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Home 2022 August 2

Daily Archives: 08/02/2022

DeepRoute.ai completes test of its autonomous driving solution

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News Desk
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DeepRoute.ai completes test of its autonomous driving solution
A driverless vehicle equipped with DeepRoute-Driver 2.0 production-ready solution. The appearance of the vehicle is very close to existing cars.

DeepRoute.ai, an international autonomous driving technology company, has announced the results of the latest fully-driverless test of its Driver 2.0 L4 production-ready autonomous driving solution. DeepRoute.ai released a video exhibiting a driverless vehicle retrofitted with a production-ready L4 solution on Central Business District roads in Shenzhen, demonstrating its advanced capacity in complex and challenging traffic environments. This marks the first legalized driverless test in China as Shenzhen unveiled China’s first regulation on intelligent connected vehicles on July 6, 2022.

The fully driverless vehicle drove just under 14 miles in one hour, navigating through significant traffic and narrow lanes safely and efficiently. The vehicle intelligently maneuvered around double-parked cars, counterflow e-scooters and pedestrians, negotiated with oncoming vehicles to calculate the right timing and trajectory to pass busy intersections, conducted multiple lane changes and unprotected left turns.

driverless
The driverless vehicle navigates on a crowded narrow street.

“The recent legislation permitting driverless Robotaxis in Shenzhen is the first of its kind, a major milestone in advancing autonomous driving technology to wider and faster adoption,” said Maxwell Zhou, CEO of DeepRoute.ai. “As we advance our mission for commercial deployment of autonomous driving vehicles, we will collaborate with automakers to refine our L4 solution to make it as safe and efficient as possible.”

DeepRoute.ai has made significant improvements to achieve driverless capability, with both software and hardware meeting auto-grade standards. The safety mechanism was also upgraded to guarantee driverless safety on the road. In the case of long tail scenarios, the system will alert the remote monitoring center to intervene or take other safety measures.

The driverless vehicle is equipped with Driver 2.0, a production-ready L4 solution that includes five solid-state LiDARs, eight cameras and other sensors, and a computing platform integrated with its proprietary inference engine.

The perception algorithm with sensor fusion can achieve precise object detection up to nearly 220 yards. The planning and control algorithm based on game theory can choose optimal routes and make decisions based on real-time situations when negotiating with oncoming vehicles and other road agents.

With its deep learning approach, the inference engine optimizes compute resources, allowing the algorithm to run on its low-cost and power-efficient computing platform effectively and stably. As a result, Driver 2.0 can be priced at $3,000 for automakers in mass production and the algorithm can work with 2 to 5 solid-state LiDARs for automakers customization needs.

driverless
A driverless vehicle equipped with DeepRoute-Driver 2.0 production-ready solution.
The appearance of the vehicle is very close to existing cars.

The latest legal and regulatory framework is aligned with autonomous driving industry developments and is deemed the prelude to mass production and commercialization of autonomous driving vehicles. DeepRoute.ai is now working with automakers to mass produce consumer vehicles integrated with Driver 2.0 that will be available for consumer purchase 2025 and onwards, as well as used for Robotaxi operations.

Royal HaskoningDHV publishes its first Open-Source package

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News Desk
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Royal HaskoningDHV publishes its first Open-Source package

Royal HaskoningDHV launches its first open-source package called SAM for Smart Asset Management and it has been used as an internal Python package for years. 

Time series data and anomaly detection

SAM is a Python toolbox to work with time series data and it is used by data scientists, data engineers and data analysts. It contains numerous functions and classes for data loading, preprocessing, validation, visualization and feature building as well as creating machine learning models for forecasting and anomaly detection. SAM makes creating machine learning models easier by simplifying the creation of rolling features and time features. It also allows the users to easily create models that predict multiple steps ahead or predict quantile values, which can be used for anomaly detection.

Data Science meetup

If you’d like to know more about the details of this package, we will present it in more detail during the next Royal HaskoningDHV Data Science meetup, which is planned for October 21st at our office in Amersfoort.

Royal HaskoningDHV has decided to make this package open-source and available to all, because it allows us to work together more effectively and we want to share our experience with time series analysis with the rest of the open-source community. At the same time, we are also working on our Machine Learning as a Service (MLaaS) platform, that will make it easy to deploy multiple models created with SAM.

Aeva Partners With German Firm SICK AG For New-age LiDAR Sensors

By
Priya Chadha
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Aeva Partners With German Firm SICK AG For New-age LiDAR Sensors

Aeva, a leader in next-generation sensing and perception systems, has forayed into the industrial sector to sell  sensors following its collaboration with SICK AG.

Outmaneuvering its competitors, Aeva has announced a multi-year collaboration to bring its FMCW (Frequency Modulated Continuous Wave) 4D LiDAR™ to a variety of industrial sensing applications, including long-range sensing, starting with Aeries™ II.

On the tie-up, Dr. Niels Syassen, Member of the Executive Board responsible for Technology and Digitization at SICK, said, “We are pleased to partner with Aeva and will work closely to leverage FMCW technology for high performance sensing in industrial applications.”

What Aeva sensors do?

If an object is projected in a 3-dimesional view, it can be seen from any position. Aeva sensors not only help self-driving cars gain the 3D view but also their surroundings. Low-power laser emitted by these  sensors can determine distance,  direction as well as speed of the objects coming to or moving away from them.

Aeva 4D LiDAR sensors detect velocity in addition to 3D position. Besides, allowing vehicles and robots to make more intelligent and safe decisions.

“We are convinced that their unique approach to FMCW technology, which includes instant velocity detection and long range performance, will provide new opportunities for us and our customers in a variety of industrial sensing applications where traditional time of flight LiDAR technologies are challenged, Syassen said.”

Aeva’s FMCW 4D LiDAR technology is far better than other sensing technologies like cameras and legacy 3D LiDAR sensors. First, it provides better dynamic range performance to identify low and high reflectivity targets, thus facilitating transition of automated machinery from indoor to outdoor operation.

Second, automated machines using Aeva’s 4D LiDAR are expected to perceive when highly reflective objects such as safety vests, cones and tape are in the sensor’s field of view.

Soroush Salehian, Co-founder and CEO at Aeva, said, “This strategic collaboration is a testament to the industry-leading performance and versatility of our unique 4D LiDAR technology for scaled deployment in industrial applications.”

Aeva is transforming autonomy with its groundbreaking sensing and perception technology that integrates all key LiDAR components.

How Autonomous Mobility Is Enabling Business Transformation

By
Siddhartha Bal
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How Autonomous Mobility Is Enabling Business Transformation

Disruption is the underlying theme that unites the current global mobility scene. With the world turning to sustainable innovations, improved modes of transportation and accessibility are transforming industries and society alike. Since its inception, the automobile industry has been a focal point for technological, economic and social innovation.

The McKinsey Center for Future Mobility modelled more than 40 transportation use cases across a global mix of urban and highway settings under a range of technological, economic and other factors to better grasp the magnitude and scope of the AV opportunity.

Business model evolution

The outcomes of an AV-driven future are unquestionably favourable. Data, knowledge and understanding of the roadway layout, traffic patterns, human behavior, situational prediction, driving etiquette and meteorological information are key enablers for AVs.

The emergence of AVs in conjunction with the service-based economy has the potential to transform society and usher in a new era of mobility in which the value of asset ownership will be lower and the development of business models will be driven by convenience and user experience.

According to the Automobile Industry report by the Indian Brand Equity Foundation, India could be a leader in shared mobility by 2030, providing opportunities for electric cars and AVs.

 The ability to entertain passengers will also become a more crucial component of product differentiation as drivers become less involved in vehicle operation. Today, there are numerous examples of audio entertainment incorporated into automotive systems (Tesla and Spotify, Pandora and various OEMs) and AVs can expand this to video entertainment (Netflix, TV), or productivity suites (Microsoft, Apple).

Emerging models

A new era of ‘NextGen mobility’, in which traditional ownership declines, is being ushered in by the growth of autonomy. The development of ride-sharing mobility models like Uber, which evolved from taxi services, is an important example of this shift to mobility as a developing model.

The capacity to maximize vehicle utilization to take advantage of in-the-moment demand is a crucial skill that serves as the basis for mobility potential models. Operators that use AV fleets can change their business models to meet the varying demands of their customers. For rental firms and other fleet operators with huge fleets, purchasing a completely autonomous fleet is expensive. The retrofit strategy is ideal, where new features or technologies are integrated into existing systems to increase functionality and efficiency or to conform to environmental requirements.

Autonomous mobility is enabling business transformation

While several major technology businesses are working to make self-driving technology a reality, many other sectors must adopt autonomous mobility, or they risk experiencing significant disruptions. Some industries that can gain from updating their business strategies are:

Auto parts and repairs: Smart driving software, such as brake assistance, will likely cause less damage to cars, which will need fewer replacements. AVs may not always be less expensive to maintain, though. Costs may merely move to computational power, which is where an AV’s value lies. More technologically-oriented businesses like Nvidia, which works with prominent automakers, will probably pose challenges to traditional component producers. Additionally, traditional repair shops will need to adopt modern technology like real-time diagnostics to give connected-car owners the ability to diagnose engine problems.

Telematics technology: Telecommunications-based communication and data collection from cars may allow driving-based service providers to switch to operating self-driving fleets that follow predetermined routes and carry out defined duties as efficiently as possible. Benefits from these systems are not guaranteed, however. The selection of the right operating model is crucial. These systems have the potential to reduce fleet management costs by up to 40%.

Ride-hailing companies: For their fleets, ride-hailing companies may collaborate with an AV developer, primarily continuing their current role as a middleman between individuals in need of transportation and those with available vehicles.

 Healthcare: There is room for AV and major technology businesses to work together to create more seamless patient care experiences. Partnerships between pharmaceutical and AV technology firms have already been established to revolutionise distribution. CVS Health, for example, is exploring autonomous prescription delivery with Nuro. Such collaboration could be a gamechanger thanks to the greater dependability and efficiency of autonomous delivery.

Surveying and mapping: Safe AVs must have accurate self-positioning data as well as high-definition 3D digital maps to recognize their positions with accuracy. Keeping data updated with frequent changes in cities is a problem for mapping. Traditional maps with GPS-enabled navigation cannot be used in driverless automobiles. AI-enabled HD maps that combine and analyze data from various sources, including sensors, satellites, Lidar, onboard cameras and more are necessary for AV software. Companies may encounter additional challenges in collecting proprietary geospatial data, which is often protected by governments and private organisations. They also need to consider the high cost of HD mapmaking.

 Urban planning: The real estate sector will undoubtedly experience disruption and change because of AV technology. Urban areas are being reimagined using AVs, which calls into question not only the buildings that should be constructed but also the significance of the land on which they stand. City planners and architects need to rethink their strategies if they want to create structures that will last for at least the next 100 years.

 Auto dealerships: More riders might give up traditional automobile ownership models if fleets of AVs are made available, whether by automakers or through ride-hailing services. It’s possible that car ownership will move towards a subscription model in which a rental firm offers a car and all maintenance for a set price so that customers can access special features without having to make a commitment to purchase the vehicle.

These new developments, combined with encouraging government initiatives and laws, are expected to support the automotive industry’s expansion. The development of sustainable manufacturing techniques and the creation of job prospects within the industry can be aided by developing technology.

To give themselves enough time to position themselves positively, it is crucial for businesses to start thinking about the implications of these paradigm shifts right now. The essential insights can be obtained using a flexible model that considers different scenarios.

All Eyes on UNGGIM

By
Anusuya Datta
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All Eyes on UNGGIM

The global geospatial community will have its gaze fixed on the UN headquarters this week as the 12th session of the United Nations Committee of Experts on Global Geospatial Information Management (UN-GGIM) takes place Aug 3 – 5 in New York. The first in-person gathering after two years of virtual meetings is significant in many ways. One of the major points in the agenda include strengthening global geospatial information management arrangements and determining the future geospatial information ecosystem.

At the eleventh session, held virtually last year, the Committee of Experts had adopted a decision that emphasized the importance of the Integrated Geospatial Information Framework (IGIF) in providing an overarching paradigm to further strengthen nationally integrated geospatial information management. This applies to not only Member States that were in the early stages of adopting national spatial data infrastructures but also for those that had already successfully implemented spatial data infrastructure capabilities.

However, the committee acknowledged the necessity of continuous collaboration  with emerging and complementary initiatives, such as the Geospatial Knowledge Infrastructure (GKI) or the European Union Location Framework Blueprint.

In fact, last week, the co-chairs of the Committee of Experts submitted a report titled “Enhancing global geospatial information management”, to the United Nations Economic and Social Council (ECOSOC) for its consideration and adoption.

The call for strengthening international cooperation in global geospatial information management is gaining ground as the geospatial ecosystem is becoming more and more expansive, thanks to rapid technological developments and mainstreaming of geospatial with the increased use and adoption of geospatial information across diverse government, industry and user sectors. In this background, it’s crucial to get a clear understanding of what the future geospatial information ecosystem beyond the IGIF might look like.

At Geospatial World, we believe partnerships are the wellspring of information exchange, as the genesis and evolution of knowledge is only through multi-level collaboration. That’s why we have been working with the United Nations and  national governments in defining and elucidating the role  of GKI in bringing together governments,  industries, and non-profits  to collaborate in an increasingly automated, dynamic, and real-time global environment.

We earnestly believe that Geospatial Knowledge Infrastructure will bolster governmental and private sector efforts in delivering sustainable economic, social, and environmental benefits.

Apart from deliberating on the future geospatial information ecosystem, the other moot points include discussions on various issues such as contribution of regional committees to the global geospatial information agenda; a global geodetic reference frame; building a geospatial information and services for disasters; implementation and adoption of standards for the global geospatial information community; and collaboration with the United Nations Group of Experts on Geographical Names, among others.

As the week progresses, it will be exciting to witness new developments and announcements straight from the UN HQ for setting directions towards nationally integrated geospatial information management and furthering development agendas.

For better understanding of What is GKI, you may download this WHITEPAPER: The Power of Where: A Geospatial Knowledge Infrastructure to Enhance World Economy, Society and Environment 

China prepares for launch of second space station module

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News Desk
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China prepares for launch of second space station module

China is gearing up to send a second module to its under-construction space station with a launch from the coastal Wenchang spaceport later this month.

A Long March 5B heavy-lift rocket will launch the roughly 22-ton Wentian experiment module around 02:20 a.m. ET (0620 UTC) July 24, according to recently announced area clearance notices consistent with such a launch.

The 53.7-meter-long, 837.5 metric ton rocket will be rolled out to the pad at Wenchang in the coming days.

Wentian is expected to rendezvous and join Tianhe, the similarly-sized core module for the Tiangong space station which launched in April 2021. Tianhe made orbital adjustments earlier this month to prepare for the arrival of Wentian.

The new module has a length of 17.9 meters and a maximum diameter of 4.2 meters. It features crew quarters and an airlock cabin which will become the main exit-entry point for extravehicular activities (EVAs) once active, replacing the role now played by the Tianhe docking hub.

The new crew facilities will allow China to perform a first crew handover. This will take place when the current Shenzhou-14 crew greet three new astronauts due to fly aboard Shenzhou-15 in December. Tiangong will then host six astronauts for a period of days.

Its main role is hosting experiment racks for science experiments, while also providing backups to the life support and control functions of Tianhe. Wentian carries a five-meter-long robotic arm, supplemental to the 10-meter-long Tianhe arm. The two arms can also join together.

Wentian will also come with 30-meter-long solar arrays, boosting the power available to Tiangong. Wentian will host a new round of live science lectures, following on from those presented by the Shenzhou-13 crew aboard Tianhe.

“Wentian is a critical stage in the building of China’s space station,” says Brian Harvey, author of China in Space: The Great Leap Forward. “The Tianhe crew has overseen numerous undockings and redockings, so such maneuvers are well practiced, but nothing can be taken for granted, especially for the first time.”

The Shenzhou-14 astronauts aboard Tianhe have been undergoing a training program including rendezvous and docking operations and using Tianhe’s mechanical arm in preparation for the arrival of Wentian.

Tianzhou-2, a cargo craft initially charged to deliver supplies to Tianhe for the first crew, Shenzhou-12, was used early this year for a transposition test to verify procedures for moving a module from the forward docking port and towards a lateral port.

Tianhe has so far been visited by three separate three-person crews. The most recent, Shenzhou-14, arrived on June 5 and will oversee the arrival of Wentian and Mengtian, another 22-ton experiment module scheduled for launch in October.

The arrival of the latter will complete the planned T-shaped Tiangong space station, though China has suggested it could later expand the complex to six modules.

“The real work of the station, which we can expect to fly into the 2040s, will begin,” Harvey says, once Mengtian is docked in position. 

The Chinese space station was first envisioned in 1992 with the approval of Project 921 which called for the development of human spaceflight capabilities. The project suffered delays due to issues with development and performance of the Long March 5B, but could also be expanded to six modules and most commercial and tourist missions.

The country also plans to launch a co-orbiting optical telescope module, named Xuntian, in late 2023. It will be capable of docking with Tianhe for repairs, maintenance, refueling and upgrades, and aims to survey 40 percent of the sky across a decade. 

Xuntian features a two-meter-diameter aperture and a field of view more than 300 times greater than the 32-year-old Hubble Space Telescope. NASA plans a new survey mission, the Nancy Grace Roman Space Telescope, around 2027.

Wentian fallout?

The two previous Long March 5B launches, which carried a test new generation crew spacecraft prototype and the Tianhe module respectively, notably saw the large first stage of the rocket enter orbit and make uncontrolled reentries.

Attention will be on whether or not the launch profile has been altered or deorbiting capabilities, such as restarting engines, have been added. If not, the mission could see another uncontrolled reentry occur. Exceptionally, the Long March 5B includes a core stage and boosters. 

Usually smaller second or further stages do the final work to carry a spacecraft into orbit, with the larger first stage cutting off before reaching orbital velocity and falling within a calculated, safe area.

Chinese foreign ministry spokesperson Wang Wenbin stated last year that it was “common practice across the world for upper stages of rockets to burn up while reentering the atmosphere.” In this case, the large first stage is also the upper stage.

While such an event would involve particularly large and massive spacecraft, the standalone threat of the spent rocket stage causing damage or harm will be very low. Most of the stage will burn up in the atmosphere and is likely to land in the oceans or uninhabited areas.

There is however a larger cumulative risk, according to academics, from uncontrolled reentries stemming from space launch activities. 

Area clearance notices provide drop zones for the boosters and payload fairings for the upcoming Wentian launch, but no indication of a zone for the first stage.

NASA’s Artemis 1 moon rocket gets Aug. 29 launch date

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News Desk
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NASA’s Artemis 1 moon rocket gets Aug. 29 launch date

NASA hopes to get its moon megarocket off the ground as soon as late August.

NASA is working towards three “placeholder” launch dates for Artemis 1, an uncrewed test flight around the moon that serves as a keystone in testing for future human missions: August 29, September 2 and September 5. These dates are pending repairs and tweaks, however, to the Space Launch System rocket and related systems in light of results from a “wet dress rehearsal” June 20 that NASA declared a success, officials said in a teleconference with media held on Wednesday (July 20).

“It’s not an agency commitment,” Jim Free, NASA’s associate administrator of exploration systems, said of the interim launch dates. NASA will announce a more firm commitment about one week before the launch, he said, when the agency completes its standard flight readiness review of the Artemis 1 stack, including SLS and the Orion capsule riding atop the rocket.