Industry Videos

Lexus: Enjoy Driving While We Still Can?

/0 Comments/in , , , ,

The latest commercial from Lexus for its new 2017 Lexus IS luxury sedan has raised some interesting questions among car enthusiasts: Could the thrill of driving be on its way out? Should we take advantage and enjoy it while we still can?

Obviously, that’s the premise of the commercial — that driving the new 2017 Lexus IS is so thrilling, you should savor every moment, while drivers still have the ability or choice to drive. In the last few seconds of the commercial, the car morphs into a self-driving car, and the driver is left to ponder those times when he could enjoy the power of the car’s controls in his hands.

However, one interesting note — the driver’s hair goes from youthful and dark to gray during the morph, suggesting that, while Lexus is all but promising to deliver a self-driving car in the future, it’s not just around the corner — it’s long enough away to age a man considerably.

Image and video by Lexus

Land Rover Video Demos Off-Road V2V Connected SUVs

/0 Comments/in , , ,

A video from Jaguar Land Rover shows the firm’s luxury off-road SUVs conducting vehicle-to-Vehicle (V2V) communications, and automatically taking control of a vehicle when the road surface changes.

The video is posted on The Auto Channel YouTube site. It is two videos from Jaguar Land Rover pasted together, then duplicated in what appears to be a glitch. There’s is no voice over describing the activity.

The vehicles are equipped with a mix of cameras, lidar, radar and ultrasonic sound, according to engadget.  Jaguar Land Rover did not report when all the technology in the video would be available commercially.

The video shows two of the Land Rovers in an off-road test area with difficult conditions performing what the auto OEM calls ‘Connected Convoy’ research, or a form of vehicle-to-Vehicle (V2V) communications.

The demo shows a front car driving through the difficult road area and stopping after about 50 yards, where the driver decides to change his vehicle’s Terrain Response to adapt to conditions.

That change is automatically transmitted wirelessly to car 2, where the driver can decide whether to make the same change.

In another capability, car 1 travels over some rocks and hilly terrain, and the vehicle wirelessly shares wheel slip and suspension data with the rear car. In this demo, car 2 activates its Optimum Terrain Response mode to better handle the road.

The vehicles also apply technology that helps them to identify and predict upcoming road surface changes.

A camera on the front of a vehicle scans the road ahead and finds it will change from asphalt to gravel. The vehicle then prompts the driver to change the terrain response mode.

That capability is pushed further when the vehicle automatically reduces speed to adjust to a new road surface, in this case standing water about a foot deep. The vehicle then automatically returns to its previous speed when the car has driven past the water.

Jaguar Land Rover is a UK-based subsidiary of India’s Tata Motors.

French Shuttle Toddles to Tokyo (Video)

/0 Comments/in , , ,

Burney Simpson

About as exciting as French rock and roll.

EasyMile scored another victory in the driverless-shuttle sector, partnering with Japan’s DeNA to announce an August launch of its bus service in a shopping center in the Chiba Prefecture near Tokyo.

The Robot Shuttle will use EasyMile’s EZ10 electric-powered, driverless shuttle that carries up to 12 passengers and tops out around 25 mph.

Here is a video the companies released that is somewhat like watching paint dry or viewing a major golf tournament.

DeNA is an app maker that has made a name for itself in mobile gaming. Its data-processing expertise could prove valuable as it works to expand into driverless transportation. The company reported revenues of $1.4 billion in its fiscal year ending March 2015, according to The Wall Street Journal.

DeNA has teamed with wireless carrier NTT Docomo with plans to take the EZ10 to public roads in the Japanese city of Fukuoka. That could be a gamechanger for Robot Shuttle as it has been used on private roads or in controlled traffic areas like resort communities.

Nikkei Asian Review reports that Docomo’s “fifth-generation mobile communications network (is) 100 times faster than the current standard. … (and it) aims to have a working 5G service by 2020.”

EasyMile is a joint partnership of two French firms, vehicle manufacturer Ligier Group and robotics experts Robosoft.

Robosoft says it has deployed more than 1,000 robots in business applications in the last three decades.

EasyMile driverless shuttles were used this year during the European Project CityMobil2 conference in San Sebastian in the Basque region of Spain. They have also been demonstrated in Finland, France, Greece, Italy, and Switzerland.

EasyMile reports that more than 1.5 million passengers have been transported since 2008 in its autonomous shuttle models. The firm claims expertise in multi-sensor localization, obstacle detection, navigation, V2I and V2V connectivity, fleet management, and cybersecurity.

Video courtesy of Impress Watch.

Video: NHTSA Driverless Guidelines Coming in July - Rosekind

/0 Comments/in , , , ,

Federal regulators will release deployment guidance and state model policy on autonomous driving technology in July, Mark Rosekind, administrator, National Highway Traffic Safety Administration, told Autoline Network at the TU-Automotive Detroit 2016 show on Thursday. (See the interview below).

The state guidelines are designed to give some uniform structure to autonomous regulations across the nation, said Rosekind.

At the same time, NHTSA must be nimble and flexible in its regulatory approach to driverless vehicles so the rules can evolve as the technology changes, he said.

In addition, we have to make sure the federal role and the state role are clearly identified, Rosekind tells Autoline. Broadly, the feds have oversight of the vehicle while states have oversight of the driver.

For instance, the leader of Volvo complained to US DOT recently that Europe’s patchwork regulatory approach to autonomous driving technology is a hindrance to the technology there, said Rosekind.

“We have a chance in the United States to create a platform that would accelerate (driverless technology) rather than be a barrier,” Rosekind said. “I’m hoping in July when we announce we create a new framework that people around the world will (review). They might say, ‘That’s an approach that works’”, said Rosekind.

NHTSA is working with the American Association Motor of Vehicle Administrators (AAMVA) on the guidelines to ensure that the states are on board with the policy, said Rosekind. The AAMVA is the organization for leaders of state departments of motor vehicles.

NHTSA also will probably ask Congress in July for greater leeway in its oversight of the testing of new vehicles, and for “new kinds of approval process” to speed deployment, said Rosekind.

He noted that NHTSA now has exemption authority over tests of vehicles and equipment, giving it the power to allow a test of a maximum of 2,500 vehicles over two years.

NHTSA might ask Congress for the authority to allow the testing of larger fleets over a longer time frame. That would give it the ability to gather a larger sample of data to be analyzed.

 

Google Car - Google IO 2016

/0 Comments/in

A ‘quick and dirty’ look at Google’s Koala car at the IO 2016. Nothing high-tech here, just a video walk around with a view inside. Interesting to see just how spare the inside is, though it does have pedals.

Thanks to mobilgeeks.de!

Self-Driving, Electric Forklifts Automate Warehouses

/0 Comments/in

Automated, electric-powered forklifts developed at the Carnegie Mellon Robotics Institute are contributing to the growing use of self-driving technology.

Coraopolis, Penn.-based Seegrid takes off-the-shelf electric-powered forklifts, adds hardware and software, and turns them into Vision Guided Vehicles (VGV), said Amanda Merrell, Seegrid marketing director.

This video shows the VGVs in action and contrasts their measured approach to the driving style of their human counterparts.

Once transformed, the VGVs perform such warehouse tasks as Put Away; Long Haul; End of Line where the finished product is taken to a shipping dock; Replenishment where inventory is moved from storage to picking; and more.

Seegrid says its VGVs reduce labor costs, improve warehouse safety, and increase productivity.

Customers include Volvo, Daimler, Denso, BMW, Jaguar Land Rover, and Freightliner.

The hardware that Seegrid adds includes 10 cameras that keep the forklift aware of its surroundings. The software includes coding that allows the warehouse operator to program a driving route for the VGV.

“You simply get on the machine, hit record, drive it on some particular route, get off, hit play, and it just loops around on that route forever,” Seegrid CEO Jim Rock told WESA.fm in Pittsburgh.

It hasn’t all been easy. Seegrid declared Chapter 11 bankruptcy in 2014 as it got ahead of itself and explored new markets. Rock helped the firm to re-focus on its core forklift sector. In addition, supermarket operator Giant Eagle, an original Seegrid funder, agreed to swap debt for a greater equity share of the firm.

The company exited bankruptcy in February 2015.

A customer that purchases VGVs will use the Seegrid Supervisor app to manage the devices. It provides for real-time monitoring, intersection control, and the ability to set operating rules, such as recharging.

The operator programs the forklift to visit a charging station once its battery power has dropped to a certain level, “say when it’s at 30 percent,” said Merrell.

A human is still needed to physically attach the forklift to the recharging station, said Merrell.

Rock says the VGVs have operated safely for more than 125,000 miles due to sensors that stop the forklift when it senses a human is within a certain distance. And the VGVs beep and make other noises as they move so workers are made aware of their presence.  

Dr. Hans Moravec developed Seegrid’s technology at Carnegie Mellon in Pittsburgh. It was officially founded in 2003 and launched its first VGV in 2008.

Nvidia Video of Self-Driving Car in Rain, Unmarked Lanes

/0 Comments/in , , ,

A new video from Nvidia researchers offers an extended view of an autonomous car driving on public roads in

Nearly all of the 14-minute video presents the point of view of a car observing the autonomous vehicle. There are a few minutes showing the autonomous car’s view as it travels a curving country road.

The researchers used an Nvidia DevBox and Torch 7 for training and an Nvidia Drive PX self-driving car using a Torch 7. The system operates at 30 frames per second.

The video shows the vehicle on a multilane highway, a curving country road, moving through a tight curve, driving in the rain, and on an unmarked dirt road.

The video was shot around Matawan and the Cheesequake State Park in N.J.

Much of the video shows the autonomous vehicle in a business park, and in what appears to be a parking lot that may have blocked off standard-driving vehicles.

The new video is linked to a paper “End to End Learning for Self-Driving Cars” from 13 Nvidia researchers based in the firm’s regional office in Holmdel, N.J., an old Bell Labs site.

The paper abstract reports the researchers “trained a convolutional Neural Network (CNN) to map raw pixels from a single-front-facing camera directly to steering commands.”

This system soon learned to drive on local roads “with and without lane markings,” on highways, and on unpaved roads, the researchers report.

The researchers says their system automatically learns how to detect road features with minimal human intervention.

They conclude that their system will bring better performance and smaller systems because “the internal components self-optimize to maximize overall system performance, instead of optimizing human-selected intermediate criteria, e.g., lane detection. Such criteria understandably are selected for ease of human interpretation which doesn’t automatically guarantee maximum system performance.

“Smaller networks are possible because the system learns to solve the problem with the minimal number of processing steps.”