The trend towards communal sidewalk-based personal mobility systems (like shared bikes and scooters) has resulted in some amount of actual personal mobility, but also a lot of cluttered sidewalks, injured riders and pedestrians, and questionable business models. Fortunately, there are other solutions to the last-kilometer problem that are less dangerous and annoying, like this prototype for an inflatable e-bike under development at the University of Tokyo. From a package of folded-up fabric that fits in a backpack, Poimo (POrtable and Inflatable MObility) can be quickly inflated with a small pump into a comfortable and intrinsically safe mobility system that can be deflated again and packed away once you get where you’re going.
The city of Carmel, Ind., has trucks for plowing snow, salting streets, and carrying landscaping equipment. But one cherry-red pickup can do something no other vehicle can: produce its own hydrogen.
A 45-kilogram metal box sits in the bed of the work truck. When a driver starts the engine, the device automatically begins concocting the colorless, odorless gas, which feeds into the engine’s intake manifold. This prevents the truck from guzzling gasoline until the hydrogen supply runs out. The pickup has no fuel cell module, a standard component in most hydrogen vehicles. No high-pressure storage tanks or refueling pumps are needed, either.
Post Syndicated from Mark Anderson original https://spectrum.ieee.org/transportation/self-driving/surprise-2020-is-not-the-year-for-selfdriving-cars
In March, because of the coronavirus, self-driving car companies, including Argo, Aurora, Cruise, Pony, and Waymo, suspended vehicle testing and operations that involved a human driver. Around the same time, Waymo and Ford released open data sets of information collected during autonomous-vehicle tests and challenged developers to use them to come up with faster and smarter self-driving algorithms.
These developments suggest the self-driving car industry still hopes to make meaningful progress on autonomous vehicles (AVs) this year. But the industry is undoubtedly slowed by the pandemic and facing a set of very hard problems that have gotten no easier to solve in the interim.
Five years ago, several companies including Nissan and Toyota promised self-driving cars in 2020. Lauren Isaac, the Denver-based director of business initiatives at the French self-driving vehicle company EasyMile, says AV hype was “at its peak” back then—and those predictions turned out to be far too rosy.
Now, Isaac says, many companies have turned their immediate attention away from developing fully autonomous Level 5 vehicles, which can operate in any conditions. Instead, the companies are focused on Level 4 automation, which refers to fully automated vehicles that operate within very specific geographical areas or weather conditions. “Today, pretty much all the technology developers are realizing that this is going to be a much more incremental process,” she says.
For example, EasyMile’s self-driving shuttles operate in airports, college campuses, and business parks. Isaac says the company’s shuttles are all Level 4. Unlike Level 3 autonomy (which relies on a driver behind the wheel as its backup), the backup driver in a Level 4 vehicle is the vehicle itself.
“We have levels of redundancy for this technology,” she says. “So with our driverless shuttles, we have multiple levels of braking systems, multiple levels of lidars. We have coverage for all systems looking at it from a lot of different angles.”
Another challenge: There’s no consensus on the fundamental question of how an AV looks at the world. Elon Musk has famously said that any AV manufacturer that uses lidar is “doomed.” A 2019 Cornell research paper seemed to bolster the Tesla CEO’s controversial claim by developing algorithms that can derive from stereo cameras 3D depth-perception capabilities that rival those of lidar.
However, open data sets have called lidar doomsayers into doubt, says Sam Abuelsamid, a Detroit-based principal analyst in mobility research at the industry consulting firm Navigant Research.
Abuelsamid highlighted a 2019 open data set from the AV company Aptiv, which the AI company Scale then analyzed using two independent sources: The first considered camera data only, while the second incorporated camera plus lidar data. The Scale team found camera-only (2D) data sometimes drew inaccurate “bounding boxes” around vehicles and made poorer predictions about where those vehicles would be going in the immediate future—one of the most important functions of any self-driving system.
“While 2D annotations may look superficially accurate, they often have deeper inaccuracies hiding beneath the surface,” software engineer Nathan Hayflick of Scale wrote in a company blog about the team’s Aptiv data set research. “Inaccurate data will harm the confidence of [machine learning] models whose outputs cascade down into the vehicle’s prediction and planning software.”
Abuelsamid says Scale’s analysis of Aptiv’s data brought home the importance of building AVs with redundant and complementary sensors—and shows why Musk’s dismissal of lidar may be too glib. “The [lidar] point cloud gives you precise distance to each point on that vehicle,” he says. “So you can now much more accurately calculate the trajectory of that vehicle. You have to have that to do proper prediction.”
So how soon might the industry deliver self-driving cars to the masses? Emmanouil Chaniotakis is a lecturer in transport modeling and machine learning at University College London. Earlier this year, he and two researchers at the Technical University of Munich published a comprehensive review of all the studies they could find on the future of shared autonomous vehicles (SAVs).
They found the predictions—for robo-taxis, AV ride-hailing services, and other autonomous car-sharing possibilities—to be all over the map. One forecast had shared autonomous vehicles driving just 20 percent of all miles driven in 2040, while another model forecast them handling 70 percent of all miles driven by 2035.
So autonomous vehicles (shared or not), by some measures at least, could still be many years out. And it’s worth remembering that previous predictions proved far too optimistic.
This article appears in the May 2020 print issue as “The Road Ahead for Self-Driving Cars.”
Post Syndicated from Charles Q. Choi original https://spectrum.ieee.org/tech-talk/transportation/marine/quantum-water
Underwater quantum links are possible across 30 meters (100 feet) of turbulent water, scientists have shown. Such findings could help to one day secure quantum communications for submarines.
Quantum cryptography exploits the quantum properties of particles such as photons to help encrypt and decrypt messages in a theoretically unhackable way. Scientists worldwide are now endeavoring to develop satellite-based quantum communications networks for a global real-time quantum Internet.
In addition to beaming quantum communications signals across the air, through a vacuum, and within fiber optic cables, researchers have investigated establishing quantum communications links through water. Such work could lead to secure quantum communications between submarines and surface vessels, and with other subs, aircraft, or even satellites.
Two years ago, our own Lawrence Ulrich wrote that Lucid Motors “might just have a shot at being a viable, smaller-scale competitor to Tesla,” with series production of its fiendishly fast electric car, the Air, then slated for 2019.
Here we are in 2020, and you still can’t buy the Air. But now all systems are go, insists Peter Rawlinson, the chief executive and chief technology officer of Lucid and, in a former incarnation, the chief engineer for the Tesla Model S. He credits last year’s infusion of US $1 billion from the sovereign wealth fund of Saudi Arabia.
For the past two months, the vegetables have arrived on the back of a robot. That’s how 16 communities in Zibo, in eastern China, have received fresh produce during the coronavirus pandemic. The robot is an autonomous van that uses lidars, cameras, and deep-learning algorithms to drive itself, carrying up to 1,000 kilograms on its cargo compartment.
The unmanned vehicle provides a “contactless” alternative to regular deliveries, helping reduce the risk of person-to-person infection, says Professor Ming Liu, a computer scientist at the Hong Kong University of Science and Technology (HKUST) and cofounder of Unity Drive Innovation, or UDI, the Shenzhen-based startup that developed the self-driving van.
Post Syndicated from Lawrence Ulrich original https://spectrum.ieee.org/transportation/advanced-cars/2020-top-10-high-tech-cars
In 2019, the auto industry finally started acting like its future was electric. How do we know? Just follow the money.
General Motors just announced it was spending US $20 billion over five years to bring out a new generation of electric vehicles. Volkswagen Group has pledged $66 billion spread over five years, most of it for electric propulsion. Ford hopes to transform its lineup and image with an $11.5 billion program to develop EVs. And of course, Tesla has upstaged them all with the radical, scrapyard-from-Mars Cybertruck, a reminder that Elon Musk will remain a threat to the automotive order for the foreseeable future.
This past year, I saw the first fruit of Volkswagen Group’s massive investment: the Porsche Taycan, a German sport sedan that sets new benchmarks in performance and fast charging. It lived up to all the hype, I’m happy to say. As for Tesla and Ford, stay tuned. The controversial Tesla Cybertruck, the hotly anticipated Ford Mustang Mach-E, and the intriguing Rivian pickup and SUV (which has been boosted by $500 million in backing from Ford) are still awaiting introduction. EV fans, as ever, must be patient: The Mach-E won’t reach showrooms until late this year, and as for the Rivian and Cybertruck, who knows?
As is our habit, we focus here on cars that are already in showrooms or will be within the next few months. And we do include some good old gasoline-powered cars. Our favorite is the Corvette: It adopts a mid-engine design for the first time in its 67-year history. Yes, an electrified version is in the works.
Chevrolet Corvette Stingray C8
The middle: where no Corvette engine has gone before
Base price: US $59,995
By now, even casual car fans have heard that the Corvette has gone mid-engine. It’s a radical realignment for a car famous for big V8s nestling below long, flowing hoods since the ’Vette’s birth in 1953. Best of all, it works, and it means the Stingray will breathe down the necks of Ferraris, McLarens, and other mid-engine exotics—but at a ridiculous base price of just US $59,995.
Tadge Juechter, the Corvette’s chief engineer, says that the previous, seventh-generation model had reached the limits of front-engine physics. By rebalancing weight rearward, the new design allows the Stingray to put almost preposterous power to the pavement without sacrificing the comfort and everyday drivability that buyers demand.
I got my first taste of these new physics near the old stagecoach town of Tortilla Flat, Ariz. Despite having barely more grunt than last year’s base model—369 kilowatts (495 horsepower) from the 6.2-liter V8 rumbling just behind my right shoulder—the Corvette scorches to 60 miles per hour (97 kilometers per hour) nearly a full second quicker, at a supercar-baiting 2.9 seconds.
This Stingray should top out at around 190 mph. And there are rumors of mightier versions in the works, perhaps even an electric or hybrid ’Vette with at least 522 kW (700 hp).
With the engine out back, driver and passenger sit virtually atop the front axle, 42 centimeters (16.5 inches) closer to the action, wrapped in a fighter-jet-inspired cockpit with a clearer view over a dramatically lowered hood. Thanks to a new eight-speed, dual-clutch automated gearbox, magnetorheological shocks, and a limited-slip rear differential—all endlessly adjustable—my Corvette tamed every outlaw curve, bump, and dip in its Old West path. It’s so stable and composed that you’ll need a racetrack to approach its performance limits. It’s still fun on public roads, but you can tell that it’s barely breaking a sweat.
Yet it’s nearly luxury-car smooth and quiet when you’re not romping on throttle. And it’s thrifty. Figure on 9 to 8.4 liters per 100 kilometers (26 to 28 miles per gallon) at a steady highway cruise, including sidelining half its cylinders to save fuel. A sleek convertible model does away with the coupe’s peekaboo view of the splendid V8 through a glass cover. The upside is an ingenious roof design that folds away without hogging a cubic inch of cargo space. Unlike any other mid-engine car in the world, the Corvette will also fit two sets of golf clubs (or equivalent luggage) in a rear trunk, in addition to the generously sized “frunk” up front.
The downside to that convenience is a yacht-size rear deck that makes—how shall we put this?—the Chevy’s butt look fat.
An onboard Performance Data Recorder works like a real-life video game, capturing point-of-view video and granular data on any drive, overlaying the video with telemetry readouts, and allowing drivers to analyze lap times and performance with Cosworth racing software. The camera-and-GPS system allows any road or trip to be stored and analyzed as though it was a timed circuit—perfect for those record-setting grocery runs.
This hybrid is tuned for performance
Base price: US $156,500
Consider the Polestar 1 a tech tease from Volvo. This fiendishly complex plug-in hybrid will be seen in just 1,500 copies, built over three years in a showpiece, enviro-friendly factory in Chengdu, China. Just as important, it’s the first of several planned Polestars, a Volvo sub-brand that aims to expand the company’s electric reach around the globe.
I drove mine in New Jersey, scooting from Hoboken to upstate New York, as fellow drivers craned their necks to glimpse this tuxedo-sharp, hand-built luxury GT. The body panels are formed from carbon fiber, trimming 227 kilograms (500 pounds) from what’s still a 2,345-kg (5,170-pound) ride. Front wheels are driven by a four-cylinder gas engine, whose combo of a supercharger and turbocharger generates 243 kilowatts (326 horses) from just 2.0 liters of displacement, with another 53 kW (71 hp) from an integrated starter/generator. Two 85-kW electric motors power the rear wheels, allowing some 88 kilometers (55 miles) of emissions-free range—likely a new high for a plug-in hybrid—before the gas engine kicks in. Mashing the throttle summons some 462 kW (619 hp) and 1,000 newton meters (737 pound-feet) of torque, allowing a 4.2-second dash to 60 miles per hour (97 kilometers per hour). It’s fast, but not lung-crushing fast, like Porsche’s Taycan.
Yet the Polestar’s handling is slick, thanks to those rear motors, which work independently, allowing torque vectoring—the speeding or slowing of individual wheels—to boost agility. And Öhlins shock absorbers, from the renowned racing and performance brand, combine precise body control with a creamy-smooth ride. It’s a fun drive, but Polestar’s first real test comes this summer with the Polestar 2 EV. That fastback sedan’s $63,750 base price and roughly 440-km (275-mile) range will see it square off against Tesla’s sedans. Look for it in next year’s Top 10.
It has the automation of a much pricier car
Base price: US $24,330
The U.S. market for family sedans has been gutted by SUVs. But rather than give up on sedans, as Ford and Fiat Chrysler have done, Hyundai has doubled down with a 2020 Sonata that’s packed with luxury-level tech and alluring design at a mainstream price.
The Sonata is packed with features that were recently found only on much costlier cars. The list includes Hyundai’s SmartSense package of forward-collision avoidance, automated emergency braking, lane-keeping assist, automatic high-beam assist, adaptive cruise control, and a drowsy-driver attention warning, and they’re all standard, even in the base model. The SEL model adds a blind-spot monitor, but with a cool tech twist: Flick a turn signal and a circle-shaped camera view of the Sonata’s blind spot appears in the digital gauge cluster in front of the driver. It helped me spot bicyclists in city traffic.
Hyundai’s latest infotainment system, with a 10-inch (26-centimeter) monitor, remains one of the industry’s most intuitive touch screens. Taking a page from much more expensive BMWs, the Hyundai’s new “smart park” feature, standard on the top-shelf Limited model, lets it pull into or out of a tight parking spot or garage with no driver aboard, controlled by the driver through the key fob.
That fob can be replaced by a digital key, which uses an Android smartphone app, Bluetooth Low Energy, and Near Field Communication to unlock and start the car. Owners can share digital-key access with up to three users, including sending codes via the Web.
Even the Sonata’s hood is festooned with fancy electronics. What first looks like typical chrome trim turns out to illuminate with increasing intensity as the strips span the fenders and merge into the headlamps. The chrome was laser-etched to allow a grid of 0.05-millimeter LED squares to shine through. Add it to the list of bright ideas from Hyundai.
It outperforms Tesla—for a price
Base price: US $114,340
Yes, the all-electric Porsche Taycan is better than a Tesla Model S. And it had damn well better be: The Porsche is a far newer design, and it sells at up to double the Tesla’s price. What you get for all that is a four-door supercar GT, a technological marvel that starts the clock ticking on the obsolescence of fossil-fueled automobiles.
This past September I spent two days driving the Taycan Turbo S through Denmark and Germany. One high point was repeated runs to 268 kilometers per hour (167 miles per hour) on the Autobahn, faster than I’ve ever driven an EV. From a standing start, an automated launch mode summoned 560 kilowatts (750 horsepower) for a time-warping 2.6-second dash to 60 mph.
As alert readers have by now surmised, the Taycan is fast. But one of its best time trials takes place with the car parked. Thanks to the car’s groundbreaking 800-volt electrical architecture—with twice the voltage of the Tesla’s—charging is dramatically quicker. Doubling the voltage means the current needed to deliver a given level of power is of course halved. Pulling off the Autobahn during my driving test and connecting the liquid-cooled cables of a 350-kW Ionity charger, I watched the Porsche suck in enough DC to replenish its 93.4-kW battery from 8 to 80 percent in 20 minutes flat.
Based on my math, the Porsche added nearly 50 miles of range for every 5 minutes of max charging. In the time it takes to hit the bathroom and pour a coffee, owners can add about 160 kilometers (100 miles) of range toward the Taycan’s total, estimated at 411 to 450 km (256 to 280 miles) under the new Worldwide Harmonized Light Vehicle Test Procedure. But the U.S. Environmental Protection Agency (EPA) seems to have sandbagged the Porsche, pegging its range at 201 miles, even as test drivers report getting 270 miles or more. Porsche hopes to have 600 of the ultrafast DC chargers up and running in the United States by the end of this year.
That 800-volt operation brings other advantages, too. With less current to carry, the wiring is slimmer and lighter, saving 30 kilograms in the electrical harness alone. Also, less current is drawn during hard driving, which reduces heat and wear on the electric motors. Porsche says that’s key to the Taycan’s repeatable, consistent performance.
In its normal driving mode, the Turbo S version kicks out 460 kW (617 horsepower) and 1,049 newton meters (774 pound-feet) of torque. The front and back axles each have an electric motor with a robust 600-amp inverter; in other models the front gets 300 amps and the rear gets 600 amps.
The Porsche’s other big edge is its race-bred handling. Though this sedan tops 2,310 kg (5,100 pounds), its serenity at boggling speeds is unmatched. Credit the full arsenal of Porsche’s chassis technology: four-wheel-steering, active roll stabilization, and an advanced air suspension offering three levels of stiffness, based on three separate pressurized chambers. Porsche claims class-leading levels of brake-energy recuperation. It’s also Porsche’s most aerodynamic production model, with a drag coefficient of just 0.22, about as good as any mass-production car ever.
Porsche invested US $1 billion to develop the Taycan, with $800 million of that going to a new factory in Zuffenhausen, Germany. For a fairer fight with Tesla, a more-affordable 4S model arrives in U.S. showrooms this summer, with up to 420 kW (563 hp) and a base price of $103,800.
Audi RS Q8
Mild hybrid, wild ride
Base price (est.): US $120,000
I’m rocketing up a dormant volcano to the highest peak in Spain, Mt. Teide in the Canary Islands. There may be more efficient ways to test a luxury crossover SUV, but none more fun.
I’m in the Audi RS Q8, a mild-hybrid version of the Q8, introduced just last year. I’m getting a lesson in how tech magic can make a roughly 2,310-kilogram (5,100-pound) vehicle accelerate, turn, and brake like a far smaller machine.
The RS Q8’s pulsing heart is a 4-liter, 441-kilowatt (591-horsepower) twin-turbo V8. It’s augmented by a mild-hybrid system based on a 48-volt electrical architecture that sends up to 12 kW to charge a lithium-ion battery. That system also powers trick electromechanical antiroll bars to keep the body flatter than a Marine’s haircut during hard cornering. An adaptive air suspension hunkers down at speed to reduce drag and center of gravity, while Quattro all-wheel drive and four-wheel steering provide stability.
A mammoth braking system, largely shared with the Lamborghini Urus, the Audi’s corporate cousin, includes insane 10-piston calipers up front. That means 10 pressure points for the brake pads against the spinning brake discs, for brawny stopping power and improved heat management and pedal feel. Optional carbon-ceramic brakes trim 19 pounds from each corner.
Audi’s engineers fine-tuned it all in scores of trials on Germany’s fabled Nürburgring circuit, which the RS Q8 stormed in 7 minutes, 42 seconds. That’s faster than any other SUV in history.
Audi’s digital Virtual Cockpit and MMI Touch center screens are smoothly integrated in a flat panel. A navigation system analyzes past drives to nearby destinations, looking at logged data on traffic density and the time of day. And the Audi Connect, an optional Android app that can be used by up to five people, can unlock and start the Audi.
Audi quotes a conservative 3.8-second catapult from 0 to 100 kilometers per hour (62 miles per hour). We’re betting on 0 to 60 mph in 3.5 seconds, maybe less.
Mini Cooper SE
It offers all-electric sprightliness
The Manhattan skyline paints a stunning backdrop across the harbor. My Red Hook apartment happens to be a short walk from this temporary circuit; so is the neighborhood Tesla showroom, and an Ikea and a Whole Foods, both equipped with EV chargers. In other words, this densely populated city is perfect for the compact, maneuverable, electric Mini, that most stylish of urban conveyances.
It’s efficient, too, as Britain’s Mini first proved 61 years ago, with the front-drive car that Sir Alec Issigonis created in response to the gasoline rationing in Britain following the 1956 Suez crisis. This Mini squeezes 32.6 kilowatt-hours worth of batteries into a T-shaped pack below its floor without impinging on cargo space. At a hair over 1,360 kilograms (3,000 pounds), this Mini adds only about 110 kg to a base gasoline Cooper.
With a 135-kilowatt (181-horsepower) electric motor under its handsome hood, the Mini sails past the Formula E grandstand, quickening my pulse with its go-kart agility and its ethereal, near-silent whir. The body sits nearly 2 centimeters higher than the gasoline version, to accommodate 12 lithium-ion battery modules, but the center of gravity drops by 3 cm (1.2 inches), a net boost to stability and handling. Because the Mini has neither an air-inhaling radiator grille nor an exhaust-exhaling pipe, it’s tuned for better aerodynamics as well.
A single-speed transmission means I never have to shift, though I do fiddle with the toggle switch that dials up two levels of regenerative braking. That BMW electric power train, with 270 newton meters (199 pound-feet) of instant-on torque, punts me from 0 to 60 miles per hour (0 to 97 kilometers per hour) in just over 7 seconds, plenty frisky for such a small car. The company claims a new wheelspin actuator reacts to traction losses notably faster, a sprightliness that’s particularly gratifying when gunning the SE around a corner.
It all reminds me of that time when the Tesla Roadster was turning heads and EVs were supposed to be as compact and light as possible to save energy. The downside is that a speck-size car can fit only so much battery. The Mini’s has less than one-third the capacity of the top Tesla Model S. That’s only enough for a mini-size range of 177 km (110 miles). That relatively tiny battery helps deliver an appealing base price of $23,250, including a $7,500 federal tax credit. And this is still a hyperefficient car: On a subsequent drive in crawling Miami traffic, the Mini is on pace for 201 km (125 miles) of range, though its battery contains the equivalent of less than 0.9 gallon of gasoline.
Following a full 4-hour charge on a basic Level 2 charger, you’ll be zipping around town again, your conscience as clear as the air around the Mini.
Vintage Fiat 124 Spider, Retooled by Electric GT
A drop-in electric-drive system gives new life to an old car—like this 1982 Spider
System base price: US $32,500
Vintage-car aficionados love to grouse about the time and money it takes to keep their babies running. Electric GT has a better idea: Skip ahead a century. The California company has developed an ingenious plug-and-play “crate motor” that transplants an electric heart into most any vintage gasoline car.
I drove an orange 1982 Fiat 124 Spider that Electric GT converted to battery drive. With a relatively potent 89 kilowatts (120 horsepower) and 235 newton meters (173 pound-feet) of torque below its hood, and 25 kilowatt-hours’ worth of repurposed Tesla batteries stuffed into its trunk area, the Fiat can cover up to 135 kilometers (85 miles) of driving range, enough for a couple hours of top-down cruising.
Best of all, the system is designed to integrate exclusively with manual-transmission cars, including the Fiat’s charming wood-topped shifter and five forward gears. This romantic, Pininfarina-designed Fiat also squirts to 60 miles per hour in about 7 seconds, about 3 seconds quicker than the original old-school dawdler.
Electric GT first got attention when it converted a 1978 Ferrari 308, best known as Tom Selleck’s chariot on the U.S. TV show “Magnum, P.I.,” to electric drive. The company’s shop, north of Los Angeles, is filled with old Porsches, Toyota FJ40s, and other cars awaiting electrification.
The crate motors even look like a gasoline engine, with what appears at first glance to be V-shaped cylinder banks and orange sparkplug wires. Systems are engineered for specific cars, and the burliest of the bunch store 100 kWh, enough to give plenty of range.
With system prices starting at US $32,500 and topping $80,000 for longer-range units, this isn’t a project for the backyard mechanic on a Pep Boys budget. Eric Hutchison, Electric GT’s cofounder, says it’s for the owner who loves a special car and wants to keep it alive but doesn’t want to provide the regular babying care that aging, finicky machines typically demand.
“It’s the guy who says, ‘I already own three Teslas. Now, how do I get my classic Jaguar electrified?’ ” says Hutchison.
Components designed for easy assembly should enable a good car hobbyist to perform the conversion in just 40 to 50 hours, the company says.
“We’re taking out all the brain work of having to be an expert in battery safety or electrical management,” Hutchison says. “You can treat it like a normal engine swap.”
Toyota RAV4 Hybrid
A redesigned hybrid system optimizes fuel economy
Base price: $29,470
The RAV4 is the best-selling vehicle in the United States that isn’t a pickup truck. What’s more, its hybrid offshoot is the most popular gas-electric SUV. No wonder: Forty-four percent of all hybrids sold in America in 2018 were Toyotas. And where many hybrids disappoint in real-world fuel economy, the RAV4 delivers. That’s why this Toyota, whose 2019 redesign came too late to make last year’s Top 10 list, is getting its due for 2020.
My own tests show 41 miles per gallon (5.7 liters per 100 kilometers) in combined city and highway driving, 1 mpg better than the EPA rating. Up front, a four-cylinder, 131-kilowatt (176-horsepower) engine mates with an 88-kW (118-hp) electric motor. A 40-kW electric motor under the cargo hold drives the rear wheels. Altogether, you get a maximum 163 kW (219 hp) in all-wheel-drive operation, with no driveshaft linking the front and rear wheels. The slimmer, redesigned hybrid system adds only about 90 kilograms (about 200 pounds) and delivers a huge 8-mile-per-gallon gain over the previous model. Toyota’s new Predictive Efficient Drive collects data on its driver’s habits and combines that with GPS route and traffic info to optimize both battery use and charging. For example, it will use more electricity while climbing hills in expectation of recapturing that juice on the downhill side. And when the RAV4 is riding on that battery, it’s as blissfully quiet as a pure EV. Toyota’s Safety Sense gear is standard, including adaptive cruise control, lane-keeping assist, and automatic emergency braking. Next year will bring the first-ever plug-in hybrid version, which Toyota says will be the most powerful RAV4 yet.
Ford Escape Hybrid
This SUV has carlike efficiency
Base price: US $29,450
Years ago, Americans began abandoning their cars for SUVs. So by now you might think those SUVs would be achieving carlike efficiencies. You’d be correct. Exhibit A: the new Ford Escape Hybrid, with its class-topping EPA rating of 5.7 liters per 100 kilometers (41 miles per gallon)in combined city and highway driving. That’s 1 mpg better than its formidable Top 10 competitor, the Toyota RAV4 Hybrid. Where the Toyota aims for a rugged-SUV look, the Ford wraps a softer, streamlined body around its own hybrid system.
That includes a 2.5-L, four-cylinder Atkinson-cycle engine, and a pair of electric motor/generators for a 150-kilowatt (200 horsepower) total. A briefcase-size battery pack, about a third the size of the old Escape Hybrid’s, tucks below the front passenger seat. The Toyota’s rear electric motor drives the rear wheels independently and thus offers only an all-wheel-drive version. The Escape forges a mechanical connection to the rear wheels, allowing both all-wheel drive and front-wheel-drive versions. The latter is lighter and more efficient when you’re not dealing with snow, ice, off-roading, or some combination of the three. The 0-to-60-mph run is dispatched in a whisper-quiet 8.7 seconds, versus 7.5 seconds for the Toyota. The Ford fires back with powerful, smartly tuned hybrid brakes that have more stopping power than either the Toyota or the gasoline-only Escapes can manage.
Tech features include a nifty automated self-parking function, evasive-steering assist, and wireless smartphone charging. A head-up display available on the Titanium—Ford’s first ever in North America—projects speed, navigation info, driver-assist status, and other data onto the windshield. FordPass Connect, a smartphone app, lets owners use a smartphone to lock, unlock, start, or locate their vehicle, and a standard 4G LTE Wi-Fi system links up to 10 mobile devices.
A plug-in hybrid version will follow later this year with what Ford says will be a minimum 30 miles of usable all-electric range. All told, it’s a winning one-two punch of efficiency and technology in an SUV that starts below $30,000.
Aston Martin Vantage AMR
High tech empowers retro tech
Base price: US $183,081
Take an Aston Martin Vantage, among the world’s most purely beautiful sports cars. Add a 375-kilowatt (503-horsepower) hand-assembled V8 from AMG, the performance arm of Mercedes-Benz. Assemble a team of engineers led by Matt Becker, Aston’s handling chief and the former maestro of Lotus’s chassis development. Does this sound like the recipe for the sports car of your dreams? Well, that dream goes over the top, with the manual transmission in the new Vantage AMR.
Burbling away from Aston’s AMR Performance Centre, tucked along the Nürburgring Nordschleife circuit in Germany, I am soon happily pressing a clutch pedal and finessing the stick shift on the Autobahn. The next thing I know, the Aston is breezing past 300 kilometers per hour (or 186 miles per hour), which is not far off its official 195-mph top speed. That’s a 7-mph improvement over the automatic version. This stick shouts defiance in a world in which the Corvette C8, the Ferrari, the Lamborghini, and the Porsche 911 have sent their manual transmissions to the great scrapyard in the sky.
But what’s impressive is how seamlessly the company has integrated this classic technology with the newest tech, including an adaptive power train and suspension. The AMR’s 1,500-kilogram (3,298-pound) curb weight is about 100 kg less than that of an automatic model.
The seven-speed manual, a once-maddening unit from Italy’s Graziano, has been transformed. An all-new gearbox was out of the question: No supplier wanted to develop one for a sports car that will have just 200 copies produced this year. So Aston had to get creative with the existing setup. Technicians reworked shift cables and precisely chamfered the gears’ “fingers”—think of the rounded teeth inside a Swiss watch—for smoother, more-precise shifts. A dual-mass flywheel was fitted to the mighty Mercedes V8 to dampen resonance in the driveline so the gearbox doesn’t rattle. The standard Vantage’s peak torque has been lowered from 681 to 625 newton meters (from 502 to 461 pound-feet) to reduce stress on transmission gears.
Aston also sweated the ideal placement of shifter and clutch pedal for the pilot. A dual-chamber clutch master cylinder, developed from a Formula One design, moves a high volume of transmission fluid quickly, but without an unreasonably heavy, thigh-killing clutch pedal. A selectable AM Shift Mode feature delivers modern, rev-matching downshifts, eliminating the need for human heel-and-toe maneuvers, with thrilling matched upshifts under full throttle.
The Graziano still takes a bit of practice: Its funky “dogleg” first gear sits off to the left, away from the familiar H pattern of shift gates. Second gear is where you’d normally find first, third replaces second, and so on. The layout originated in old-school racing, the idea being that first gear was unneeded, unless you were rolling through the pit lane. The dogleg pattern allows easier shifting from second to third and back without having to slide the shifter sideways. Once acclimated, I can’t get enough: The shifter grants me precise control over the brawny V8, and the Aston’s every balletic move. More improbably, this sweet shifter on the AMR won’t become a footnote in Aston history: It will be an option on every Vantage in 2021.
This article appears in the April 2020 print issue as “ 2020 Top 10 Tech Cars.”
Post Syndicated from Mark Anderson original https://spectrum.ieee.org/transportation/efficiency/companies-report-rush-electric-vehicle-battery-advances
Electric vehicles have recently boasted impressive growth rates, more than doubling in market penetration every two years between 2014 and 2018. And batteries play a key role in EV performance and price. That’s why some companies are looking to new chemistries and battery technologies to sustain EV growth rates throughout the early 2020s.
Three recent developments suggest that executives are more than just hopeful. They are, in fact, already striking deals to acquire and commercialize new EV battery advances. And progress has been broad—the new developments concern the three main electrical components of a battery: its cathode, electrolyte, and anode.
TESLA’S BIG BETS Analysts think Tesla’s upcoming annual Battery Day (the company hadn’t yet set a date at press time) will hold special significance. Maria Chavez of Navigant Research in Boulder, Colo., expects to hear about at least three big advancements.
The first one (which Reuters reported in February) is that Tesla will develop batteries with cathodes made from lithium iron phosphate for its Model 3s. These LFP batteries—with “F” standing for “Fe,” the chemical symbol for iron—are reportedly free of cobalt, which is expensive and often mined using unethical practices. LFP batteries also have higher charge and discharge rates and longer lifetimes than conventional lithium-ion cells. “The downside is that they’re not very energy dense,” says Chavez.
To combat that, Tesla will reportedly switch from standard cylindrical cells to prism-shaped cells—the second bit of news Chavez expects to hear about. Stacking prisms versus cylinders would allow Tesla to fit more batteries into a given space.
A third development, Chavez says, may concern Tesla’s recent acquisition, Maxwell Technologies. Before being bought by Tesla in May of 2019, Maxwell specialized in making supercapacitors. Supercapacitors, which are essentially charged metal plates with proprietary materials in between, boost a device’s charge capacity and performance.
Supercapacitors are famous for pumping electrons into and out of a circuit at blindingly fast speeds. So an EV power train with a supercapacitor could quickly access stores of energy for instant acceleration and other power-hungry functions. On the flip side, the supercapacitor could also rapidly store incoming charge to be metered out to the lithium battery over longer stretches of time—which could both speed up quick charging and possibly extend battery life.
So could blending supercapacitors, prismatic cells, and lithium iron phosphate chemistry provide an outsize boost for Tesla’s EV performance specs? “The combination of all three things basically creates a battery that’s energy dense, low cost, faster-to-charge, and cobalt-free—which is the promise that Tesla has been making for a while now,” Chavez said.
SOLID-STATE DEALS Meanwhile, other companies are focused on improving both safety and performance of the flammable liquid electrolyte in conventional lithium batteries. In February, Mercedes-Benz announced a partnership with the Canadian utility Hydro-Québec to develop next-generation lithium batteries with a solid and nonflammable electrolyte. And a month prior, the Canadian utility announced a separate partnership with the University of Texas at Austin and lithium-ion battery pioneer John Goodenough, to commercialize a solid-state battery with a glass electrolyte.
“Hydro-Québec is the pioneer of solid-state batteries,” said Karim Zaghib, general director of the utility’s Center of Excellence in Transportation Electrification and Energy Storage. “We started doing research and development in [lithium] solid-state batteries…in 1995.”
Although Zaghib cannot disclose the specific electrolytes his lab will be working with Mercedes to develop, he says the utility is building on a track record of successful battery technology rollouts with companies including A123 Systems in the United States, Murata Manufacturing in Japan, and Blue Solutions in Canada.
STARTUP SURPRISE Lastly, Echion Technologies, a startup based in Cambridge, England, said in February that it had developed a new anode for high-capacity lithium batteries that could charge in just 6 minutes. (Not to be outdone, a team of researchers in Korea announced that same month that its own silicon anode would charge to 80 percent in 5 minutes.)
Echion CEO Jean de la Verpilliere—a former engineering Ph.D. student at the nearby University of Cambridge—says Echion’s proprietary “mixed niobium oxide” anode is compatible with conventional cathode and electrolyte technologies.
“That’s key to our business model, to be ‘drop-in,’ ” says de la Verpilliere, who employs several former Cambridge students and staff. “We want to bring innovation to anodes. But then we will be compatible with everything else in the battery.”
In the end, the winning combination for next-generation batteries may well include one or more breakthroughs from each category—cathode, anode, and electrolyte.
This article appears in the April 2020 print issue as “EV Batteries Shift Into High Gear.”
Neolix, a maker of urban robo-delivery trucks, made an interesting claim recently. The Beijing-based company said orders for its self-driving delivery vehicles were soaring because the coronavirus epidemic had both cleared the roads of cars and opened the eyes of customers to the advantages of driverlessness. The idea is that when the epidemic is over, the new habits may well persist.
Neolix last week told Automotive News it had booked 200 orders in the past two months after having sold just 159 in the eight months before. And on 11 March, the company confirmed that it had raised US $29 million in February to fund mass production.
Of course, this flurry of activity could merely be coincidental to the epidemic, but Tallis Liu, the company’s manager of business development, maintains that it reflects changing attitudes in a time of plague.
“We’ve seen a rise in both acceptance and demand both from the general public and from the governmental institutions,” he tells IEEE Spectrum. The sight of delivery bots on the streets of Beijing is “educating the market” about “mobility as a service” and on “how it will impact people’s day-to-day lives during and after the outbreak.”
During the epidemic, Neolix has deployed 50 vehicles in 10 major cities in China to do mobile delivery and also disinfection service. Liu says that many of the routes were chosen because they include public roads that the lockdown on movement has left relatively empty.
The company’s factory has a production capacity of 10,000 units a year, and most of the factory staff has returned to their positions, Liu adds. “Having said that, we are indeed facing some delays from our suppliers given the ongoing situation.”
Neolix’s deliverybots are adorable—a term this site once used to describe a strangely similar-looking rival bot from the U.S. firm Nuro. The bots are the size of a small car, and they’re each equipped with cameras, three 16-channel lidar laser sensors, and one single-channel lidar. The low-speed version also has 14 ultrasonic short-range sensors; on the high-speed version, the ultrasonic sensors are supplanted by radars.
If self-driving technology benefits from the continued restrictions on movement in China and around the world, it wouldn’t be the first time that necessity had been the mother of invention. An intriguing example is furnished by a mere two-day worker’s strike on the London Underground in 2014. Many commuters, forced to find alternatives, ended up sticking with those workarounds even after Underground service resumed, according to a 2015 analysis by three British economists.
One of the researchers, Tim Willems of Oxford University, tells Spectrum that disruptions can induce permanent changes when three conditions are met. First, “decision makers are lulled into habits and have not been able to achieve their optimum (close to our Tube strike example).” Second, “there are coordination failures that make it irrational for any one decision maker to deviate from the status quo individually” and a disruption “forces everybody away from the status quo at the same time.” And third, the reluctance to pay the fixed costs required to set up a new way of doing things can be overcome under crisis conditions.
By that logic, many workers sent home for months on end to telecommute will stay on their porches or in their pajamas long after the all-clear signal has sounded. And they will vastly accelerate the move to online shopping, with package delivery of both the human and the nonhuman kind.
On Monday, New York City’s mayor, Bill de Blasio, said he was suspending his long-running campaign against e-bikes. “We are suspending that enforcement for the duration of this crisis,” he said. And perhaps forever.
Post Syndicated from Mark Harris original https://spectrum.ieee.org/cars-that-think/transportation/self-driving/echodyne-cognitive-radar-self-driving-cars
As a transportation technology journalist, I’ve ridden in a lot of self-driving cars, both with and without safety drivers. A key part of the experience has always been a laptop or screen showing a visualization of other road users and pedestrians, using data from one or more laser-ranging lidar sensors.
Ghostly three-dimensional shapes made of shimmering point clouds appear at the edge of the screen, and are often immediately recognizable as cars, trucks, and people.
At first glance, the screen in Echodyne’s Ford Flex SUV looks like a lidar visualization gone wrong. As we explore the suburban streets of Kirkland, Washington, blurry points and smeary lines move across the display, changing color as they go. They bear little resemblance to the vehicles and cyclists I can see out of the window.
A lot of people in the auto industry talked for way too long about the imminent advent of fully self-driving cars.
In 2013, Carlos Ghosn, now very much the ex-chairman of Nissan, said it would happen in seven years. In 2016, Elon Musk, then chairman of Tesla, implied his cars could basically do it already. In 2017 and right through early 2019 GM Cruise talked 2019. And Waymo, the company with the most to show for its efforts so far, is speaking in more measured terms than it used just a year or two ago.
It’s all making Gill Pratt, CEO of the Toyota Research Institute in California, look rather prescient. A veteran roboticist who joined Toyota in 2015 with the task of developing robocars, Pratt from the beginning emphasized just how hard the task would be and how important it was to aim for intermediate goals—notably by making a car that could help drivers now, not merely replace them at some distant date.
That helpmate, called Guardian, is set to use a range of active safety features to coach a driver and, in the worst cases, to save him from his own mistakes. The more ambitious Chauffeur will one day really drive itself, though in a constrained operating environment. The constraints on the current iteration will be revealed at the first demonstration at this year’s Olympic games in Tokyo; they will certainly involve limits to how far afield and how fast the car may go.
Earlier this week, at TRI’s office in Palo Alto, Calif., Pratt and his colleagues gave Spectrum a walkaround look at the latest version of the Chauffeur, the P4; it’s a Lexus with a package of sensors neatly merging with the roof. Inside are two lidars from Luminar, a stereocamera, a mono-camera (just to zero in on traffic signs), and radar. At the car’s front and corners are small Velodyne lidars, hidden behind a grill or folded smoothly into small protuberances. Nothing more could be glimpsed, not even the electronics that no doubt filled the trunk.
Pratt and his colleagues had a lot to say on the promises and pitfalls of self-driving technology. The easiest to excerpt is their view on the difficulty of the problem.
“There isn’t anything that’s telling us it can’t be done; I should be very clear on that,” Pratt says. “Just because we don’t know how to do it doesn’t mean it can’t be done.”
That said, though, he notes that early successes (using deep neural networks to process vast amounts of data) led researchers to optimism. In describing that optimism, he does not object to the phrase “irrational exuberance,” made famous during the 1990s dot-com bubble.
It turned out that the early successes came in those fields where deep learning, as it’s known, was most effective, like artificial vision and other aspects of perception. Computers, long held to be particularly bad at pattern recognition, were suddenly shown to be particularly good at it—even better, in some cases, than human beings.
“The irrational exuberance came from looking at the slope of the [graph] and seeing the seemingly miraculous improvement deep learning had given us,” Pratt says. “Everyone was surprised, including the people who developed it, that suddenly, if you threw enough data and enough computing at it, the performance would get so good. It was then easy to say that because we were surprised just now, it must mean we’re going to continue to be surprised in the next couple of years.”
The mindset was one of permanent revolution: The difficult, we do immediately; the impossible just takes a little longer.
Then came the slow realization that AI not only had to perceive the world—a nontrivial problem, even now—but also to make predictions, typically about human behavior. That problem is more than nontrivial. It is nearly intractable.
Of course, you can always use deep learning to do whatever it does best, and then use expert systems to handle the rest. Such systems use logical rules, input by actual experts, to handle whatever problems come up. That method also enables engineers to tweak the system—an option that the black box of deep learning doesn’t allow.
Putting deep learning and expert systems together does help, says Pratt. “But not nearly enough.”
Day-to-day improvements will continue no matter what new tools become available to AI researchers, says Wolfram Burgard, Toyota’s vice president for automated driving technology.
“We are now in the age of deep learning,” he says. “We don’t know what will come after—it could be a rebirth of an old technology that suddenly outperforms what we saw before. We are still in a phase where we are making progress with existing techniques, but the gradient isn’t as steep as it was a few years ago. It is getting more difficult.”
With global consumers tethered to their smartphones, automakers realize their cars need to deliver a similar infotainment experience—even if that means sharing the ride with Google and other tech giants. The long-awaited Android Automotive OS system debuts in a few months in the 2020 Polestar 2, and will ultimately power millions of cars from General Motors, Fiat Chrysler Automobiles, and the Renault-Nissan-Mitsubishi alliance.
If you’re not familiar, Polestar is the new, electric and high-performance division of Sweden’s Volvo Cars and its China-based parent Geely Auto Group. And the Polestar Precept, an electric concept car unveiled online on Tuesday, after the coronavirus forced the cancellation of the Geneva International Motor Show, suggests a bright future for both Polestar design and Android OS.
What would it take to be as free as a bird—flying above the treetops with the wind in your face and the world far beneath your feet?
For Mariah Cain and Jeff Elkins, the team behind DragonAir Aviation of Panama City Beach, Fla., the answer is a personal flying machine that makes the pilot look like a skier grasping two poles, standing atop an oversized hobby drone. For Stephen Tibbitts, who built the Zero-emissions Electric Vehicle Aircraft (ZEVA) ZERO in Tacoma, Wash., it was a bulbous eight-foot disc in which a pilot lies prone, sped across the sky by eight propellers.
Maybe you’d design something different—like a tiny helicopter, open to the breeze? Or a lounge chair surrounded by a ring of rotors? How about a gondola with two sets of blades at its base? Or your machine might resemble a flying motorcycle, with rotors clustered in front and back.
Those are just some of the machines, many of them conceived by startups, built for a competition started by GoFly, a New York-based tech incubator. It plans to offer a US $1 million grand prize to the winners of a fly-off at NASA’s Ames Research Center in California from 27 to 29 February.
The facets of autonomous car development that automakers tend to get excited about are things like interpreting sensor data, decision making, and motion planning.
Unfortunately, if you want to make self-driving cars, there’s all kinds of other stuff that you need to get figured out first, and much of it is really difficult but also absolutely critical. Things like, how do you set up a reliable network inside of your vehicle? How do you manage memory and data recording and logging? How do you get your sensors and computers to all talk to each other at the same time? And how do you make sure it’s all stable and safe?
In robotics, the Robot Operating System (ROS) has offered an open-source solution for many of these challenges. ROS provides the groundwork for researchers and companies to build off of, so that they can focus on the specific problems that they’re interested in without having to spend time and money on setting up all that underlying software infrastructure first.
Apex.ai’s Apex OS, which is having its version 1.0 release today, extends this idea from robotics to autonomous cars. It promises to help autonomous carmakers shorten their development timelines, and if it has the same effect on autonomous cars as ROS has had on robotics, it could help accelerate the entire autonomous car industry.
For more about what this 1.0 software release offers, we spoke with Apex.ai CEO Jan Becker.
IEEE Spectrum: What exactly can Apex.OS do, and what doesn’t it do?
Jan Becker: Apex.OS is a fork of ROS 2 that has been made robust and reliable so that it can be used for the development and deployment of highly safety-critical systems such as autonomous vehicles, robots, and aerospace applications. Apex.OS is API-compatible to ROS 2. In a nutshell, Apex.OS is an SDK for autonomous driving software and other safety-critical mobility applications. The components enable customers to focus on building their specific applications without having to worry about message passing, reliable real-time execution, hardware integration, and more.
Apex.OS is not a full [self-driving software] stack. Apex.OS enables customers to build their full stack based on their needs. We have built an automotive-grade 3D point cloud/lidar object detection and tracking component and we are in the process of building a lidar-based localizer, which is available as Apex.Autonomy. In addition, we are starting to work with other algorithmic component suppliers to integrate Apex.OS APIs into their software. These components make use of Apex.OS APIs, but are available separately, which allows customers to assemble a customized full software stack from building blocks such that it exactly fits their needs. The algorithmic components re-use the open architecture which is currently being built in the open source Autoware.Auto project.
So if every autonomous vehicle company started using Apex.OS, those companies would still be able to develop different capabilities?
Apex.OS is an SDK for autonomous driving software and other safety-critical mobility applications. Just like iOS SDK provides an SDK for iPhone app developers enabling them to focus on the application, Apex.OS provides an SDK to developers of safety-critical mobility applications.
Every autonomous mobility system deployed into a public environment must be safe. We enable customers to focus on their application without having to worry about the safety of the underlying components. Organizations will differentiate themselves through performance, discrete features, and other product capabilities. By adopting Apex.OS, we enable them to focus on developing these differentiators.
What’s the minimum viable vehicle that I could install Apex.OS on and have it drive autonomously?
In terms of compute hardware, we showed Apex.OS running on a Renesas R-Car H3 and on a Quanta V3NP at CES 2020. The R-Car H3 contains just four ARM Cortex-A57 cores and four ARM Cortex-A53 cores and is the smallest ECU for which our customers have requested support. You can install Apex.OS on much smaller systems, but this is the smallest one we have tested extensively so far, and which is also powering our vehicle.
We are currently adding support for the Renesas R-Car V3H, which contains four ARM Cortex-A53 cores (and no ARM Cortex-A57 cores) and an additional image processing processor.
You suggest that Apex.OS is also useful for other robots and drones, in addition to autonomous vehicles. Can you describe how Apex.OS would benefit applications in these spaces?
Apex.OS provides a software framework that enables reading, processing, and outputting data on embedded real-time systems used in safety-critical environments. That pertains to robotics and aerospace applications just as much as to automotive applications. We simply started with automotive applications because of the stronger market pull.
Industrial robots today often run ROS for the perception system and non-ROS embedded controller for highly-accurate position control, because ROS cannot run the realtime controller with the necessary precision. Drones often run PX4 for the autopilot and ROS for the perception stack. Apex.OS combines the capabilities of ROS with the requirements of mobility systems, specifically regarding real-time, reliability and the ability to run on embedded compute systems.
How will Apex contribute back to the open-source ROS 2 ecosystem that it’s leveraging within Apex.OS?
We have contributed back to the ROS 2 ecosystem from day one. Any and all bugs that we find in ROS 2 get fixed in ROS 2 and thereby contributed back to the open-source codebase. We also provide a significant amount of funding to Open Robotics to do this. In addition, we are on the ROS 2 Technical Steering Committee to provide input and guidance to make ROS 2 more useful for automotive applications. Overall we have a great deal of interest in improving ROS 2 not only because it increases our customer base, but also because we strive to be a good open-source citizen.
The features we keep in house pertain to making ROS 2 realtime, deterministic, tested, and certified on embedded hardware. Our goals are therefore somewhat orthogonal to the goals of an open-source project aiming to address as many applications as possible. We, therefore, live in a healthy symbiosis with ROS 2.
[ Apex.ai ]
Post Syndicated from Lawrence Ulrich original https://spectrum.ieee.org/cars-that-think/transportation/sensors/boschs-smart-virtual-visor-tracks-sun
The automotive sun visor has been around for nearly a century, first affixed in 1924 as a “glare shield” on the outside of a Ford Model T. Yet despite modest advances—lighted vanity mirrors, anyone?—it’s still a crude, view-blocking slab that’s often as annoying as it is effective.
Bosch, finally, has a better idea: An AI-enhanced liquid crystal display (LCD) screen that links with a driver-monitoring camera to keep the sun out of your eyes without blocking the outward view. The German supplier debuted the Bosch Virtual Visor at the recent CES show in Las Vegas.
Yesterday I drove from Silicon Valley to San Francisco. It started raining on the way and I hadn’t thought to take an umbrella. No matter—I had the locations of two parking garages, just a block or so from my destination, preloaded into my navigation app. But both were full, and I found myself driving in stop-and-go traffic around crowded, wet, hilly, construction-heavy San Francisco, hunting for street parking or an open garage for nearly an hour. It was driving hell.
So when I finally arrived at a launch event hosted by Cruise, I couldn’t have been more receptive to the company’s pitch for Cruise Origin, a new vehicle that, Cruise executives say, intends to make it so I won’t need to drive or park in a city ever again.
Post Syndicated from Philip E. Ross original https://spectrum.ieee.org/cars-that-think/transportation/self-driving/damons-hypersport-motorcycle-safety-ai
For all its pure-electric acceleration and range and its ability to shapeshift, the Hypersport motorcycle shown off last week at CES by Vancouver, Canada-based Damon Motorcycles matters for just one thing: It’s the first chopper swathed in active safety systems.
These systems don’t take control, not even in anticipation of a crash, as they do in many advanced driver assistance systems in cars. They leave a motorcyclist fully in command while offering the benefit of an extra pair of eyes.
Why drape high tech “rubber padding” over the motorcycle world? Because that’s where the danger is: Motorcyclists are 27 times more likely to die in a crash than are passengers in cars.
“It’s not a matter of if you’ll have an accident on a motorbike, but when,” says Damon chief executive Jay Giraud. “Nobody steps into motorbiking knowing that, but they learn.”
The Hypersport’s sensor suite includes cameras, radar, GPS, solid-state gyroscopes and accelerometers. It does not include lidar–“it’s not there yet,” Giraud says–but it does open the door a crack to another way of seeing the world: wireless connectivity.
The bike’s brains note everything that happens when danger looms, including warnings issued and evasive maneuvers taken, then shunts the data to the cloud via 4G wireless. For now that data is processed in batches, to help Damon refine its algorithms, a practice common among self-driving car researchers. Some day, it will share such data with other vehicles in real-time, a strategy known as vehicle-to-everything, or V2x.
But not today. “That whole world is 5-10 years away—at least,” Giraud grouses. “I’ve worked on this for over decade—we’re no closer today than we were in 2008.”
The bike has an onboard neural net whose settings are fixed at any given time. When the net up in the cloud comes up with improvements, these are sent as over-the-air updates to each motorcycle. The updates have to be approved by each owner before going live onboard.
When the AI senses danger it gives warning. If the car up ahead suddenly brakes, the handlebars shake, warning of a frontal collision. If a vehicle coming from behind enters the biker’s blind spot, LEDs flash. That saves the rider the trouble of constantly having to look back to check the blind spot.
Above all, it gives the rider time. A 2018 report by the National Highway Traffic Safety Administration found that from 75 to 90 percent of riders in accidents had less than three seconds to notice a threat and try to avert it; 10 percent had less than one second. Just an extra second or two could save a lot of lives.
The patterns the bike’s AI tease out from the data are not always comparable to those a self-driving car would care about. A motorcycle shifts from one half of a lane to the other; it leans down, sometimes getting fearsomely close to the pavement; and it is often hard for drivers in other vehicles to see.
One motorbike-centric problem is the high risk a biker takes just by entering an intersection. Some three-quarters of motorcycle accidents happen there, and of that number about two-thirds are caused by a car’s colliding from behind or from the side. The side collision, called a T-bone, is particularly bad because there’s nothing at all to shield the rider.
Certain traffic patterns increase the risk of such collisions. “Patterns that repeat allow our system to predict risk,” Giraud says. “As the cloud sees the tagged information again and again, we can use it to make predictions.”
Damon is taking pre-orders, but it expects to start shipping in mid-2021. Like Tesla, it will deliver straight to the customer, with no dealers to get in the way.
Post Syndicated from IEEE Spectrum Recent Content full text original https://spectrum.ieee.org/whitepaper/test-of-complex-autonomous-vehicle-designs
Autonomous vehicles (AV) combine multiple sensors, computers and communication technology to make driving safer and improve the driver’s experience. Learn about design and test of complex sensor and communication technologies being built into AVs from our white paper and posters.
Key points covered in our AV resources:
- Comparison of dedicated short-range communications and C-V2X technologies
- Definition of AV Levels 0 to 5
- Snapshot of radar technology from 24 to 77 GHz
Post Syndicated from Tekla S. Perry original https://spectrum.ieee.org/transportation/safety/panasonics-cloud-analytics-will-give-cars-a-guardian-angel
Vehicle-to-everything (V2X) technology—“everything” meaning other vehicles and road infrastructure—has long promised that a digital seatbelt would make cars safer. This year Panasonic expects to keep that promise by taking data to the cloud.
Car seatbelts, made mandatory in the United States in 1968, dramatically reduced the likelihood of death and serious injury. Airbags, becoming standard equipment some 20 years later, gave added protection. Roadway innovations—like rumble strips, better guardrail designs, and breakaway signposts—have also done their part.
In the past few years, however, the number of fatalities in U.S. car crashes has been creeping up—possibly (but not provably) because people are increasingly being distracted by their mobile devices. What’s to be done, given how difficult it has been to get people off their cellphones?
Panasonic engineers, working with the departments of transportation in Colorado and Utah, think they can help turn the trend around. They are starting with what some call a digital seatbelt. This technology allows cars to talk to the transportation infrastructure, sending key information like speed and direction, and enables the infrastructure to talk back, alerting drivers about trouble ahead—a construction zone, perhaps, or a traffic jam.
This back-and-forth conversation is already happening on stretches of highway around the world, most notably in Europe. But these efforts use limited information—typically, speed, heading, and sometimes brake status—in limited areas. Panasonic thinks the digital seatbelt could do more for more drivers if it looked at a lot more data and processed it all centrally, no matter where it originates.
So, in the second half of this year, the company is launching Cirrus by Panasonic, a cloud-based system designed to make car travel a lot safer.
The Cirrus system takes the standard set of safety data that today’s cars transmit along the controller-area network (CAN) bus—including antilock brake status, stability control status, wiper status, fog light and headlight status, ambient air temperature, and other details and transmits it to receivers along the roadway. The receivers send the data to a cloud-based platform for analysis, where it can be used to generate personalized safety warnings for drivers.
This data is already being used in a number of ways by auto companies and researchers, but Chris Armstrong, vice president for V2X technology at Panasonic Corp. of North America, says Panasonic is the first company to use so much of it in a commercially available safety system.
“We are building a central nervous system for connected cars,” he says.
Blaine Leonard, transportation technology engineer for the Utah Department of Transportation, says, “Right now, when you are driving down a road, you might see a static road sign that says, ‘Bridge ices before road does,’ or an electronic sign that says ‘Ice ahead, beware.’ ” Drivers generally don’t pay much attention to these very imprecise warnings, he notes. But with Cirrus, Leonard says, “the temperature gauge of a vehicle passing through the area, along with the slippage of its wheels, will give us the exact location of the ice, so we can send that as a message to be displayed on the dashboard of a subsequent vehicle: ‘Ice ahead, 325 feet.’ A driver will be more likely to pay attention to a message that really is just for him. And if he passes through the area and the ice is no longer there, his vehicle will report that back, so the next driver won’t get the alert.”
Or consider an airbag deployment. “With this system,” Leonard says, “we will know within seconds if an airbag deployed, how fast the vehicle was traveling, and how many other cars in that area had airbag deployments. That information can allow us to get an emergency response out minutes faster than if the accident had been reported by a 911 call, and two to three minutes can save a life.”
The Utah Department of Transportation, along with its counterpart in Colorado, is acting as a test bed for the technology. The Utah people expect the data-gathering side of their system to be operational in May. It will start with 30 state-owned vehicles and 40 roadside receivers this year, with each receiver designed to transmit for 300 meters in all directions. (Receivers don’t have to be placed so that their individual ranges always meet; the system will also be able to briefly store data locally and share it with the cloud moments later.)
In the next few years, Utah plans to roll out 220 roadside sensors and equip thousands of vehicles to talk to them; although the department has a five-year plan to work with Panasonic, the exact pace of installation hasn’t been set. Last year, Colorado installed 100 receivers and equipped 94 vehicles; plans to go further are currently on hold pending evaluation by the state’s new administration.
Panasonic will feed data collected from these two implementations into machine-learning programs, which will make the algorithms better at predicting changing or hazardous road and traffic conditions. “For example, if we can build up historical data about weather events—ambient air temperature, status of control systems, windshield wipers—our systems will learn which data elements matter, understand the conditions as they develop, and potentially send out alerts proactively,” Panasonic’s Armstrong says.
Using the system today requires adding a module that collects the data from the CAN bus and sends it to the receivers, receives alerts, and displays the alerts to the driver. Panasonic’s engineers expect that its system will soon have the capability to collect the data and send it out either via dedicated short-range communications (DSRC), a variant of Wi-Fi, or by cellular-based vehicle-to-everything (C-V2X). One or the other method of wireless communication will eventually be built into all cars. Volkswagen is incorporating DSRC in its latest Golf model, and Cadillac has announced plans to start offering it in its crossover vehicles.
And then Panasonic will be free to focus on running the cloud-based platform and making the system available to app developers. The company expects that those developers will find ways to enhance safety even further.
This article appears in the January 2020 print issue as “A Guardian Angel for Your Car.”
As the fraction of vehicles on the road that are electric increases, finding places to charge up away from home gets more complicated. Ideally, you want your car charging whenever it’s parked so that it’s always topped up, but in urban parking garages, typically just a few spaces (if any) are equipped for electric vehicle charging.
Ideally, the number of EV-friendly spaces would increase with demand, but wiring up a bajillion parking spaces with dedicated chargers isn’t likely to happen anytime soon. With that in mind, Volkswagen has come up with a concept for a way to charge any vehicle in a parking garage, using an autonomous mobile robot that can ferry battery packs around and plug them directly into your car.