fabiochiu/medium-articles huggingface dataset:
Futurride Briefs | 2020 12 20: Your source for quick sustainable mobility news
Tags: Autonomousvehicle, Ambition2039, Driverless

In this edition we cover the Mercedes-EQ EV plan, Motional and Lyft driverless rideshare, Veoneer thermal sensing for Cadillac, Vayyar 4D imaging radar, Mobileye and Luminar collaboration clarifications, Britishvolt’s battery ‘gigaplant,’ and Faraday Future and Philips on user wellness monitoring.

We summarize key news in sustainable mobility to lighten your info load. Check back often, or better yet subscribe at https://bit.ly/2FtvyNL, and share with your colleagues, customers, and friends to support our content development.





Mercedes-Benz announces six new Mercedes-EQ EV launches by 2022

Mercedes-Benz is targeting leadership in electric drives and vehicle software, and recently gave an update on its electrification plans of product portfolio — key elements of the strategic focus called Ambition 2039 on the way to CO2 neutrality. With the company’s ‘Electric First’ strategy, “our vehicle portfolio becomes electric and thus also our global production network with vehicle and battery factories,” said Markus Schäfer, Member of the Board of Management of Daimler AG and Mercedes-Benz AG, responsible for Daimler Group Research and COO Mercedes-Benz Cars. “We intend to lead in the field of e-mobility and focus in particular on battery technology.” It company just announced production plans for six models on its way to eight all-electric Mercedes-EQ models in 2022. It is integrating Mercedes-EQ models into series production in existing plants. In Germany, the Sindelfingen plant will produce the EQS electric luxury sedan (in Factory 56) in the first half of 2021, and the Rastatt (and Beijing) plant will produce the EQA, the first all-electric compact SUV, in 2021. Plants in Kecskemét, Hungary, and Beijing will produce the EQB, the second all-electric compact SUV, in 2021

Click on the link below to read the full post online.
Patent Newz Box- Stay on top of global patent news- Oct 1, 2020
Tags: Patents, Smart Cities, Autonomous Vehicles, Intellectual Property, Healthcare

Apple’s patent application reveals wireless 5G NR Sub-6 GHz architecture for human safety

patentlyapple

Apple’s latest patent application relates to a radio frequency system that implements millimeter-wave to facilitate wireless communication of data between electronic devices and/or with a network. The emitted energy rate is absorbed by a Maximum Permissible Exposure (MPE) limit and by a Specific Absorption Rate (SAR) set.

NASA patented a faster, cheaper route to the moon

businessinsider

Nasa has patented a new orbital route to reach the moon faster. This is suitable for smaller robotic spaceships. This is mainly meant for the mission DARE (Dark Ages Radio Explorer) to reach the far side of the moon.

Sony patent reveals VR controller design

roadtovr

The Sony’s patent outlines a VR motion controller embedded with LED tracking markers and optical tracking from the headset. The controller disclosed in the patent has standard button layout joystick that provides reliable tracking.

Read more global patent news and stories…
Delivered first fully autonomous EV Star to Jacksonville Transportation Authority
By: Neil Martin
Tags: Autonomous Vehicles, Automation, Automotive, Driverless, Driverless Cars

First fully autonomous EV Star to Jacksonville Transportation Authority delivered

GreenPower’s EV Star expected to enter full Level 5 Autonomous Service with JTA in early 2021; GreenPower, Perrone and First Transit have signed an agreement to build second fully autonomous EV Star for demonstration tour in early 2021

Los Angeles-based GreenPower Motor Company, a leading manufacturer and distributor of zero emissions electric powered medium and heavy duty vehicles, has delivered the first fully autonomous EV Star to Jacksonville Transportation Authority (JTA) in collaboration with Perrone Robotics.

The JTA is currently working with local colleges, medical campuses, and other partners to create the nation’s first public transportation network powered by autonomous vehicles. GreenPower’s fully autonomous EV Star, developed in collaboration with Perrone Robotics, is expected to enter service in February 2021 after an initial calibration period.

Brendan Riley, President of GreenPower, said; “We are seeing a dramatic increase in autonomous vehicle demand and this vehicle demonstrates the compelling marriage of advanced technologies with the customer’s own unique requirements. An autonomous vehicle like our EV Star really opens the door for other automated applications, such as delivery services, and we really see a wide-open market. With a fully autonomous EV Star, GreenPower can lead the way in this exciting, disruptive space.”

Ryne Shetterly, VP of Sales and Marketing at GreenPower, added: “The collaboration between Perrone Robotics and GreenPower Motor Company has proved successful and we are excited to deliver the first unit to JTA.

“As a result, we are in the process of building a second unit in partnership with both First Transit and Perrone Robotics for a nationwide sales demo tour scheduled to begin in March 2021. First Transit is one of the leading transit solutions providers to transit properties all across country and this tour will allow GreenPower to leverage their reach and influence within the space.”
Blue White Robotics
By: David Silver
Tags: Israel, Autonomous Vehicles

I always enjoy learning about new autonomous vehicle companies. Recently I heard from an Israeli startup called Blue White Robotics that is working with lots of different types of autonomous vehicles.

BWR offers an end-to-end service that includes robots, software, operations, and even “boots on the ground.” Their website has photos of drones and autonomous shuttles and self-driving cars, alongside business objectives that range from agricultural pollination to medical transportation to HAZMAT.

Their website sizes the company at 60 employees, which implies a fairly large existing operational portfolio.

Like Bestmile, the goal for Blue White Robotics appears to be a multi-modal platform that customers can configure for their specific needs. A little bit like “AWS for autonomy.”

This is a big goal and I am excited to see companies like BWR aiming for it.
Welcome, Goodyear! SafeAI’s autonomous ecosystem is growing
Tags: Heavy Equipment, Innovation, Autonomous Vehicles, Construction, Mining

At SafeAI, we’ve always believed in the power of a collaborative approach. That’s how we’ve introduced an autonomy solution to construction and mining job sites. We’re building an OEM-agnostic autonomous ecosystem — a platform that welcomes the entire portfolio of industry players, from tires to fleet management systems.

Today, we’re excited to announce a new partner joining our ecosystem: Goodyear Tire & Rubber Company. Goodyear has been at the forefront of supporting vehicle innovation for more than one hundred years — from passenger vehicles, to freight trucks, to dump trucks. And in January, we’re banding together to take on a new frontier: tire intelligence for autonomous heavy equipment.

Tire health is a critical, and often-overlooked, element of a successful, efficient project site. When it’s not properly attended to, small problems like underinflation can cause wear and tear and blow up into big problems, derailing project timelines and budgets. That quickly adds up — to projects that take 20% more time than anticipated, and up to 80% over budget, according to McKinsey. Our integration with Goodyear is designed to monitor and protect tire health, eliminate costly downtime and create smarter, safer sites.

Goodyear will outfit a Caterpillar 725, already retrofitted with SafeAI’s autonomous software, with TPMS Heavy Duty rim-mounted sensors at our Obayashi site in Cupertino, CA. The sensors will collect temperature and pressure data to identify and communicate early or potential problems before they worsen and prompt costly repairs and downtime. The integration also enables Goodyear and SafeAI to exchange site data — on pressure, temperature, speed, miles traveled, etc. — to inform future innovation for both companies and arm site operators with full visibility into equipment performance.

For us at SafeAI, this is a major validation of our model by the leader in the tire industry. Tire intelligence for autonomous heavy equipment is nascent, and we’re thrilled to be working with Goodyear to lead the charge and push the boundaries of industry innovation. With our growing ecosystem, we’re equipped to remaster the operations of diverse heavy equipment fleets to create safer, more efficient construction and mining projects.

We’re looking forward to sharing updates from the Cupertino site in the new year and continuing to deploy fleets of SafeAI autonomous vehicles.

To learn more about our technology and what we’re doing, please visit https://safeai.ai/.

For more information about partnering with us, click here.
Autonomous Vehicle Technology Report
By: Michael Chase
Tags: Technology, Autonomous Vehicles, Report, Wevolver, AI

Fascinating read — 2020 Autonomous Vehicle Technology Report from Wevolver — this guide to understanding the state of the art in hardware & software for #selfdrivingvehicles

#innovation#technology#imagination#imagine#ai#artificialintelligence#autonomousvehicles
What Tesla has in common with baby’s brain? And why it’s a good example of health economics?
By: Kasparas Aleknavicius
Tags: Artificial Intelligence, Deep Learning, Autonomous Vehicles, Autonomous Cars, Machine Learning

Comma.ai — holistic approach and decisions of a mature brain.

And there sits comma.ai at the other side of a table. They train their neural networks without parsing the information into small details and tasks. They instead supply neural nets with full photo/video material. Networks then learn from the view of a driver and from the surroundings of a car (6 cameras attached to the car). It means that networks learn about how a particular situation should look like visually and what a car should do in order to change or maintain the view — decisions are made by changing current visual to the desired one.

Main words characterizing the method are “full visual data”. For comparison imagine that neural networks learn that a car should stay right behind the vehicle in front; at the same time they learn how far away from other objects it should be — how far away from the markings, barriers, walls. All of that without knowing the information what a lane, marking, sign or a barrier is. They are not even told what a red traffic light looks like. Neural networks learn all this holistic visual representation of the situation themselves, and the details behind that are left semi-hidden.

It does not mean that comma.ai networks are not considering the details of the situation. This method means that network chooses the details to make a decision almost by themselves. They may be unable to mark a window, roof or a sill, but they would still know how a house looks like. This is exactly how our mature human brain makes decisions — we do not feel the complex calculations in our head when automatically looking into a mirror during a car maneuver. We don’t need to actively think about mom using two legs to walk and dog having a fur to distinguish them. But these calculations of all the small details are constantly spinning in our brain.
What would you do in a “Robotaxi” or autonomous vehicle?
By: James Crawford
Tags: Autonomous Vehicles, Autonomy, Future, Autonomous Cars, Future Transportation

What would you do in a “Robotaxi” or autonomous vehicle?

Was watching this week’s episode of Tesla Time News on the Now You Know YouTube channel and saw they had an interesting poll question.

What would you do in a robotaxi?

The usual answers were the most popular: sleep, take in the scenery and get some work done. However, Zac was expecting more from their audience. Something more innovative.

So, that got me thinking… what new ways could we use autonomous vehicles? Would we be limited to social gatherings during commutes or could we embrace new concepts?

Perhaps, maybe live streaming a game, music session, or whatever else you normally send your kilobytes of video data to Twitch? The only difference being in your car that’s now autonomously traveling around, giving you additional scenery in your stream?

Never hurts to dream. Anywho, here’s the full episode for those interested:
Futurride Briefs | 2020 12 04: Your source for quick sustainable mobility news
Tags: Autonomousvehicle, Autonomous, Batterycooling

In this edition we cover Uber, Rivian, JetBlue, Cabify, and Boom Supersonic signing The Climate Pledge; Nvidia powering Einride’s Pod; Luminar going public; Faraday Future partnering with MIVOLT; Trimble and SiriusXM on vehicle positioning; and Volvo introducing electric truck.

We summarize key news in sustainable mobility to lighten your info load. Check back often, or better yet subscribe at https://bit.ly/2FtvyNL, and share with your colleagues, customers, and friends to support our content development.







Uber, Rivian, JetBlue, Cabify, and Boom Supersonic sign The Climate Pledge



During the Web Summit 2020, Amazon and Global Optimism announced that Boom Supersonic, Cabify, JetBlue, Rivian, and Uber have joined The Climate Pledge, a commitment to be net-zero carbon by 2040 — a decade ahead of the Paris Agreement’s goal of 2050. “By signing The Climate Pledge, companies around the world are making a bold commitment to help protect our planet from the devastating impacts of climate change,” said Jeff Bezos, Amazon Founder and CEO. He added that the transportation sector plays a critical role in accelerating our carbon reduction goals. New signatories are implementing real, science-based, high-impact changes to their businesses, including deploying renewable energy, investing in sustainable buildings, and mobilizing supply chains to reach net-zero carbon by 2040. So far, 18 companies who have signed The Climate Pledge, cofounded in 2019 by Amazon and Global Optimism as a commitment to reach the Paris Agreement 10 years early. The other organizations are Amazon, Best Buy, Henkel, Infosys, McKinstry, Mercedes-Benz, Oak View Group, Real Betis, Reckitt Benckiser, Schneider Electric, Siemens, Signify, and Verizon. For more information, visit www.theclimat

Click on the link below to read the full post online.
Futurride Briefs | 2020 12 03: Your source for quick sustainable mobility news
Tags: Brake To Steer, Autosense, Autonomousvehicles

In this edition we cover Audi’s increased budget for electromobility, Hispano Suiza’s sportier Carmen Boulogne, Sono Motors’ partnership with Team Rosberg Engineering, DTS’ occupant monitoring solution, the Integrity Security Services and Unex V2X collaboration, CNXMotion’s brake-to-steer technology, and IDTechEx’s study on 3D LiDAR.

We summarize key news in sustainable mobility to lighten your info load. Check back often, or better yet subscribe at https://bit.ly/2FtvyNL, and share with your colleagues, customers, and friends to support our content development.







Audi increases budget for ‘electromobility,’ other sustainable mobility



Audi AG says it is pushing ahead in its transformation to a provider of networked and sustainable premium mobility, with about half of its total budget for 2021 to 2025 of about €35 billion, or some €17 billion, allocated to those areas. “Technological leadership in electric-powered and fully networked driving is the aim of the supervisory board and management board,” said Herbert Diess, Chairman of the Supervisory Board of Audi AG. Those sums take into account VW Group synergies. For example, development and implementation of electric platforms takes place across group brands. Audi and Porsche are developing the premium platform electric (PPE), and Audi uses group technology of the MEB modular electrification platform. For the implementation of Roadmap E, a €15 billion total will be split €10 billion for electromobility (full electric) and €5 billion to hybridization. By 2025, Audi will expand its e-portfolio to about 30 models, of which about 20 will be powered entirely by electric batteries. For “digitalization” and software, Audi also benefits from group cooperation. Software development by the group’s Car.Software organization now led by Audi CEO Markus Duesmann comb

Click on the link below to read the full post online.
It is time to start treating road deaths like a global pandemic
By: Barry Lunn
Tags: Artificial Intelligence, Road Safety, Automotive Adas Industry, Autonomous Vehicles, Automotive

Provizio Accident Prevention Technology™ platform road test

At the time of writing most of the world is in lockdown. Our more vulnerable citizens are cocooning in their homes and our communities and politics are divided. It’s a global pandemic, caused by an uncompromising killer.

According to the World Health Organization (WHO), there have been 1.2 million Covid-19 deaths worldwide, 44 million cases and the cost to the global economy is estimated to hit $1 trillion.

The world has rallied. United in the belief that this level of carnage is not acceptable we are taking draconian measures to stop the spread and investing billions in the science that will ultimately save millions of lives.

The automotive pandemic

According to the WHO, each year there are over 1.35 million road deaths worldwide, over 50 million people maimed and the cost to the global economy is estimated to be over $2 trillion (Link to the study here: WHO)

The numbers quoted above have not changed for more than 20 years. Unless action is taken, they will continue their current trajectory. Preventable human error is responsible for more than 90% of road accidents.

International regulatory policy for the last 20 years has focused on trying to make us better, more responsible drivers. This approach has failed consistently.

The focus by automakers on driver comfort and reactive safety measures has also, predictably failed.

Autonomous driving will ultimately solve the problem but has failed to move beyond level 2 autonomy despite $80 billion invested and will continue to do so while the roads are shared.

The vaccine

We started Provizio to solve the global road death pandemic. We believe that with the right focus, robotics and drivers can work together to reduce both road deaths and accidents to zero. 1.35 million to zero drives everything we do.

We are building augmented, guardian angel technology that will make us all better and safer drivers. We are using unparalleled ‘beyond line-of-sight’ sensor technology coupled with artificial intelligence ‘on-the-edge’ to perceive, predict and prevent accidents.

We are partnering with the top automotive OEMs and Tier 1’s to bring this capability to the masses.

Join our mission to wipe out the global road death pandemic.
Asked Me Anything
By: David Silver
Tags: Autonomous Vehicles, Self Driving Cars

Today I had the privilege of taking over Udacity’s Twitter account to host a 60-minute AMA on robotics and artificial intelligence. Some blasts from my Udacity past even made an appearance :-)

It was fun :-)
Introducing atlatec HD Maps for Cognata
By: Atlatec Gmbh
Tags: Autonomous Vehicles, Simulation Software, Autonomous Driving, Self Driving Cars, Hd Maps

There are a lot of differences of opinion in the autonomous vehicle space, but one thing everyone can agree on:

Virtual training and validation of AV/ADAS systems and components are a key factor in achieving the massive scale of testing which is necessary.

To this end, we at atlatec are always working to support more simulation tools, allowing our customers to continue working with their toolchain of choice when leveraging our HD maps.

Today, we are happy to announce the newest addition to our list of supported simulation software: Cognata.

Cognata is a cloud-based simulation platform designed specifically for autonomous driving and ADAS applications and is used for AV training, validation and analysis. It offers several datasets to test AV components against, such as traffic lights, signs, pedestrians and vehicles.

By importing atlatec HD maps, Cognata customers will have the added benefit of training and testing on road environments that are highly accurate digital twins of real-world routes, ensuring a more robust system performance and similar results to a real drive-test. The maps are supplied in the OPENdrive format.

If you are a Cognata user and interested in learning more about how to leverage our HD maps, please reach out via email or schedule a call with us.
ADAS Lidar
By: David Silver
Tags: Laser, Autonomous Vehicles, Self Driving Cars

New cars with camera systems attached to the windshield have become commonplace. Just about every automotive brand now has a front-camera-enabled ADAS system, optional or even standard on their vehicles.

New cars with lidar systems are virtually non-existent.

There are several reasons for this, starting with cost: cameras are cheaper than lasers, all the more so because they are widely mass-produced for applications beyond automotive. Camera data is also easier for engineers to work with than lidar data, and it’s probably more helpful than lidar data.

That said, lidar data is still very helpful, particularly as a complement to camera data.

Velodyne’s H800 lidar unit, which will go into production in 2021, is designed for ADAS, and looks that way. The form factor itself appears designed to plug into a windshield.

At $500, the price point is still high. I assume that $500 becomes more like $5000 by the time the price of the whole lidar-equipped system gets sold to a car buyer. But even a $500 unit / $5000 system is in the realm of feasibility for consumers, whereas a bottom-of-the-line VLP-16 that retailed for $4,000 probably wasn’t realistic.

In an ADAS system, these sensors should facilitate features like automatic lane-switching, route adjustments, and even fleet mapping, which could lead to ever-greater autonomy.

Lasers, coming to a car near you in 2021.
Is Anybody Big Enough to Acquire Uber ATG?
By: David Silver
Tags: Autonomous Vehicles, Uber, Self Driving Cars

Kirsten Korosec has a blockbuster story in TechCrunch about Uber’s efforts to spin off its Advanced Technology Group (ATG). This marks the latest twist in the too-crazy-even-for-Hollywood saga of Uber’s self-driving unit.

Korosec reports that Uber is in discussions to sell ATG to Aurora, although Korosec notes that:

“Even with the expected depletion in Uber ATG’s valuation, it would be seemingly out-of-range for Aurora unless it was able to secure additional outside investment or structure the deal in a way that would allow Uber to keep some equity.”

Uber ATG has twice as many employees as Aurora, further raising the question of who would be acquiring whom.

ATG has been through all sorts of drama — starting with controversy related to hiring away a large portion of Carnegie Mellon University’s robotics team, to subsequently acquiring Otto, a startup headed by former leaders of what is now Waymo (and was then called the Google Self-Driving Car Project). Google sued Uber and Otto founder Anthony Levandowski, in particular, settling just as the case went to trial. That particular controversy was a factor in the ouster of Uber founder and CEO Travis Kalanick.

The biggest ATG crisis was the fatal collision with pedestrian Elaine Herzberg in Phoenix, Arizona, in early 2018. That collision prompted ATG to halt all on-road autonomous vehicle testing for months, and cast a shadow over the whole industry.

I have always been impressed by the caliber of the ATG team, particularly the individuals who worked with Udacity to build our Self-Driving Car Engineer Nanodegree Program.

As Korosec’s article points out, Uber is trying to divest non-core groups across the board, including its JUMP bicycle division and several international affiliates. ATG is part of that effort. But, at 1200 employees, ATG may be the single largest self-driving car organization in the world right now — perhaps only Cruise and Waymo are of comparable size. Which raises all sorts of questions about who might be able to or interested in absorbing all that talent.
Big Day for ADAS
By: David Silver
Tags: Autonomous Vehicles, Self Driving Cars

Two big ADAS announcements today!

Honda announced they will mass produce the world’s first SAE Level 3-capable vehicle.

Rivian posted specs and features for their upcoming electric light trucks, including the news that Driver+ will come standard on every vehicle.

Some caveats are in order.

Honda’s announcement seems to hinge closely on a recent approval from the Japanese government. Whether this level 3 system will be available outside Japan is unclear.

Audi launched an A8 model several years ago that was L3-capable. But they never enabled Level 3 autonomy, due to regulatory concerns.

Rivian’s Driver+, meanwhile, garnered comparison to GM SuperCruise, which is among the best such systems in the industry.

“With the system engaged, your Rivian will automatically steer, adjust speed, and change lanes on your command. Enabled on select highways at launch, more road types will be introduced through over-the-air updates. Like all driver assistance systems available today, Driver+ requires your full attention on the road at all times and you should not use a hand-held device behind the wheel.”

That’s a big claim! I’m excited to see some reviews of the system.
Big Money for Autonomous Vehicles, Again
By: David Silver
Tags: Autonomous Vehicles, Self Driving Cars

After a year or more spent in the “trough of disillusionment”, autonomous vehicles seem to be riding high again. Within a few weeks, Nuro has raised $500 million and Pony.ai has raised $400 million. Luminar also continues its path towards a SPAC merger that would raise $400 million at a $3.4 billion valuation.

My old business school teacher, Mark Leslie, used to preach that for startups, “cash is oxygen, and oxygen is life.” It’s good to see that there is still lots of life in autonomous vehicles.
By 2025 one can expect to see many millions of electric AVs on our roads.
By: Eric Jensen
Tags: Technology, Autonomous Vehicles, Transportation, Self Driving Cars

By 2025 one can expect to see many millions of electric AVs on our roads. By then too, electric aerial autonomous taxis could be available for longer journeys because they would usually be more practical for this than AVs.
Ep. 1 — Connected Everything. Prepping for a Digital Tomorrow with…
By: Wharton Tech Toks
Tags: Product Management, Technology, Autonomous Vehicles, Podcast, Strategy

Prepping for a Digital Tomorrow with Zafar Razzacki

Episode 1. Connected Everything: Prepping for a Digital Tomorrow

See bottom of the post for links to your preferred podcast player

Podcast Episode 1 Description

Everything is becoming a connected device — my car, my speakers, my TV, my coffee machine, my toothbrush — what’s next? My toilet paper? Join us as we talk about human-centered design and connected devices, particularly Autonomous Vehicles, with Zafar Razzacki. Zafar is an expert on the design, development and launch of connected and innovative products.

In this conversation, we cover a variety of topics on the future of connected devices. We discuss the future of autonomous vehicles and where we are in the roadmap today. We dive into some critical questions of safety and accountability in the self driving world. We explore the tough meta questions about the impact of connected everything will have on us as humans. How close are we to the Jetsons? Will we use the time we get back from self-driving to have more conversations or mind numbingly absorb more Charlie D’Amelio videos on Tik Tok? Tune in and check it out!

Today’s Guest: Zafar Razzacki

Zafar has led the design, development, and launch of a variety of innovative products and services including: autonomous vehicles and mobility services; software platforms and digital experiences; and medical devices. His experience spans over 15 years of product, marketing, and strategy roles at companies including Google, General Motors, Accenture, and multiple technology start-ups. He describes himself as a hybrid strategist, designer, and product manager who is obsessive about delivering great experiences through human-centered design and modern product development practices.

Interesting Relevant Frameworks:

Other podcast players:

Google Podcast, Pocket Casts, Anchor, Spotify, Breaker, RadioPublic,

Check out Wharton Tech Toks socials:

IG: whartontech

LinkedIn: https://www.linkedin.com/company/wharton-tech-club/
Pony.ai strikes autonomous deal with FAW
Tags: Autonomousvehicle, 5ycapital

The Chinese automaker is just the latest partner for the supplier to explore autonomous vehicle technology, specifically involving SAE Level 4 systems for “pre-installation mass production and business operations models.”

Chinese automaker FAW has announced a strategic investment in Pony.ai, marking the second time this year that the autonomous technology company has received funding from a leading car manufacturer. In February, Pony.ai announced that it received a strategic investment from Toyota Motor Corp.



According to an FAW statement, the two companies will give full play to their respective technical and product advantages in vehicle design and manufacturing, V2X, and mobility-as-a-service. They will work to integrate their advanced autonomous driving systems and vehicle platforms to explore SAE Level 4 systems for “pre-installation mass production and business operations models.” The agreement involves a Red Flag EV passenger vehicle platform and a Jiefang Truck commercial-vehicle platform, according to Pony.ai.



Pony.ai was founded in Silicon Valley in December 2016 and is now co-headquartered in Silicon Valley and Guangzhou, China. It has daily testing and operations in Fremont and Irvine, CA, and Beijing and Guangzhou, China, exceeding 1.5 million autonomous kilometers in 2019.



Under CEO and Cofounder Dr. James Peng’s leadership, the company has quickly become an industry leader and launched multiple autonomous driving fleets to the public across the globe. Prior to cofounding Pony.ai, he worked at Baidu and Google for 11 years. The company’s CTO and Cofounder, Dr.

Click on the link below to read the full post online.
Last mile delivery
By: Jj Delgado
Tags: Last Mile Delivery, Autonomous Vehicles, Robots, Innovation

Last mile delivery will be disrupted by 2025. Delivery costs will tend to zero.

This autonomous parcel delivery robot avoid obstacles like pedestrians and trees. This first successful prototype was tested in Australia by Australian Post office for after hours deliveries in a range of 200Km delivering more than a hundred parcels.

#robot #digitaltranformation #digitalbusiness #innovation

More curated content #jjdelgado

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A New Brain-inspired Intelligent System Drives a Car Using Only 19 Control Neurons!
By: Louis, What S Ai
Tags: Artificial Intelligence, Deep Learning, Autonomous Vehicles, Self Driving Cars, Machine Learning

IST Austria And MIT’s New Intelligent System — NCPs

Let’s now enter a little deeper into how this new system works.

It consists of two parts. At first, there’s a compact convolutional neural network, which is used to extract structural features from the pixels of the input images. Using such information, the network decides which part of the image is important or interesting and passes only this part of the images to the second system.

End-to-end representation of the architecture — Image from the paper

Which they called a “control system” that steers the vehicle using decisions made by a set of biologically-inspired neurons. This control part is also called neural circuit policy, or NCP. Basically, it translates the data from the compact convolutional model outputs to only 19 neurons in an RNN structure inspired by the nematode’s nervous system controlling the vehicle and allowing it to stay into the lanes. Following the architecture shown above. You can find more details about the implementations of these NCPs networks in their paper or clear guide they made on their GitHub [2].

This is where the biggest reduction in parameters happens. Mathias Lechner explains that “NCPs are up to 3 orders of magnitude smaller than what would have been possible with previous state-of-the-art models” as you can see in table 2 shown below. Both of these systems are trained simultaneously and work together to create this self-driving car.

Network size comparison — Image from the paper

Being so small, they were able to see where the system was focusing its attention on the images fed. They discovered that having such a small network extracting the most important part of the picture made the few decision neurons focus exclusively on the curbside and the horizon. Which is a unique behavior among artificial intelligence systems that are currently analyzing every single detail of an image, using way too much information than needed.

Global network dynamics — Image from the paper

Just take a second to look at how little information is sent into the NCP network compared to other types of networks. Just by looking at this image, we can see that it is clearly more efficient and faster to compute than current approaches.

Plus, while noise is a big problem for current approaches, such as rain or snow in lane-keeping applications, their NCP system demonstrated strong resistance to input artifacts because of its architecture and novel neural model keeping their attention on the road horizon even if the input camera is noisy, as you can see in the short video below.
SafeAI Teams Up with Obayashi for Autonomous Construction Pilot
Tags: Artificial Intelligence, Autonomous Vehicles, Mining, Construction

This fall, we’re excited to announce the upcoming launch of an autonomous construction site and our growing partnership with Obayashi Corporation. In collaboration with Obayashi, we will kick off this November with a pilot program in which a Caterpillar 725 articulated dump truck will autonomously complete a vital on-site function: load-haul-dump cycles.

Obayashi is the Japanese-based global leader of connected construction solutions. By teaming up with one of the largest names in construction, we’re demonstrating industrial autonomy in a real-world situation and setting a standard for future autonomous heavy equipment. This pilot follows Obayashi’s investment in SafeAI in November 2019.

Construction represents one of the largest sectors in the global economy. According to the Association of General Contractors, construction creates nearly $1.3 trillion worth of structures each year in America. But the industry also faces a slew of urgent safety concerns (one in five worker deaths last year were in construction), increasing labor shortages, missed deadlines, and rising costs — and COVID-19 has only accelerated these bottlenecks.

Autonomous heavy equipment delivers a safer, more productive solution for the construction industry. By retrofitting existing fleets of industrial equipment with its autonomy platform, the SafeAI team is propelling the industry forward as efficiently and seamlessly as possible. In doing so, we’re also paving the way for the future of autonomous technology outside of on-road vehicles.

“We are investing in autonomous solutions that we believe will play a critical role in our success both in the near term and also down the road. SafeAI has built a powerful autonomous ecosystem that ushers in safer, more productive worksites,” said Hiroto Sato, COO of Obayashi SVVL (Silicon Valley Ventures & Laboratory). “Throughout our partnership, we look forward to building operational and organizational structure to support this pilot and more deployments like it in the future.”

The importance of this pilot is two-fold. There’s a critical need for autonomy outside of on-road vehicles, and this demonstration is a turning point for real-world application of autonomous technology. Beyond that, this also indicates the beginning of a larger shift in the construction industry — one that involves an increasing interest in connected technologies and commitment to more innovative solutions.

We’re here to deliver. To learn more about our technology and what we’re doing, please visit https://safeai.ai/. For more information about partnering with us, click here.
In times of disaster, AVs lend a helping hand
Tags: Avs, Autonomousvehicles

In times of disaster, AVs lend a helping hand Futurride ·Oct 20, 2020

Eric Tanenblatt of global law firm Dentons writes that experiments during the coronavirus pandemic have demonstrated the significant public safety applications for autonomous transportation.

First responders, healthcare providers, national guardsmen⁠ — they are all workers who have been considered essential since the earliest days of their trade, the people we depend on in the aftermath of natural disasters, crises, and, most recently, pandemics.



But COVID-19 has birthed a new class of essential emergency workers, like the crew stocking supermarket shelves and delivering to-go dinners, social workers, bank tellers, and truck drivers. This lot signed up for a paycheck, not a pandemic, but working through this crisis to help ensure continuity of critical services like food supply has exposed these workers to profound risk.



On an ordinary day, these essential workers come into contact with hundreds of people every day, each one a possible disease vector.



This new normal presents an opportunity for a fresh vision of autonomous vehicles focused on public health and safety. There are countless examples of small-scale deployments of autonomous vehicles that assist or could assist essential workers in avoiding human contact. Three specific examples are worth highlighting.







Driverless delivery



Nuro, an autonomous vehicle company specializing in completely driverless delivery vehicles, received only the second fully autonomous test-drive permit from California in early April.

Click on the link below to read the full post online.
Transportation Technology Q3 Summary Card
By: Venture Scanner
Tags: Autonomous Vehicles, Autonomous Cars, Self Driving Cars, Transportation, Connected Cars

Below you will find our transportation technology q3 summary card, which summarizes transportation technology startup funding, maturity, and exit trends for the last quarter.

Download PDF

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Feature Report: Robotaxi business in China
By: Tech In China
Tags: Waymo, Robotaxi, Autonomous Vehicles, Autonomous Cars, Didi

Recently, the global leading players in the Robotaxi industry have become clear.

Chinese companies in the industry are led by Baidu Apollo, Pony AI, AutoX, WeRide, and Didi, and the lead international players are Waymo and Zoox, Cruise, and Aurora, etc.

In the Robotaxi field, there are a lot more moving parts that need to be done. Currently, most of the companies are still software developing firms and provide only autonomous driving software services.

The final realization of autonomous driving still needs to adapt the software to specific hardware models. Aside from policy and technical thresholds, the cost is a key factor in the development of the Robotaxi industry: a Robotaxi may cost as low as $0.18 per mile, which is significantly lower compared to the average cost of Uber’s traditional carpool service ($1–2 per mile).

According to McKinsey’s forecast, China may be the world’s largest autonomous driving market.

By 2030, the total sales of autonomous vehicles will reach $230 billion, and the total value of the travel orders based on autonomous driving will reach $260 billion.

iResearch predicts that by 2022, the global penetration rate of autonomous driving at L1 to L5 levels will reach over 50%, and the global penetration rate of autonomous driving will increase to 70% by 2030.
Lyft Level 5’s Machine Learning Pipeline
By: David Silver
Tags: Autonomous Vehicles, Pytorch, Machine Learning, Self Driving Cars, Lyft

Lyft Level 5 recently published an amazing overview of their PyTorch-based machine learning pipeline.

They confess that a few years ago, their development process was slow:

“Our first production models were taking days to train due to increases in data and model sizes.…Our initial deployment process was complex and model developers had to jump through many hoops to turn a trained model into a “AV-ready” deployable model….We saw from low GPU and CPU utilization that our initial training framework wasn’t able to completely utilize the hardware.”

The post proceeds to described the new pipeline Lyft built to overcome these obstacles. They started with a proof-of-concept for lidar point cloud segmentation, and then grew that into a production system.

The pipeline accomplishes a lot of infrastructure wins.

Testing. The pipeline incorporates continuous integration testing, both to ensure that the models don’t regress, and also to verify that the code researchers write will run in the PyTorch-based vehicle environment.

Containerization. Lyft invested in a uniform container environment, to mitigate the distinction between local and cloud model training.

Deployment. The system relies heavily on LibTorch and TorchScript for deployment to the vehicle’s C++ runtime. Depending on existing libraries reduces the amount of custom code Lyft’s team needs to write.

Distributed Training. PyTorch provides a fair bit of built-in support for distributed training across GPU clusters.

There’s a lot more in the post. It’s a pretty rare glimpse of a machine learning team’s internal infrastructure, so check it out!
Cruise to Test Fully Driverless Vehicles in San Francisco
By: David Silver
Tags: Autonomous Vehicles, Self Driving Cars

Cruise CEO Dan Amman announced yesterday that his company will test fully driverless vehicles on the streets of San Francisco “before the end of this year.”

The post heavily emphasizes the environmentally friendly nature of Cruise’s all-electric fleet, including its Origin prototype vehicle.

“Single occupant, human-driven, gasoline-powered cars are the second largest contributors of greenhouse gases on Earth…burning fossil fuels is no way to build the future of transportation.”

A video by Cruise founder and CTO Kyle Vogt accompanies that announcement. Vogt mentions that Cruise has accumulated “over a million miles of fully autonomous driving, in complex urban environments.”

That seems much lower than I would’ve guessed, so much so that I wonder if it was a mis-statement. Given Waymo’s record of over 20 million autonomous miles, I would assume Cruise would want something closer to that before putting fully autonomous vehicles on the road.

Combined with Waymo’s recent move to open driverless vehicles in Phoenix to the public, it’s been a great week for self-driving cars.
The Autonomous Vehicle Has Arrived
By: Frank Diana
Tags: Autonomous Vehicles, Autonomous Cars, Self Driving Cars

That is a quote from a recent Article on Waymo’s announcement of a Completely Driverless Service for the general public in Chandler, Tempe and Mesa Arizona. The quote addresses all the skepticism that has surrounded the move towards autonomous vehicles. Author Enrique Dans describes the emerging service and has a message for the naysayers:

Skeptics of the world, this is the moment to admit defeat: those who said it couldn’t be done have been proved wrong; those who said autonomous vehicles couldn’t adapt to real road conditions, that these vehicles would end up waiting at junctions for hours, that legislation would be held up, that nobody would dare use it

As we stare into this emerging future, we must accept that a transition period requires our attention. These future scenarios provide society with an opportunity for growth and prosperity as we transition to a future state. However, once we arrive, the challenges that come with scenarios like autonomous vehicles (e.g., loss of jobs) are realized. That means we have a chance to manage the transition. For example, while this new Waymo driverless service does not require a driver (sorry Uber), these taxis are still monitored, and that requires workers with new skills. As described in the article, the process will have to be refined to allow a single operator to monitor several vehicles. More importantly, this scenario captures what is likely to happen across most future scenarios: the human monitors will be eliminated or replaced by algorithms — having been trained by the human monitor.

Understanding this possible future affords us the opportunity to manage the path. In so doing, we avoid the fear of building a future where our most intractable problems are solved. This belief in our potential is described very clearly in Rethinking Humanity. It is therefore incumbent on us to see the future, understand its possible implications, let go of our current mental models, and manage the path.
#43 of #100Scenarios — Autonomous Vehicles
By: Scalable Analysis
Tags: Scenarios, Regulations, Autonomous Vehicles, 100scenarios, Carmakers

It’s so strange, how a technology that seemed inevitable can stall, and now it has. I guess this is an example of how technology adoption is not always linear despite the hype. This was a technology that was demonstrated in 2005, and in urban contexts in 2007. It’s been 13 years now, and of course, COVID-19 must have have affected some of the plans. OR one could argue that autonomous vehicles are already here — many carmakers have varying levels of autonomy in the software — it’s just that we don’t trust it enough to drive the car completely. Is it still just a matter of time, or will we never get to autonomous driving?
MG Motors Has Designed the ADAS Capability of The Gloster For India’s Traffic
By: Surbhi Rathore
Tags: Adas, Traffic Solution, Automobile, Mg Motor India, Autonomous Vehicle

MG Motors Has Designed the ADAS Capability of The Gloster For India’s Traffic Surbhi Rathore ·Oct 16, 2020

Compact Story:

One of the prime features of the MG Gloster is the ADAS or advanced driver assistance system alongside level 1 autonomous driving. The problem with ADAS in India is the traffic as it can get triggered in an almost irritating way in the country’s famed bumper to bumper traffic situations. Rajeev Chaba, MG Motor India’s President and Managing Director told that the Gloster’s ADAS system has been ‘tweaked’ for India.

“So you know, so that’s why a little bit, you need to tweak it depending on our Indian driving dynamics,” said Chaba who used to be a VP at GM in China before joining MG Motors to lead the India business in 2017

Reference :

https://www.carandbike.com/news/exclusive-mg-motors-has-designed-the-adas-capability-of-the-gloster-for-indias-traffic-2300543