the back office access.

This fall, Orolia’s Ultima-DT was certified as an emergency locator transmitter with distress tracking (ELT-DT) by Cospas-Sarsat, an international humanitarian search-and-rescue system. Cospas-Sarsat uses space-based technology to detect and locate model 406 emergency beacons carried by ships, aircraft or individuals venturing into remote areas — often inaccessible by GNSS signals. The system consists of a network of satellites, ground stations, mission control centers and rescue coordination centers that work together when a 406 beacon is activated.

I spoke about the certification with Christian Belleux, director, Aviation & Defense Beacons for Orolia.

Matteo Luccio (ML): Has Orolia produced aviation safety products in the past?

Christian Belleux (CB): Orolia has been supplying emergency locator transmitters for aviation since 1995 on a very large number of platforms to OEMs and airlines for use on commercial aircraft — Airbus, Boeing, Embraer and Bombardier aircraft. Orolia is also participating in industry groups creating standards (Eurocae, RTCA, ARINC) or contributing to the progress of the Cospas-Sarsat search-and-rescue satellite system as a member of the Expert Working Group.

ML: What are the key challenges in making an aviation ELT?

CB: With new requirements for lithium batteries and new regulations introducing distress tracking, recent times have been rich in innovation. We were granted the first ETSO certification ever for an ELT-DT and the same product, the Ultima-DT, was also the first ELT to be certified for its lithium battery.

ML: What did Cospas-Sarsat certification of the ELT-DT entail?

CB: The ELT-DT is a new type of beacon with a new communication protocol. The labs performing the certification tests must be approved by Cospas-Sarsat before we can apply. Then the Cospas-Sarsat organization and infrastructure must be updated to receive and consider the new ELT-DT protocol. The Cospas-Sarsat certification of our ELT-DT means that it complies with the performance requirements described in Cospas-Sarsat standards and can communicate with the infrastructure.

ML: What is new about an ELT-DT?

CB: The principle of an ELT-DT is to activate in flight before a crash, as opposed to a legacy ELT that is activated by the shock of a crash. This means that the aircraft and the ELT-DT can analyze the health of the aircraft and its parameters, and activate if a catastrophic event is about to occur. Once activated, the ELT-DT transmits a high-rate distress signal that makes it possible to track the aircraft until it crashes. The ELT-DT contains its own GNSS receiver that is independent the aircraft’s navigation system.

ML: Did you cooperate closely with one or more avionics manufacturers to develop your device?

CB: Orolia was in very close contact with Airbus, which designed the avionics components.

ML: Do you already have contracts with airlines or aircraft manufacturers besides Airbus for the Ultima-DT?

CB: We have several contacts with aircraft manufacturers and airlines interested in the Ultima-DT.

ML: When will the first batch of the ELT-DT / Ultima-DT be operational?

CB: We started flight tests months ago at Airbus and delivered production units. Airbus soon will announce its first delivery of an aircraft equipped with the Ultima-DT.

When it comes to ground transportation, most of the R&D regarding GNSS is aimed at developing driver-assist systems and, ultimately, driverless cars and trucks. For that purpose, GNSS receivers are integrated with inertial navigation systems, radar, lidar, computer vision and ultrasonics.

Leveraging decades of robotics experience and knowledge of control algorithms, AutonomouStuff, part of Hexagon’s Autonomy & Positioning division, has developed a software stack for autonomous vehicles based on the Apollo open-source software stack.

“Think of this software stack as a brain powering the autonomous platform,” said Kevin Fay, product manager for Hexagon’s platforms and vehicle software business. The software stack can be customized across platforms and to meet equipment needs.

Most recently, in a collaborative project with the National Advanced Driving Simulator at the University of Iowa, AutonomouStuff worked with the Automated Driving Systems for Rural America project to outfit a Ford Transit 350HD shuttle for autonomous operation. First, it created a drive-by-wire system that enabled electronic control of the vehicle, and then it installed positioning, navigation and perception sensors. The result is a platform ready to be autonomous as soon as the software stack is integrated.
Rural roads — which have a wider range of speeds than urban ones — may be encumbered by wildlife or heavy equipment. They also vary in surface from asphalt to gravel, providing a particularly challenging test environment for the autonomy software.

“The Iowa vehicle has done a sizable amount of automated driving on a combination of urban and rural roads, where traditional sensing falls flat,” Fay said. “It has excelled in areas such as gravel roads that have limited or no lane markings, or are narrower than normal. We deployed it earlier this year to do things such as traffic-light detection with the cameras on board, so that it navigates traffic-light intersections appropriately.”

While rural roads are generally free of the GNSS multipath challenges presented by urban canyons, they also provide fewer navigation landmarks. Another challenge is inclement weather. During snowstorms, Fay pointed out, country roads might be unplowed. “If you run on the right lane of the road all the time, you might be out of the ruts that are on the road, and then you’re struggling to get through.” The vehicle must learn to navigate appropriately in those conditions.

The University of Iowa Ford Transit shuttle is a limited deployment, mainly to collect data for research purposes. Meanwhile, it is giving real rides to residents, though with a safety driver. “They’re always attentive, but their hands will be next to the wheel,” Fay said. “There will be times where they may have to take over.”

Other universities and companies are using the platform to further their autonomy programs. Most of them are doing urban driving in complex routes with live traffic, for a total of a dozen vans nationwide.

Hexagon equips the vehicles with a variety of sensors, including a front-mounted adaptive radar, a roof-mounted Velodyne lidar, a roof-mounted NovAtel GNSS receiver and cameras mounted inside the vehicle. “Which ones we provide depends largely on the customer and on which software they’re deploying,” Fay said. “We provide our customers a complete package that can be used with minimal work out of the box. It has the software, the interface to the vehicle, and sensors on it. But we can also provide them with a vehicle that simply has an interface for control, and they add their own computer and software on top of it.”
Hexagon’s first Ford Transit was deployed in 2021. The company released the current version in the spring of 2022, and the Iowa project is slated to run through the middle of 2023. “We’ve not had something running in live traffic before,” Fay said, “so it allows us to continue to grow our skill sets and our overall expertise.”

ASENSING, a Chinese positioning solutions company for autonomous vehicles, is ready to provide its navigation systems globally. The company already has more than 500,000 autonomous vehicles integrated with its navigation systems and is discussing global product expansion with major Western brands.

ASENSING is the first in series production of an automotive solution that combines IMU and GNSS, enabling it to develop an algorithm to maintain navigation accuracy at various temperatures. Its positioning solutions are designed for autonomous driving at L2 level and above and meet functional safety requirements.

ASENSING has received nominations from more than 20 OEMs to provide solutions for more than 70 vehicle models. Additionally, the company has partnerships with traditional brands such as SAIC, Geely, and Chery, as well as with new energy vehicle makers, including XPeng, Li Auto, and NIO.

The company has three global branches, in the United States, Germany, and Japan with plans to launch more smart plants in east and south China to accommodate for an influx of orders. ASENSING will exhibit its mass-produced positioning solutions at the Consumer Technology Association’s Consumer Electronics Show 2023 in Las Vegas, Nevada.

On Dec. 20, u-blox banned the use of its GNSS modules in military UAVs in the war between Russia and Ukraine. The company had become aware that its GNSS modules were being used in certain Russian reconnaissance UAVs and stated that this use was against company policy.

U-blox obtained media reports that Russia had stocked up on components in anticipation of war, then integrated products from the company in UAVs it manufactured after attacking Ukraine.

After Russia began its invasion of Ukraine, the company halted all sales to Russia, Russian territories, and Russian-occupied areas, as it intends its GNSS modules and other products to be used only commercially. U-blox company policy bans the use of its products in weapons, including systems for target identification.

U-blox is investigating the infringement of its policy and plans to take legal action if it has been violated. The company also condemns the invasion of Ukraine by Russian forces.

On Dec. 22, Hexagon AB announced its acquisition of LocLab, a German company that specializes in 3D digital twin content creation. LocLab will operate as a part of Hexagon’s Geosystems division.

This acquisition, which began as a partnership, strengthens Hexagon’s ability to make its Smart Digital Reality, a 3D hub for data management and information, more accessible to new and existing users while giving LocLab’s users a platform to host, share and keep 3D digital twins up to date.

LocLab’s toolchain leverages several data input formats such as terrestrial videogrammetry, survey data and point clouds, but only requires photos or videos. Hexagon is integrating LocLab’s 3D digital content with its HxDR cloud-based storage, visualization, and collaboration platform. This integration drives HxDR’s expansion as a digital reality platform into the transportation, construction and urban planning industries.

The integration of HxDR and LocLab’s capabilities strengthens Hexagon’s reality capture and software portfolio while offering LocLab global scalability opportunities through Hexagon’s sales and partner network.

On Dec. 20, the Linux Foundation announced its AgStack Project, which will host an open-source code base, along with a fully automated, continuous computation engine that will maintain a global dataset of boundaries for agricultural fields. The AgStack Asset Registry dataset will aid food traceability, carbon tracking, crop production, and other field-level analytics.

This ‘registry’ is designed to continuously update using data from satellites and real field registrations that contain boundary information, which will train machine learning models to ascertain more boundaries, among other capabilities.

Agricultural datasets are rarely public information. By using computer science and artificial intelligence (AI), users can create global field boundaries as a digital open source for public use, which can help farmers, agricultural companies, and the public manage crop production, study management practices, assess levels of productivity, monitor the spread of pests and diseases and more.

The AgStack project seeks to enable all types of agricultural data and services by combining computing and AI expertise with a global network of partners in an open-source software system. All code is being contributed under an open-source license and will be governed by the AgStack community, within the Linux Foundation.

Point One’s FusionEngine software, which is rated for automotive safety integrity level (ASIL), is now compatible with STMicroelectronics’ Teseo ASIL Precise Positioning GNSS chipset (TeseoAPP). This assures functional safety as ASIL-B, a requirement for Level 3+ advanced driver assistance systems (ADAS).

FusionEngine can be integrated into several different host processors that are used for enabling high level ADAS and autonomous driving systems. The combination of TeseoAPP’s receiver and the STA5365S external RF front-end provides dual-band measurement data for all visible GNSS satellites to the main host processor into which FusionEngine is integrated.

FusionEngine software is a precise location solution for automotive applications. For accuracy and to ensure the safety and integrity required for high level autonomous vehicles it combines data from multiple sensors, including the TeseoAPP multi-band GNSS receiver. It also enables developers to complete the functional safety concept phase for host system software integration.