Flipping the traditional scenario, in which car racers risk their lives on a racetrack, the Indy Autonomous Challenge (IAC) aimed to help save lives by improving collision avoidance systems, train future automotive engineers, and make the public more comfortable with autonomous cars. Held Oct. 23 at the Indianapolis Motor Speedway and organized by Energy Systems Network, the race saw 21 universities from nine countries forming nine teams to compete for a $1 million grand prize. Following in the footsteps of the DARPA Grand Challenge, first held in 2004 and later renamed the DARPA Urban Challenge, the IAC was the world’s first high-speed autonomous race. The winning team was TUM Autonomous Motorsport from the Technical University of Munich, Germany.
All competing teams were given the same identical vehicle to work with, a Dallara AV-21, modified to carry no one in the cockpit and equipped with two Hexagon | NovAtel PwrPak7-Ds multi-frequency, multi-constellation GNSS receivers, six cameras (two of which faced backward), three lidar scanners and four radars. Each team had to develop its own autonomy-enabling software stack, including the algorithms and neural networks. All the components, except the computer, had to be commercial-off-the-shelf, available on the market. No sensors could be custom-made.
Since 2001, Dallara has been the sole supplier of the Indy Lights series, a championship to prepare drivers for the NTT IndyCar Series. The Dallara AV-21 is a collaboration between Dallara’s Italian headquarters in Varano Melegari (Parma) and Dallara IndyCar Factory in Speedway, Indiana. The new car offers a modern, stylish appearance and provides the proper training required for drivers as the final step on the ladder to the NTT IndyCar Series.
The process by which the automated vehicle sensors and computers were fused into a singular package and integrated into the AV-21 was led by Clemson University’s International Center for Automotive Research’s Deep Orange 12 (DO12) project. The Deep Orange process mirrors that of automotive original equipment manufacturers (OEMs), and the DO12 project scope allowed for engineering and innovation across multiple subsystems. Student groups within the DO12 team explored solutions within and across multiple subsystems, including:
vehicle-to-vehicle communications
perception systems
onboard computing
drive-by-wire chassis control systems
vehicle dynamics
vehicle-to-infrastructure communications
powertrain design and integration
vehicle demonstration based on high precision GPS.
Hexagon’s Autonomy & Positioning division provided GNSS receivers and subject-matter experts to the Deep Orange 12 team. The team architected the sensor kit for the Dallara reference vehicle, which AutonomousStuff then replicated 10 times. The team did not compete in the IAC to avoid a conflict of interest and allow students to work closely with competitor teams from universities around the world. The PwrPak7-E1 contains a MEMS IMU to deliver Hexagon | NovAtel’s SPAN technology, a deeply coupled GNSS + inertial engine in a single-box solution. Each GNSS receiver has two antennas to provide heading. The Deep Orange 12 team used HxGN SmartNet RTK corrections, which brought the accuracy down to a few centimeters.
Without developing a driverless decision-making algorithm, Clemson students tested the vehicle with the help of a high-precision positioning system. They developed a control algorithm that can track the optimal line around the Indianapolis Motor Speedway such that all vehicle systems could be validated in a simulated racing environment. Data from these tests were shared with the competition teams to aid in their development of driverless algorithms.
Energy Systems Network will host a head-to-head, high-speed autonomous racecar passing competition at the Las Vegas Motor Speedway on Jan. 7, 2022, during the Consumer Electronics Show. Several of the teams that competed in the IAC, including the winner and finalists, will participate. The primary goal is to advance technology to speed commercialization of fully autonomous vehicles and deployments of advanced driver-assistance systems.
Swiss company u-blox designs and manufactures GNSS receivers used in the automotive market, including driverless cars, and for micro-mobility devices, such as the Bird scooter.
In deep urban canyons, the biggest challenge for positioning cars is achieving sufficient accuracy despite multipath, said Aravinthan Athmanathan, product manager for the company’s Automotive GNSS line of receivers. “The challenge for autonomous driving is reliable lane-accurate positioning and integrity.”
The company develops its own dead-reckoning algorithms, which use data from an inertial measurement unit (IMU) and wheel speed sensors. “We also provide dual output, so the end customer can choose whether to use GNSS only or a sensor-fused solution,” said Athmanathan. This is especially challenging at the sub-meter accuracy level.
Different Uses, Different Sensors
Different automotive use cases require different GNSS receivers. To meet this challenge, u-blox offers the NEO-M9L for standard precision and the ZED-F9K for high precision, depending on the customer’s needs. Additionally, it is investing a lot “in functionally safe GNSS and in being the GNSS enabler for car manufacturers,” said Karin Steinhauser, the company’s senior marketing communications manager.
For navigation with meter-level accuracy, the NEO-M9L is integrated with dead-reckoning technology and sensor fusion, using algorithms that process sensor data from the IMU and from wheel-speed sensors. It can provide reliable location data in challenging environments, such as urban canyons, where multipath becomes an issue, or tunnels, where GNSS signals are partially or totally denied, Steinhauser said. Additionally, the NEO-M9L can operate in temperatures of up to 105° C, making it suitable for integration on the roof, behind the windscreen, or inside hot electronic control units. The NEO-M9L addresses the use cases in urban environments for both navigation and systems, such as Europe’s eCall, that provide an automated message to emergency services following a road crash, including the precise location of the accident.
The ZED-F9K, on the other hand, is well suited for use cases at the higher levels of advanced driver assist systems (ADAS) defined by the Society of Automotive Engineers (SAE), which require decimeter-level accuracy. “At L3 and above, you need correction services with integrity to allow for trustworthy and reliable GNSS positioning,” Steinhauser said. “We have partnerships with Bosch on projects to develop functionally safe GNSS solutions based on a ISO26262-certified version of u-blox generation 9 GNSS technology.” The ZED-F9K is a multi-band receiver that uses GPS signals on L1-L2 and Galileo signals on E5b. “We also have a special set of features adequate for the ADAS and the autonomous driving features,” Athmanathan said.
Image: 3alexd/E+/Getty Images
Bottlenecks
One of the factors limiting how quickly u-blox can roll out solutions based on the ISO 26262 standard (titled “Road vehicles – Functional safety”) is that highly autonomous systems require more integration work by the customers, said Alex Ngi, the company’s product manager for High Precision GNSS. “The first systems are now available.” Another hurdle, he pointed out, is the legal framework for deploying autonomous driving systems. “The regulations about how things need to be tested, and the liabilities for when systems fail, affect how quickly these systems can get adopted.”
GNSS can be used as a complementary technology to enable absolute positioning for systems that fuse data streams from cameras and lidars, such as those used for ADAS level 2 applications. “Fusing all this is computationally intensive and requires high processing power, such as NVIDIA GPUs, which tend to be very hot systems. We see a lot of requirements for very high-temperature GNSS receivers, because our receivers are often co-located with these hot systems.”
Of course, u-blox does not simply hand its modules to Bosch and car manufacturers and say, “You take it from here.” Design and integration is an iterative process. “We bring in the GNSS know-how and integration support and Bosch brings in the functional safe automotive development know-how,” Ngi said.
Dead Reckoning and Map Matching
For the automotive market, u-blox has more than 20 years of experience with dead reckoning. “The sensor-fusion solution receives data from both the GNSS and the IMU, and we provide the complete final solution,” Athmanathan explained.
The system also aids the receiver by providing it external map data. “If you’re driving your car northbound and the GNSS receiver tells you that it’s headed in the opposite direction, or that you’ve jumped over to the lane to the other side of the highway, clearly that cannot be right,” Ngi said. “Map matching relies on simple messages that come into our receivers to give us positive feedback on our measurements.”
For non-automotive applications, u-blox makes the ZED-F9R. It is used, for example, in robotic lawnmowers, very common in Asia and Europe, which require centimeter-level accuracies. “That’s why it focuses on delivering corrections using SPARTN, which can be a continent-wide data stream,” Ngi said. “We also make the design so that it’s very easy to integrate and enables the designers to easily pass the corrections to their receivers fully encrypted. This way, the value of the data is delivered to the lawnmower without exposing it to the system designer, so that we don’t need to go check every design to see whether somebody is leaking secured correction services.”
By the end of November, according to u-blox, updates of the ZED-F9P multi-band GNSS receiver will include decryption of the SPARTN correction data and a 95-percentile protection level. The protection level increases the trust non-safety-critical applications can place in its position output. By continuously outputting the upper bound of the maximum likely positioning error, referred to as the protection level, the receiver lets autonomous applications, such as UAVs or robotic lawnmowers, make efficient real time path planning, increasing the quality of their operations.
Guiding eScooters and EVs
In some places, Ngi pointed out, e-scooters are required to use a bike lane, which might be only two or three feet wide and may not be along the side of a building as it would be on a sidewalk. “The ZED-F9R is a much more flexible solution than camera systems that only know sidewalks or bike lanes.” Bird uses it to throttle driving speeds to match speed limits, which change from one location to another. “It is also much more scalable for them as opposed to such solutions as using UWB [ultra-wideband] beacons to fence off different areas, which are not really scalable for a company that wants to deploy solutions to hundreds of cities.”
Xpeng Motors, a manufacturer of smart electric vehicles, uses u-blox F9 GNSS receivers, which use signals from all four GNSS constellations, in its P7 super-long-range sports electric vehicle sedan. The vehicle uses ADAS for navigation-guided driving, automated parking and autonomous driving. For instance, once a navigation destination is set on a specific highway, the P7 will follow the route guidance to execute autonomous lane changing, switch to high-speed routes, and select the optimal route in real-time.
In April, the pizza company Domino’s and self-driving delivery company Nuro launched autonomous pizza delivery in Houston, Texas. Select customers who place a prepaid online order on certain days and times from Domino’s in Woodland Heights can choose to have their pizza delivered by Nuro’s R2 autonomous, occupantless on-road delivery vehicle.
Customers selected for the service receive text alerts, which update them on R2’s location and provide them with a unique PIN to retrieve their order. Once R2 arrives, customers are prompted to enter their PIN on a touchscreen, opening its doors.
In February 2020, Nuro became the first autonomous vehicle developer to be given exemptions by the U.S. National Highway Traffic Safety Administration for testing on public roads without the need to have controls for human operators. Unlike many other autonomous vehicle companies, Nuro engineered its self-driving road vehicles to transport goods instead of people.
There’s no set timetable for how quickly Domino’s and Nuro will evaluate their testing or expand the service.
Nuro is also carrying out trials and pilot deliveries with several other companies, including restaurant chain Chipotle, Kroger grocery stores, CVS pharmacies, Walmart and FedEx.
Scooter company Bird and u-blox have jointly developed a new Smart Sidewalk Protection system to help prevent shared scooters from operating on city sidewalks. It uses the u-blox ZED-F9R, a dead-reckoning module that fuses GNSS and sensor data, delivering centimeter-level location information in any condition. This allows the system to monitor whether a Bird e-scooter is being operated unsafely, such as on a sidewalk or speeding. Using Bird data, the companies co-developed a version of the ZED F9R module tailored to meet the needs of the shared micromobility industry.
The dual-band ZED-F9R GNSS receiver supports up to eight times more satellite signal types and four times more constellations (GPS, Galileo, GLONASS and BeiDou) than typical solutions. The module processes real-time vehicle data, including wheel speed, IMU sensor data (including acceleration and heading), and real-time kinematic data that corrects for ionospheric interference. The technology is also optimized for e-scooters by applying dynamic models matching their movements.
To turn this sensor-fusion module into its Smart Sidewalk Protection system, Bird developed a five-step process for creating sidewalk maps with centimeter accuracy. It starts with a geofence outline constructed from satellite imagery or city GIS data. Bird then uses surveying equipment to measure the location of three city landmarks. Only a few measurements are needed for each city. Once the landmarks have been identified, they compare their location to the satellite imagery to determine offsets and rotations and use them to shift and transform each of the original geofence outlines. Finally, they pre-load the updated geofence outlines onto Bird vehicles to eliminate latency. When combined with the hyper-accurate location measurements provided by Bird’s sensor-fusion module, they can detect and respond to sidewalk riding almost instantly, according to Bird.
The micromobility module is being piloted in Milwaukee and San Diego. Madrid will be Bird’s first pilot city in Europe, with plans for a broader roll-out slated in 2022.
Tallysman Wireless Inc. has added the low-profile triple-band HC997EXF to its line of embedded helical GNSS antennas, and the TWA928LXF to its AccuAuto line. Both feature the company’s eXtended Filtering (XF).
Designed for UAVs and Other Applications
Photo: Tallysman
The HC997EXF is designed for precise positioning, covering the GPS/QZSS-L1/L2/L5, GLONASS-G1/G2/G3, Galileo-E1/E5a/E5b, BeiDou-B1/B2/B2a, and NavIC-L5 frequency bands. It also covers the satellite-based augmentation system (SBAS) available in the region of operation — WAAS (North America), EGNOS (Europe), MSAS (Japan) or GAGAN(India) — as well as L-band correction services.
The low-profile helical antenna is packaged in a light (11 g) and compact form factor (60 mm wide and 25 mm tall). Its precision-tuned, high-accuracy helical element provides an excellent axial ratio and operates without a ground plane. These features make the HC997EXF suitable for lightweight unmanned aerial vehicle (UAV) navigation and a wide variety of precision applications.
The HC997EXF antenna base has a flying lead and a variety of connectors. To facilitate installation, Tallysman provides an optional embedded helical mounting ring that traps the outer edge of the antenna circuit board to the host circuit board or any flat surface. Tallysman provides support for installation and integration of its embedded helical antennas to ensure optimal performance.
New Vehicle Antenna Launched
Photo: Tallysman
Another new XF antenna, the TWA928LXF, is part of Tallysman’s AccuAuto autonomous vehicle family of compact and rugged embedded antennas.
The triple-band TWA928LXF supports GPS/QZSS-L1/L2/L5, GLONASS-G1/G2/G3, Galileo-E1/E5a/E5b, BeiDou-B1/B2/B2a, and NavIC-L5 signals and frequency bands, including L-band correction services.
The TWA928LXF vehicle antenna features a patented Tallysman Accutenna technology antenna element, an integrated ground plane, radome and underside cover that provides mist and condensation protection. The bottom cover also supports the antenna cable and mitigates cable vibration to ensure that the antenna has a long service life, while the ground plane improves antenna performance.
All AccuAuto antennas are built with Automotive Electronics Council (AEC) certified electronic components designed to perform under the most challenging environmental conditions, such as extreme temperatures, shock and vibration.
XF Coming to All Lines
eXtended Filtering enables the HC997EXF antenna to mitigate new and existing radio frequency bands that interfere with GNSS signals. The custom XF filtering has been tested to mitigate new (Europe and Japan) and existing LTE signals, enabling the XF antennas to produce clean and pure GNSS radio frequency data.
For example, in North America, the planned Ligado service, which will broadcast in the frequency range of 1526 to 1536 MHz, could affect GNSS antennas that receive space-based L-band correction service signals (1539–1559 MHz).
Similarly, LTE signals or their harmonics, such as the new LTE bands in Europe–Band 32 (1452–1496 MHz)–and Japan–Bands 11 and 21 (1476–1511 MHz)–have affected GNSS antennas and receivers.
Lastly, the Inmarsat satellite communication uplink (1626.5–1660.5 MHz), commonly used on maritime vessels, can also affect nearby GNSS antennas.
Tallysman Wireless also has added eXtended Filtering (XF) to its TW3800 series of Accutenna precision antennas, and will be rolled out to all of Tallysman’s product lines.
A roundup of recent products in the GNSS and inertial positioning industry from the December 2021 issue of GPS World magazine.
OEM
Satellite-cell terminal
With built-in GPS receiver
Photo: OQ
OQ Technology’s dual-mode satellite-cellular IoT modem and tracker is a plug-and-play, small, low-cost and low-power solution that can collect data from more than 1,000 sensors. It has a built-in GPS receiver and supports 5G NB-IoT, GSM, LTE-M and bi-directional satellite links. The flexible, robust and programmable dual-mode terminal has pre-paid data packages suitable for remotely monitoring and controlling fixed and mobile assets in industries such as transportation, oil and gas, utilities, and maritime.
Provides mission-critical, extended length GPS over fiber
Photo: ViaLite
ViaLite’s GPS over Fiber Extension Kit for Microchip/Microsemi GPS timing servers provides mission-critical GPS timing and synchronization for systems requiring extremely accurate clock signals. Standard transmission distances for the extension kit can be up to 10 km, while solutions are available for distances as long as 50 km. The ViaLite kit was chosen for its unique performance with Microsemi’s S650 timing server. The ViaLite GPS link is designed to provide a remote GPS/GNSS signal or derived timing reference to equipment located where no signal is available, such as inside buildings or tunnels. By using optical fiber instead of traditional coaxial cable, extreme distances are possible with no radio frequency loss and zero introduction of noise.
The RELY-MIL-TIME-SERVER, which complies with MIL-STD-810G and MIL-STD-461G, embeds the latest timing, networking and security technology in a single SWaP platform. The all-in-one rugged edge computing device acts as a high-performance master clock and serves secure accurate timing distribution (PTP, NTP, GNSS). The timing feature is combined with high-bandwidth and high-availability Ethernet switching and L2/L3 cybersecurity services in a unique commercial-off-the-shelf device. At its heart is a Xilinx Ultrascale+ MPSoC device powered by SoC-e hardware IP cores for PTP and high-availability low-latency Ethernet networking.
The M-G370PDS0 inertial measurement unit (IMU) is equipped with a high-performance six-axis sensor. It has an angle random walk (short-term variation in output) of 0.03°/√h, which is half that of its predecessor, and can more accurately detect very slight changes in the attitude of equipment and systems, since they do not get lost in sensor noise. The small size, light weight and low power consumption will help customers make their own products smaller and lighter. It also maintains compatibility with earlier products (the M-G370/365/364/354), making performance upgrades easy.
The OSA 5400 SyncModule enables technology suppliers to integrate precise synchronization into their hardware. Its M.2 form factor can add timing capabilities to switches, routers, open compute servers and other IT devices. The SyncModule provides GNSS, precision time protocol (PTP) and network time protocol (NTP) engines as well as comprehensive PTP and GNSS monitoring and assurance functionality. It can enable assured sub-microsecond timing in public and private networks as well as critical infrastructure. Featuring multiple interface options for easy integration, the OSA 5400 SyncModule comes with an open API. It also can be managed by ADVA’s proven Ensemble Sync Director management system.
Running on Microsoft Windows, u-center 2 offers anyone working with 10th-generation (M10) u-blox GNSS technology a highly intuitive interface to configure GNSS products, evaluate their performance, improve the quality of their software, and experience the performance boost achieved using GNSS-related services. The software is the successor to the u-center GNSS evaluation software, which has been used by design engineers for almost two decades to develop GNSS receiver applications. Compatible with u-blox M10 GNSS technology, u-center 2 is designed to offer improved performance over its predecessor. New features in u-center 2 simplify configuration, evaluation and software development of GNSS-based solutions. It is free for download.
The MEA-1227-SM is a GNSS/L1 and L2 low-profile screw-mount antenna. It has high performance suitable for maintaining constant network connectivity. The MEA-1227-SM covers all GPS/GLO/BEI/ QZSS/Galileo/SBAS/L1L2 standard frequencies. It is designed for telematics systems, remote surveillance, asset tracking and any internet of things (IoT) system applications. This screw mount antenna is easy to install, with a low profile suitable for challenging installations. It has a IP67-rated housing and anti-rotation mounting.
The Cowboy e-bike solution provides riders with high-performance, real-time GNSS accuracy, enabling them to map their own paths and those of the cities in which they live. It uses smart road-companion applications to ensure riders get precise information, regardless of the route they travel. The positioning component uses Taoglas’ Accura GVLB258.A, a multi-band GNSS L1/L5, high-performance stacked patch antenna, in conjunction with u-blox’s SAM-M8Q GNSS positioning module. The combination allows for extremely low power and high accuracy. The solutions works with “micromobility” services offered by Cowboy, such as Easy Rider for theft detection, bike insurance and crash detection notifications.
Instant decimeter-level accuracy with automotive sensors
Photo: Profound Positioning
The Profound-IVT (instant vehicle tracking) provides cost-effective vehicle navigation. Based on a firmware library, and rapidly adaptable to any navigation platform, IVT combines precise point GNSS positioning (PPP), dead reckoning and radar technologies in an integrated solution to provide decimeter-level positioning accuracy plus orientation and velocity. IVT performs in tunnels, dense urban environments, multi-level highway junctions and parking garages. With errors <1% of distance travelled, resolution is extremely rapid. Base stations are not required and there are no operating range limitations. Applications include driver assistance, mobility and taxi, autonomous vehicles, geofencing, fleet tracking, insurance, driving and safety management, and connected driving.
Off-the-shelf map data through the HxGN Content Program
Photo: Hexagon
Metro HD city data is a new offering of ultra-high-resolution 2D and 3D digital twins of major cities. Metro HD expands the data stack to include high-definition true orthophotos, obliques, digital terrain models, lidar point clouds, 3D building models (LOD2), 3D meshes and land-use maps. Cities captured in 2021 include Munich, Cologne, Vienna, Milan, Amsterdam, Stockholm, Tokyo, Dallas, New York, Stuttgart and Frankfurt. More cities will be added in early 2022. The program uses a hybrid urban mapping sensor, the Leica CityMapper-2, that concurrently collects lidar and aerial imagery. The derived products, based on the strength of each subsystem, result in superior accuracy and temporal consistency across all three data dimensions.
Bad Elf LLC and Laser Tech are providing an integrated laser offset workflow for acquiring high-accuracy field data in GNSS-challenged environments. The new workflow integrates Bad Elf and LTI hardware in collaboration with ArcGIS technology from Esri. The Bad Elf Flex GNSS receiver connects to any LTI TruPulse rangefinder over a wired or Bluetooth connection to deliver high-accuracy location data to Esri ArcGIS Field Maps. Field workers can now efficiently complete position and height data collection in access-limited situations, saving time, money and effort. The Bad Elf app workflow runs on Android and iOS.
Geo-genie is a cloud-based collaborative and professional mapping and surveying platform enabling customization and creation of geocentric information systems. Teamed with Handheld’s Algiz RT8 rugged field tablet, it streamlines work and allows non-professionals to perform accurate geodetic mapping, guiding and monitoring of their data collection. The platform enables organizations to have an advanced, professional surveying and GIS platform with customized procedural workflows, management of user hierarchies, and integration with other organizational information systems. Geo-genie can connect with professional surveying equipment, such as GPS and total stations, and integrates data into a cloud-based central database with no restriction for specific data-collection hardware.
The wireless GNSS amplifier LogBuch+ increases the accuracy of location data with the cloud-based LogBuch application. The app enables voice-based digital mapping via a smartphone app, such as for the maintenance of trees. The compact device receives satellite signals on several radio frequencies, delivering significantly more precise data than a smartphone alone. Foresters can carry the GNSS amplifier in a pocket and digitally mark trees for felling using the LogBuch app.
The YellowScan Explorer lidar can be mounted on a light manned aircraft or helicopter, as well as a UAV platform such as the DJI M300. This versatility allows the end user to tackle a wide range of projects with the same unit. It uses an Applanix APX-20UAV GNSS/inertial solution and has a precision of 2.6 cm and an accuracy of 2.2 cm. Its high-power laser scanner can catch points up to 600 meters away. Flight operation speed is 5–35 m/s; it is capable of above-ground-level altitude up to 300 m. The low-weight unit (2.3 kg without battery) can be combined with YellowScan’s suite of software to extract and process point cloud data for surveying, forestry, environmental research, archaeology, industrial inspection, civil engineering and mining sectors.
The DJI Mavic 3 improves on its predecessor with better sensors, a dual-camera system, omnidirectional obstacle sensing, smarter flight modes and longer flight times. A powerful positioning algorithm improves hovering precision with signals from GPS, GLONASS and BeiDou satellites, enabling the drone to lock onto multiple satellite signals faster. The increased positioning precision also makes the drone less likely to drift in the air and more stable when shooting long exposures and time lapses. The Advanced Pilot Assistance System (APAS) 5.0 combines inputs from six fish-eye vision sensors and two wide-angle sensors to sense obstacles in all directions and plan safe flight routes.
Conduct missions, manage fleets and view video feeds
Photo: SkyGrid
SkyGrid’s autonomous remote UAV operations solution enables drone operators to remotely conduct missions, control flights, manage fleets and view live video feeds. Using artificial intelligence and airspace-related data feeds, SkyGrid enables safe remote operations, whether conducting routine inspections or generating optimal flight paths. Advanced route generation capabilities create the safest route for each drone based on the flight plan, environmental conditions, the vehicle’s performance, and the mission criteria with minimum on-site support required. SkyGrid Launch allows video feeds from drones to be consolidated to a remote central location, such as a ground station.
The Sicura EG-1100 is a heavy-lift, long endurance, single-rotor helicopter. Now in its third generation, the helicopter can haul 15 pounds. It cruises at 55 knots. The EG-1100 is available in both electric and gas engine configurations, with an endurance at 3.5 hours on gasoline and 1 hour on electric power. The new gas engine is the high-performing and efficient Skypower 110, tuned to the craft’s internally developed chassis and rotor blades. It offers stable performance in challenging environmental conditions, exceptionally stable flight and immediate flight response for image capture and lidar operations. Multiple payload sets can be carried in one flight.
The Spirit dual-rotor coaxial unmanned aerial system (UAS) is a versatile and durable system for mission-critical operations. Combined with a fully modular, plug-and-play payload design, the Spirit’s open architecture allows operators to easily add or upgrade software to unlock new operating capabilities without the need to design or develop a new aircraft. It has an all-weather airframe. With nearly 10 pounds available for batteries and payloads, Spirit sets the new standard for performance in its weight class. Setup is quick and easy, allowing for takeoff from any type of terrain. The highly streamlined all-weather airframe has a top speed of 60 miles per hour and can operate in high winds. Payloads and batteries can be mounted or stacked on the top or bottom point.
Years ago, a trucker driving down the western slope of the Rocky Mountains lost his brakes. As his truck accelerated, he hoped to make it to the next runaway truck ramp before losing control. However, when he reached it, he saw a car parked at its base with a group of teenagers drinking beers. In a split-second decision, he veered to the left instead and went off the cliff. In the coming years, faced with the same moral dilemma, what would a self-driving truck do?
Matteo Luccio
Many similar scenarios have been discussed in the technical literature on self-driving vehicles. Most of them are variations on the “trolley problem” presented to generations of college philosophy students since it was first formulated by philosopher Philippa Foot in 1967 and adapted by Judith Jarvis Thomson in 1985. In the trolley problem, a person can choose to divert a trolley from the main track, saving five people who are working on it but killing a person on the other track who otherwise would not have been involved.
When faced with an inevitable crash, should a self-driving car slam into a wall to save the lives of three children crossing the street or, in effect, target them to save its two occupants? Most people, when polled, choose the former. When shopping for a new car, however, those same people are more likely to buy one that will make their own safety its highest priority.
Human drivers react to emergencies instinctively — motivated by neither forethought nor malice — and in real time. By contrast, the choices made by autonomous vehicles are predetermined by programmers; their control systems can potentially estimate the outcome of various options within milliseconds and take actions that factor in an extensive body of research, debate and legislation. Therefore, our judgment is harsh if those vehicles make what we deem to be the “wrong” choice.
However, there is no universal agreement as to what constitutes the “right” choice, other than the fact that people generally prefer self-driving cars to minimize the number of lost lives and to privilege people over animals and younger people over older ones. General principles such as “to minimize harm” are of little help in complex and dynamic real-life situations.
Self-driving cars, in addition to their many other benefits, will dramatically reduce traffic accidents and fatalities, because they will never be distracted, drowsy, drunk or drugged. Yet accidents will still happen, and their outcomes will be largely determined far in advance.
The mass introduction of self-driving cars onto public roads will require overcoming technical, legal and ethical challenges. As a society, we will have to agree on a uniform set of ethical codes that will guide these vehicles’ decision-making processes in emergencies. This will force us to explicitly quantify the value of human life and property, and encode it in software. These are hard and uncomfortable choices.
Autonomous systems, fusing data from multiple sensors, will guide these vehicles. It is up to us to decide whom they will target and whom they will spare.
STMicroelectronics has introduced an automotive satellite-navigation chip designed to deliver high-quality position data needed by advanced driving systems.
Joining ST’s Teseo V family, the STA8135GA automotive-qualified GNSS receiver integrates a triple-band positioning measurement engine. It also provides standard multi-band position-velocity-time (PVT) and dead reckoning.
The STA8135GA’s triple-band enables the receiver to efficiently acquire and track the largest number of satellites in multiple constellations simultaneously for superior performance in difficult conditions such as in urban canyons and under tree cover.
Triple band has historically been used in professional applications such as surveying, mapping and precision agriculture that demand millimeter accuracy with minimal reliance on correction data, usually available on larger and more expensive modules than ST’s single-chip STA8135GA.
The compact STA8135GA will help driver-assistance systems make accurate decisions about the road ahead. The multi-constellation receiver delivers raw information for the host system to run any precise-positioning algorithm, such as PPP/RTK (precise point positioning/real-time kinematic). The receiver can track satellites in the GPS, GLONASS, BeiDou, Galileo, QZSS and NAVIC/IRNSS constellations.
The STA8135GA also integrates separate low-dropout voltage regulators on chip to supply the analog circuitry, digital core and input/output transceivers, simplifying selection of the external power supply.
The STA8135GA also enhances the performance of in-dash navigation systems, telematics equipment, smart antennas, V2X communication systems, marine navigation systems, drones, and other vehicles.
“The high precision and single-chip integration delivered by the STA8135GA satellite receiver enables the creation of reliable and affordable navigation systems that enable vehicles to be safer and more context aware,” said Luca Celant, general manager, ADAS, ASIC and Audio Division, Automotive and Discrete Group, STMicroelectronics. “Our unique in-house design resources and processes for high-yield manufacturing are among the critical capabilities that have made this industry-first device possible.”
The STA8135GA is housed in a 7 x 11 x 1.2 BGA package. Samples are available now and full qualification AEC-Q100 and Start Of Production are scheduled for the first quarter of 2022.
UMSZ6 module allows high-accuracy vehicle positioning to within 50 cm without correction data
Photo: Alps Alpine
Alps Alpine and Furuno Electric Co. Ltd. have jointly developed the UMSZ6 series GNSS module, providing high-accuracy positioning to within 50 centimeters without having to use position correction data.
On typical 3-meter-wide roads, the module reliably enables vehicle positioning down to the lane level, a requirement of various V2X applications, and makes possible greater sophistication of autonomous driving functions. This is achieved using a multi-frequency GNSS receiver chip based on Furuno’s Extended Carrier Aiding technology.
The module is compact at 17.8 × 18.0 × 3.11 mm while conforming to automotive-grade specifications. Running costs associated with real-time-kinematic (RTK) base stations, correction data receiving, and correction data use are not needed, maximizing cost performance.
Under the joint agreement, Furuno developed and supplied an original multi-frequency GNSS receiver chip — eRideOPUS 9 (model ePV9000B) — and algorithm. Alps Alpine is the first company to use the chip, with the UMSZ6 series.
Alps Alpine plans to carry out evaluations within a real automotive environment to assess performance and interoperability with V2X and other communication modules. Mass production is expected in 2023.
Inertial Labs has acquired Memsense, a developer of inertial measurement units (IMUs) and a long-time business partner. Inertial Labs is a developer and supplier of orientation, inertial navigation and optically enhanced sensor modules.
The Inertial Labs and Memsense workforce will address the rapidly evolving needs of global customers. The combined company of more than 100 employees and 500 customers expects to introduce breakthrough technologies at an accelerated pace across high-value areas such as autonomous vehicles, GPS-denied navigation, industrial machines, and aerospace and defense.
In addition, Inertial Labs and Memsense have a strong balance sheet to support critical business initiatives, deliver with short product lead times, and invest in promising integrations, the company stated in a press release.
“Our strategic acquisition of Memsense brings together two high growth companies with proven performance in solving some of the world’s most difficult stabilization and navigation problems,” said Jamie Marraccini, president and CEO of Inertial Labs. “Our customers will benefit from our combined capabilities and resources.”
“As we move forward, Inertial Labs and Memsense will define the future of MEMS IMUs,” said James Brunch, CEO of Memsense. “Our focus on innovation, our world-class team, and our strength in customer collaboration allow us to deliver the exact specs needed by our customers.”
Inertial Labs cites the following benefits for current and future customers:
increased production capabilities of up to 50,000 units annually to meet the needs of larger aerospace and defense contracts for guidance and navigation applications
low-cost, consumer-grade IMUs, ruggedized industrial-grade models, affordable tactical-grade IMUs, and IMUs with near-FOG level of performance (0.1 deg/h bias instability)
a larger range of devices for unmanned ground vehicles (UGV); unmanned aerial vehicles (UAV); autonomous and automated ground vehicles (AGV).
expanded research and development efforts to accelerate delivery of IMUs for stabilization applications, such as electro-optical systems, pan-and-tilt platforms, and remote weapon stations (RWS)
new IMU models with improved performance will increase capabilities of the company’s GPS-aided inertial navigation systems (INS), wave sensors, motion reference units (MRU) and attitude heading reference systems (AHRS)
development of new high-performance systems including a MEMS-based gyro-compasses (3 MILS azimuth and 1 MIL elevation accuracy).
GNSS correction service receivers and the firmware-upgraded ZED-F9P upgraded to achieve reliable centimeter-level accuracies in seconds
Photo: U-blox
U‑blox is offering a suite of products and feature additions that simplify access to reliable centimeter-level positioning accuracies for the industrial, navigation and robotics markets.
The upgraded ZED-F9P high-precision GNSS receiver module and the corresponding NEO-D9S and NEO-D9C GNSS correction data receivers offer customers flexibility in assembling scalable solutions for their specific use cases, including robotic lawnmowers, unmanned autonomous vehicles (UAV) and semi-automated or fully automated machinery.
The software-upgraded u‑blox ZED-F9P-04B high-precision GNSS receiver is the first to support a secure SPARTN GNSS correction data format. It seamlessly connects to two new GNSS correction service receiver modules that stream correction data from communication satellites:
The u‑blox NEO-D9S will initially cover the European and U.S. markets before rolling out to the other areas of the globe.
The u‑blox NEO-D9C will cover Japan.
The NEO-D9S receives correction data using the SSR SPARTN data format over the satellite L-band channel. It uses cryptography to securely deliver PPP-RTK GNSS correction data, such as that offered by u‑blox’s PointPerfect service.
The NEO-D9C leverages the subscription-free Centimeter-Level Augmentation Service (CLAS) broadcast over mainland Japan provided by the Japanese Quasi-Zenith Satellite System (QZSS) constellation on the L6-band channel.
While u‑blox GNSS receivers are designed to work with most correction services on the market, pairing the ZED-F9P with the NEO-D9C or the NEO-D9S correction data receiver enables customers to save data transmission cost and operational efforts, the company said.
ZED-F9P-04B offers a new feature called protection level, which increases the trust applications can place in its position output. By continuously outputting the upper bound of the maximum likely positioning error, referred to as the protection level, the receiver lets autonomous applications, such as UAVs, make efficient real time path planning, increasing the quality of their operations.
In the case of robotic lawnmowers, the increased accuracy and reliability of the position will, for example, make it possible to do away with boundary wires, which today are buried under the turf to delimit the mowing area. Furthermore, it will allow lawnmowers to systematically cover a plot based on a digital map, as opposed to the random mowing approach commonly used today.
First samples of these products are available today, in professional and automotive grade. The correction data receivers will be available in automotive grade for the automotive markets.
Integrated solution combines and consolidates valuable telematics data for Geotab and GM customers in Canada
Geotab Inc. has announced the availability of the Geotab Integrated Solution for General Motors in Canada. With no additional hardware installation required, the offering provides Canadian customers with a simplified fleet management platform to help businesses make better informed decisions.
With this integration, data from compatible GM vehicles, 2016 or newer, with OnStar embedded factory-first hardware can be securely transferred into Geotab’s web-based fleet management software, integrating all vehicle data into one platform, offering businesses and fleets a seamless user experience.
By enabling fleet managers to access rich proprietary vehicle data, they can generate safety reports, activity reports and measure other key metrics on one platform to help optimize fleet performance.
Users can expand the functionality of the solution further with access to the Geotab Marketplace, a growing portfolio of mobile apps and software and hardware add-ons to enable customers to tailor their fleet management solution to help meet all of their connectivity needs including improved safety, productivity and efficiency.
