This is where AI could help, reckon Xuewei Qi, Matthew Barth and their colleagues at the University of California, Riverside. They are developing a system of energy management which uses a piece of AI that can learn from past experience.
Their algorithm works by breaking the trip down into small segments, each of which might be less than a minute long, as the journey progresses. In each segment the system checks to see if the vehicle has encountered the same driving situations before, using data ranging from traffic information to the vehicle’s speed, location, time of day, the gradient of the road, the battery’s present state of charge and the engine’s rate of fuel consumption. If the situation is similar, it employs the same energy-management strategy that it used previously for the next segment of the journey. For situations that it has not encountered before, the system estimates what the best power control might be and adds the results to its database for future reference. Ultimately, the idea is that the algorithm will also learn from the experiences of its brethren in other cars, by arranging for all such systems to share their data online.
Procter & Gamble, the world’s largest ad spender, apparently came out with guns blazing at agencies and media on Sunday at the Inactive, oops, Interactive Advertising Bureau’s annual “leadership” conference.
Bravo to P&G’s Chief Brand Officer Marc Pritchard for giving the corrupt, fraud-laden, sneaky creeps running the online media world a nice healthy ass-whooping. According to a story in Ad Age, Pritchard told the group…
In the United States, more people were employed in solar power last year than in generating electricity through coal, gas and oil energy combined. According to a new report from the U.S. Department of Energy, solar power employed 43 percent of the Electric Power Generation sector’s workforce in 2016, while fossil fuels combined accounted for just 22 percent. It’s a welcome statistic for those seeking to refute Donald Trump’s assertion that green energy projects are bad news for the American economy.
Just under 374,000 people were employed in solar energy, according to the report, while coal, gas and oil power generation combined had a workforce of slightly more than 187,000. The boom in the country’s solar workforce can be attributed to construction work associated with expanding generation capacity. The gulf in employment is growing with net generation from coal falling 53 percent over the last decade. During the same period, electricity generation from natural gas increased 33 percent while solar expanded 5,000 percent.
As global ride-hailing startup Uber heads toward a possible IPO this year, Wall Street’s eyes will be on its financials. Revenues have continued to grow quickly for the eight-year-old Silicon Valley company, but the bottom line isn’t pretty: Uber was on track to lose about $3 billion in 2016 on net revenue of $5.5 billion, according to Bloomberg News. That’s remarkable for a startup that has raised more than $11 billion with scant capital costs — it does not own a global fleet of cars or much of other hard assets. Uber itself is valued at more than $60 billion.
Can Uber slow its rate of cash burn before losses start to threaten the company’s viability? On the surface, stemming the red ink doesn’t sound so hard. Since it does not own vehicles or employ drivers, the company saves a fortune in capital and workforce costs. But Wharton experts point to other substantial costs: In helping to create an innovative new market — the sharing economy — Uber spent a fortune training, recruiting and subsidizing drivers, giving away free rides so consumers would get hooked on the service, setting up a global system of local and regional offices as well as hiring lawyers to deal with lawsuits and regulators.
“I think Uber thought, ‘We have this platform — this app, this technology — that can be leveraged anywhere in the world, so let’s just go and conquer the world,’” says Wharton management professor Exequiel Hernandez, who wrote two case studies on Uber for his classes, based on interviews with executives. “What Uber underestimated were the costs that didn’t have to do with their technology and their business model, costs that have to do with the politics of being legitimate, [addressing] regulatory resistance and even cultural differences across markets.”
Sion is the first electric production car capable of recharging its batteries from the sun. So now, you’ll never have to worry about range.
Starbucks Corp. says it has become a victim of the success of its mobile order app.
The coffee chain created the app to reduce long lines at the cash register, but Starbucks Operating Chief Kevin Johnson said Thursday the lines have just shifted to the pickup counter.
“The success of mobile order-and-pay has created a new challenge,” Mr. Johnson said in an interview.
Mr. Johnson, who will become chief executive in April when Howard Schultz steps down to focus on building high-end Starbucks stores, said long waits have driven away some potential customers. The number of transactions in the company’s fiscal first quarter were down as a result.
The Internet is an ecosystem. A living entity that billions of people depend on for knowledge, livelihood, self-expression, love…. The health of this system relies on – and influences – everyone it touches. Signs of poor health in any part impacts the whole. We’re all connected.
How healthy is our Internet? How might we understand and diagnose it? We believe this is a timely and necessary conversation, and we hope you’ll join in.
Our individual actions shape the health of the Internet ecosystem. Only by recognizing where the system is healthy can we take positive steps to make it stronger. Only by understanding where it’s at risk can we avoid actions that weaken it.
Peter Altmaier, her chief of staff, spelt out the dangers at a panel debate in Berlin in November. Would Germany still lead the automobile industry when the world shifts to self-driving, electric cars and software overtakes engines as a vehicle’s most important component? “In the future, 50-60 per cent of the value of a car will consist of digital devices and tools, and 20 per cent of batteries,” he said. “So if we’re not careful, we’ll only be responsible for the windows, seats and wheels.”
That fear is spreading across the broader auto industry, but it is felt acutely in Germany where the sector is one of the largest employers. Suppliers are affected as much as the vehicle manufacturers. “If you look at all the companies that make car parts — the transmission, gearboxes, clutches, pistons — they’re all in a difficult spot right now,” says one Frankfurt-based banker. “People don’t want to invest in them because they are not sure there will be any demand for these things in future.”
There have been tons of rumors flying around how what changes Tesla had made to increase the capacity so drastically. Rumors of new cooling patents, increased voltage, new cell double bond wiring, incompatible with older cars, and all sorts of things.
Personally, I figured Tesla wouldn’t reinvent the wheel just yet and go with a whole new pack design, but who knows. Not me, so that had to be corrected. 😀
Without further ado, here is a shot of a module from the 100 kWh pack.
After wrapping up the DARPA Robotics Challenge in 2015, Gill Pratt helped to launch the Toyota Research Institute (TRI), which is investing over a billion dollars in robotics and artificial intelligence over the next five years. As you might expect, a major focus of TRI is automotive autonomy: Toyota is just as interested as any automotive manufacturer at using autonomous systems to make cars safer, more efficient, and more pleasant to drive.
At Toyota’s CES press conference earlier this month, Pratt took the stage to address some of the challenges facing anyone working on automotive autonomy. There are many of these, and frequently, the amount of progress that the industry is making towards full autonomy is misunderstood, or even occasionally misrepresented. With that in mind, he spent a solid 20 minutes giving the audience a much needed reality check.
Gerald Sussman, Hal Abelson, Lalana Kagal, Daniel Weitzner:
When humans and autonomous systems share control of a vehicle, there will be some explaining to do. When the autonomous system takes over suddenly, the driver will ask why. When an accident happens in a car that is co-driven by a person and a machine, police officials, insurance companies, and the people who are harmed will want to know who or what is accountable for the accident. Control systems in the vehicle should be able to give an accurate unambiguous accounting of the events. Explanations will have to be simple enough for users to understand even when subject to cognitive distractions. At the same time, given the need for legal accountability and technical integrity these systems will have to support their basic explanations with rigorous and reliable detail. In the case of hybrid human-machine systems, we will want to know how the human and mechanical parts contributed to final results such as accidents or other unwanted behaviors.
The ability to provide coherent explanations of complex behavior is also important in the design and debugging of such systems, and it is essential to give us all confidence in the competence and integrity of our automatic helpers. But the mechanisms of merging measurements with qualitative models can also enable more sophisticated control strategies than are currently feasible.
Our research explores the development of methodology and supporting technology for combining qualitative and semi-quantitative models with measured data to produce concise, understandable symbolic explanations of actions that are taken by a system that is built out of many, possibly autonomous, parts (including the human operator).
We have currently developed a two-step process to explain what happened and why those events happened in a particular vehicle CAN bus log. In the first step, we take a CAN bus log as input to begin an analysis of what happened during a particular car trip. This analysis includes smoothing noisy data, performing edge detection to find out when particular events occurred (e.g. when did the operator apply the brakes), and interval analysis to see how particular intervals relate to each other (e.g. did the car slow after the brakes were applied?). Using this analysis, we were able to construct a story of what happened in a particular car trip and detect particular events of interest (e.g abrupt changes in speed and braking, and dangerous maneuvers like skids).
In the second step, we take a particular event of interest (that was identified in step 1) and explain why it happened. We have developed three different models to explain vehicle physics in a human readable form. We have constructed a model of the car internals, which explains the process by which individual components of the car affect other components. We have also constructed a purely qualitative physical model of the car, which explains vehicle actions using qualitative terms like increasing, decreasing, no change, and unknown change. While this model is easy for humans to understand, it lacks the level of detail needed to explain more sophisticated actions like skids. So we have also developed a semi-qualitative model of car physics using geometry. This model infers the overall effect on the normal forces and frictional forces on the wheels from the reported lateral and longitudinal acceleration during a particular interval. Then, these effects and their consequences are explained qualitatively to the user.
A few blocks further away from where I live is a somewhat different environment, a commercial shopping, bar, and restaurant area (with the upper floors occupied by M.I.T. spin-off startups), known as Central Square^{\big 3}. There are marked pedestrian crossings there, and mostly people stick to crossing the roads at those designated places. Things are a little less civil here, perhaps because more people driving through are not local residents from right around the neighborhood.
People step out tentatively into the marked cross walks and visually check whether on-coming drivers are slowing down, or indicate in some way that they have seen the pedestrian. During the day it easy to see into the cars and get an idea of what the driver is paying attention to, and the same is actually true at night as there is enough ambient light around to see into most cars. Pedestrians and drivers mostly engage in a little social interaction, and any lack of interaction is usually an indicator to the pedestrian that the driver has not seen them. And when such a driver barrels through the crossing the pedestrians get angry and yell at the car, or even lean their hands out in front of the car to show the driver how angry they are.
Interestingly, many pedestrians reward good behavior by drivers. Getting on the main street or off of the main street from or onto a small side street can often be tricky for a driver. There are often so many people on the sidewalks that there is a constant flow of foot traffic crossing the exits or entrances of the side streets. Drivers have to be patient and ready for a long wait to find a break. Often pedestrians who have seen how patient a driver is being will voluntarily not step into the cross walk, and either with a head or hand signal indicate to a driver that they should head through the crossing. And if the driver doesn’t respond they make the signal again–the pedestrian has given the turn to the driver and expects them to take it.
Eric Newcomer and Olivia Zaleski:
Forty years later, German Tugas, a 42-year-old Uber driver, got to know it for another reason: Its parking lot was a safe spot to sleep in his car. Most weeknights, Tugas drives over 70 hours a week in San Francisco, where the work is steadier and fares are higher than in his hometown, Sacramento. So every Monday morning, Tugas leaves at 4 a.m., says goodbye to his wife and four daughters, drives 90 miles to the city, and lugs around passengers until he earns $300 or gets too tired to keep going. (Most days he nets $230 after expenses like gas.) Then, he and at least a half dozen other Uber drivers gathered in the Social Safeway parking lot to sleep in their cars before another long day of driving.
CarSaver’s digital platform allows car shoppers to select, finance and insure a vehicle through its website or on a touch-screen kiosk, backed by bilingual auto advisers available by phone. Staffers at CarSaver Centers — set up inside Wal-Mart stores across from checkout lanes and alongside other services, such as vision centers and nail salons — will explain the car-buying program to Wal-Mart customers.
Customers will be able to select a new, used or certified pre-owned vehicle and apply for financing and auto insurance on the kiosk at the CarSaver Center, on their mobile device via CarSaver’s website or by calling an 800 number.
CarSaver then will connect customers with a local, certified dealer and schedule an appointment to visit the dealership. If a shopper doesn’t contact the dealership, an auto adviser reconnects with that shopper.
Upon making a sale, the dealership pays CarSaver a “success fee” of $350 in most states. No sale, no payment to CarSaver. Depending on state law, payment may come in the form of a subscription fee.
The annual North American International Auto Show, unlike most similar events in the US, is remarkably well attended by automotive suppliers as well as major OEMs like Bosch. The tier one supplier used the latest show to debut its new eAxle, a compact unit that’s modular and scalable in design.
As you’ll see in the video, the eAxle really is a lot more compact than combining the company’s current individual systems together. “We can realize five-to-ten percent efficiency over standalone components when we move to an integrated unit,” explained Bosch’s Jon Poponea. Look in an electric vehicle on the roads right now, and you’ll probably see a whole bunch of different components, all connected with thick orange-wrapped leads.
But the eAxle packages the inverter together with the motor/generator unit, making for easier packaging, fewer wires, and decreased manufacturing costs. The lowest power output version is 50kW (67hp), but it can be specced up to 300kW (402hp). What’s more, it can also be had as either a permanent magnet or induction motor. Poponea explained that the former is more common to rear axle installations, the latter as a front axle motor providing boost to the powertrain. “It comes down to OEM strategy, and we can certainly support that,” he told Ars.
Bosch certainly thinks there’s a market for the eAxle. It cited internal research that “showed 62 percent of US new car buyers believe they will own at least one full-electric vehicle in their household within 10 years or less,” although interestingly it also noted a significant minority of holdouts—32 percent indicating they would not be interested in buying or leasing an EV within the next 15 years.
Interesting thoughts! So you think the investors and all folks in the tech industry that are bullish on Uber are wrong? What do you think will happen to the company?
I don’t see a success scenario for Uber in the case in which self-driving cars become mass market ready in the near future. Of the services that Uber is currently offering, I can only see one that could end up successful: ride sharing.
Assuming Uber continues to build a large network of drivers & riders they might be able to offer shared rides that are cheap and generate a profit. When Uber Pool works well, it becomes a viable alternative to using public transportation or to owning your own car. Does this outlook justify Uber’s latest valuation of $68 billion?
Without running the numbers myself, I doubt it4. And I can’t imagine investors would be satisfied with Uber focusing on becoming a ride-sharing company. So Uber might be in a similar situation to Twitter – it could offer a good, profitable service if it weren’t for it’s sky high valuation and ambition.
But if you want to work in our business you can’t just come out and say that. You need to hide it under steaming piles of jargon. Otherwise, you might lose your job for being “traditional.”
No, you have to do what MediaPost does — take the obvious and make it incomprehensible.
Anyone with a pulse and an IQ above 20 knows that social media marketing is largely a pile of horseshit and the only way to get any value out of Facebook is to buy ads.
If you go by the news coming out of CES and the Detroit auto show, the future of driving is luminescent. Cars are getting safer, swankier, smarter. But between showcase and wide, open road, there’s a transaction process stubbornly rooted in the 20th century: actually selling these things at the car dealership.
That’s a problem, and not just because nobody enjoys haggling with the sales folks. By virtue of their entrenched position between automaker and consumer, dealers aren’t just responsible for selling new cars to people. They’re the ones who have to explain those cars, and how to use their myriad, confusing, wonderful new features. And, to the surprise of nobody who’s spent time in a dealership lately, they’re sometimes lousy teachers.
The rapid spread of connected devices that can listen and locate has been a boon for law enforcement. Any new technology hooked up to the web has the potential to become a surveillance device, even if it’s original purpose was benign, as shown in a 2016 Arkansas murder investigation where Amazon was asked to hand over audio from a suspect’s Echo.
But such information and much more, I’ve learned, has long been retrievable from cars. Indeed, court documents reveal a 15-year history of what’s been dubbed “cartapping,” where almost real-time audio and location data can be retrieved when cops order vehicle tech providers to hand it over.
One of the more recent examples can be found in a 2014 warrant that allowed New York police to trace a vehicle by demanding the satellite radio and telematics provider SiriusXM provide location information. The warrant, originally filed in 2014 but only recently unsealed (and published below in full), asked SiriusXM “to activate and monitor as a tracking device the SIRIUS XM Satellite Radio installed on the Target Vehicle for a period of 10 days.” The target was a Toyota 4-Runner wrapped up in an alleged illegal gambling enterprise.
If I say “personal electric vehicle,” you might think “Paul Blart: Mall Cop,” or maybe “exploding hoverboards.” You don’t think global transportation revolution.
But in the past few years, with the convergence of better battery technology, lighter materials and smaller, more powerful electric motors, entirely new kinds of transportation have bloomed. The electric powertrain, unlike that of the internal combustion engine, scales smoothly from tiny to huge, powering everything from 10-pound electric skateboards to 20-ton electric buses.
This Cambrian explosion of new vehicles enables two other revolutions: self-driving technology, and the shift from vehicle ownership to transportation as a service.
The perceived wisdom is that Uber has disrupted taxis and that private automobiles are next, but what if we’ve misread what is happening in our cities?
Traditional thinking would suggest that UberPool, which allows users to split the cost of trips with other Uber riders heading in the same direction, will always be inferior to public transport. Sitting in the backseat of a Prius may be more comfortable than standing on a crowded bus or train, continues this reasoning, but carpooling can’t substitute for mass transit at rush hours without massively increasing congestion.
This is wrong. In the last six months, Uber has begun offering shared rides for as little as $1 (81p), introduced optimised pickup points that algorithmically recreate bus stops, and started testing semi-autonomous vehicles it hopes will solve its increasingly contentious labour issues.
In 1929 John Maynard Keynes predicted that by 2029 people in the developed nations could enjoy a perfectly civilised standard of living while working for 16 hours a week. His hope was for our precious hours of extra leisure to be devoted to such edifying pursuits as playing Grand Theft Auto and watching kittens skateboarding on YouTube. (Actually he didn’t predict that bit — he suggested we’d be listening to string quartets and attending poetry recitals but, hey, that was the Bloomsbury Group for you.) Today, however, not only has the work week stayed constant but, in direct contradiction of the theory, the better-paid now work disproportionately longer hours.
In 2008 some of the world’s leading economists contributed to a series of essays (Revisiting Keynes, MIT) discussing why Keynes’s dream now seems so wide of the mark. Between them, they furnished a number of competing theories. Some posited that people like working and that being busy now has the kind of social cachet that being leisured used to.
In contrast to the largely stationary internet of the early 2000s, Americans today are increasingly connected to the world of digital information while “on the go” via smartphones and other mobile devices. Explore the patterns and trends that have shaped the mobile revolution below.
The next frontier in digital advertising may be your car’s windshield.
Automakers, technology companies and glass manufacturers are teaming up to turn the display that graces the front of an iPhone into the windshield of a car — one that can show ads, directions and vehicle information to the person behind the wheel.
The advent of connected cars is creating a new sales battleground, and using a vehicle’s windshield may be the next way to pitch more products and services to consumers. McKinsey & Co. estimates that mobile and data-driven services in autos will generate $1.5 trillion by 2030. At least part of that will be spent projecting information to drivers and passengers right before their eyes.
“When you think of a person driving and what your needs are when you’re on a typical trip, it’s food, it’s fuel and it’s rest stops,” said John Butler, a Bloomberg Intelligence analyst. “Owning the inside of the car is critical, it’s really where the money is made. The real value is locked up in the ad opportunity.”
According to the latest report from our Wireless Smartphone Strategies (WSS) services: Global Smartphone Sales by Replacement Sales vs. Sales to First Time Buyers by 88 Countries : 2013-2022, global smartphone replacement sales outweighed sales to first time buyers in 2013, for the first time ever. In 2017, we expect 78% of global smartphones will be sold to replacement buyers. We forecast replacement smartphone sales will continue to dominate smartphone sales across all 6 regions by 2022.
This extensive report forecasts global smartphone sales by replacement sales and sales to first time smartphone buyers for 88 countries worldwide, from 2013 to 2022. Almost every major country worldwide is covered, including United States, China, India, Indonesia, Japan, South Korea, Russia, Brazil, Mexico, South Africa, Saudi Arabia, UK, Germany, France, Italy and Spain. This report can be used by operators, software developers, content developers, smartphone vendors, component makers, car manufacturers and other stakeholders to determine the distribution of smartphone ownership across the huge global smartphone market.
Uber’s decision this week to start releasing its traffic data from dozens of cities worldwide is a reminder that information can be as important to digital companies in shaping markets and creating value as the software and hardware used to access their services.
Uber says that sharing average travel times gleaned from millions of trips will produce a public benefit. We can safely assume it is also acting for its own benefit. Not only is Uber probably hoping to buy loyalty from the city authorities with which it frequently clashes, it may also be seeking to gain a foothold in a key area of its business model presently outside its control: urban planning and traffic management.
I love everything about self-driving cars to the extent of even taking the Self-Driving Car Engineer Degree at Udacity. That’s why this particular video from the a16z Summit really caught my attention. Frank Chen (a16z partner) goes over the most commonly asked questions about autonomous cars and I’ve decided to dive deeper into each of those here on Medium.
Level by level or straight to level five?
The major assumption is that “Everything that moves will go autonomous”, and we are not only talking about cars, all the trucks on our roads, drones in the sky, shopping cars and even toys will move by itself to the extent that our involvement will become rudimentary, undesired or even illegal.
This class is an introduction to the practice of deep learning through the applied theme of building a self-driving car. It is open to beginners and is designed for those who are new to machine learning, but it can also benefit advanced researchers in the field looking for a practical overview of deep learning methods and their application.
“THIS IS IT!” Maarten Sierhuis says. “I mean, look at this.” He points to a photo of road construction at an intersection in Sunnyvale, California, near Nissan’s Silicon Valley research center, which Sierhuis runs. A line of cones shunts traffic to the left side of the double yellow line. The light is red. A worker holds a “Slow” sign. It’s the sort of seemingly unremarkable situation that can trigger convulsions in the brain of an autonomous vehicle.
“There is so much cognition that you need here,” Sierhuis says. The driver—or the car—has to interpret the placement of the cones and the behavior of the human worker to understand that in this case, it’s OK to drive through a red light on the wrong side of the road. “This is not gonna happen in the next five to ten years.”
During the holiday season, New York City through its Taxi & Limousine Commission (the “TLC”) proposed a new rule expanding data reporting obligations for car service platform companies including Uber and Lyft. If the rule is adopted, car services will now have to report the GPS coordinates of both passenger pick-up and drop-off locations to the city government. Under NY’s Freedom of Information Law, that data in bulk will also be subject to full public release.
This proposal is either a classic case of good intentions gone awry or a clandestine effort to track millions of car service riders while riding roughshod over passenger privacy.
The stated justification for the new rule is to combat “driver fatigue” and improve car service safety. While the goal is laudable and important, the proposed data collection does not match the purpose and makes no sense. Does anyone really think GPS data measures a driver’s hours on the job or is relevant for the calculation of a trip’s duration? If the data collection were really designed to address driver fatigue, then the relevant data would be shift length (driver start/stop times, ride durations, possibly trip origination), not pick up/drop off locations.
The reporting, though, of this GPS data to the city government poses a real and serious threat to passenger privacy. The ride patterns can be mined to identify specific individuals and where they travel. In 2014, for instance, The Guardian reported that the TLC released anonymized taxi ride data that was readily reverse engineered to identify drivers. A 2015 paper shows that mobility patterns can also be used to identify gender and ethnicity. Numerous examples—from the Netflix release of subscriber film ratings that were reverse engineered to identify subscribers to the re-identification of patients from supposedly anonymous health records—show that bulk data can often be identified to specific individuals. Disturbingly, the TLC proposal only makes one innocuous reference to protecting “privacy and confidentiality” and yet includes neither any privacy safeguards against identification of individual passengers from ride patterns nor any exemption from the NY State Freedom of Information Law.
ANY sufficiently advanced technology, noted Arthur C. Clarke, a British science-fiction writer, is indistinguishable from magic. The fast-emerging technology of voice computing proves his point. Using it is just like casting a spell: say a few words into the air, and a nearby device can grant your wish.
The Amazon Echo, a voice-driven cylindrical computer that sits on a table top and answers to the name Alexa, can call up music tracks and radio stations, tell jokes, answer trivia questions and control smart appliances; even before Christmas it was already resident in about 4% of American households. Voice assistants are proliferating in smartphones, too: Apple’s Siri handles over 2bn commands a week, and 20% of Google searches on Android-powered handsets in America are input by voice. Dictating e-mails and text messages now works reliably enough to be useful. Why type when you can talk?
Given the data above, I think it’s fair to say that Alphabet and Facebook as media companies are dominating the digital advertising space. However, if you look only at their ad technology assets, Google is flat year-on-year (with declining margins) and Facebook has effectively exited the ad tech space.
I believe we are on the verge of a renaissance in ad technology, and this current phase – a cull, if you will – is necessary for us to get from here to there. Let’s be clear: this cull is not because Google and Facebook have won in ad:tech! Quite the contrary. It’s because today, if you’re a marketer and you want results, you usually get a better outcome buying inventory on Facebook than you do buying inventory on the open internet. However, we’ve seen Criteo demonstrate that through thoughtful inventory curation, the application of machine learning, and a focus on e-commerce, you can get outstanding results on the open internet. It’s not easy, but it’s possible.
The next cycle of ad technology will be based on a few key elements:
Naomi Tajitsu and Maki Shiraki
Long guarded about what was beneath the hood of its pioneering Prius cars, Toyota Motor plans to open up its powertrain technology to rivals, hoping this will boost sales and speed up the industry’s shift to lower-emission vehicles.
Announcing last week it would expand its gasoline hybrid technology development, Toyota said it would consider selling complete powertrain modules – engines, transmissions and other drive components – to its competitors.
One of the most highly-lauded advantages of self-driving cars is that a world filled with interconnected autonomous vehicles will significantly reduce the number of traffic accidents and resulting deaths. But this comes with an unintentional consequence: fewer organs will be available to hospitals for patients who need transplants.
As a new report from Slate points out, hospitals around the country already struggle with organ supply shortages. About 6,500 Americans die every year waiting for a transplant, and the waiting list for organs has nearly doubled in the past 18 years, from about 65,000 to more than 123,000.
We don’t have enough donated organs to take care of the patients who need transplants as it is, and one in five organs used in transplants come from vehicular accidents. When the number of automotive-related deaths plummets from self-driving cars, one of the most reliable sources of healthy human organs and tissues will plummet as well. Most analyses suggest that autonomous vehicles will eventually prevent over half of the 35,000 deaths that occur on American roads each year, and some reports are much more optimistic.