Plenty of good news: unsubsidised solar below 2.7c/kWh; c. 10% annual decline in Li-ion battery packs to 2030 & increasingly flexible power markets.
Welcome to the seventh issue of The Transportist. As always you can follow along at the blog or on Twitter. I am pleased to report I am now in Sydney, as long promised. Contact information is at the bottom of this newsletter. Due to the move, it should have been a bit lighter than usual, oh well.
As excitedly as we talk about it, you’d think the promise of fully autonomous vehicles is right around the bend, just another few miles and we’ll pull into our destination. In truth, we’re not there yet, and a few sceptics even suggest we’ll never get there — too many bumps in the road ahead.
As engineers, we know that we’ll get to the holy grail of autonomous driving. The key questions are how long will it take, what’s the best route and how much will it cost?
Let’s pull out a map and see how we can get there from here in automotive electronics. We know it will require serious engineering feats to integrate all of the different components and deliver seamless safe performance. The good news is we’re perched on a stepping stone right now: advanced driver assistance systems (ADAS), which are seen today in features such as emergency braking assist, drive- and steer-by-wire and collision avoidance. If we want to see this type of advanced technology in every mass-market vehicle, these systems need to be robust, low cost and low power. But this is what the collaborative design chain ecosystem does well and relentlessly optimizes. These core engineering tenets are a compass that will help us navigate the map toward the holy grail of autonomous vehicles.
Inside a bright auditorium at an abandoned airfield near Munich, rows of men and women gaze at images flashing by on a giant screen: a Mercedes sedan; Porsche and Jaguar SUVs; the face of Elon Musk. “We’re in the midst of an electric assault,” the presenter intones as the Tesla Inc. chief’s photo pops up. “This must be taken very seriously.”
The audience is composed of BMW AG employees flown in for a combination pep rally/horror film intended to make them afraid—very afraid—about the future of the industry. The takeaway: The market is shifting in ways that were unimaginable just a few years ago, and BMW must adapt. The subtext is a recognition that the company has gone from leader to laggard. For years, it set the benchmark in luxury, but it needs to hit the accelerator to fend off resurgent rivals such as Mercedes-Benz and new competitors like Tesla. “BMW is falling behind in electrics,” says Ingo Speich, a fund manager at Union Investment, which owns almost 1 percent of the company.
QUIC is enabled by default in Google’s Chrome browser and underlying Chromium open source browser code. As of March 2017, Chrome accounts for 58.9% of users browsing the web.
Brave blocks QUIC requests. QUIC is an opt-in feature in Opera, and is currently not available in other Firefox, Edge, and Safari. HTTPS requests containing the alt-svc: quic=”:443″ response header fall back to traditional TCP connections in other browsers, or when QUIC fails in Chrome.
Why so unprepared? It seems inconceivable that the structure of an industry with so many artificial constraints can remain intact much past 70 years, while all around it has changed.
This decade alone has been witness to major disruptions in the travel and transportation industries. Most prominent have been in ride sharing – Uber – and in hospitality – Airbnb. Telecommunications, media and music industries have also been turned on their heads; banks and payments are in the firing line; retail generally is being rapidly transformed. There is scarcely an industry whose fundamental structure remains intact. Except the airline industry.
Portland says it wants to be the first city to issue permits for driverless cars, with the goal of getting them on its roads for testing this year.
Autonomous vehicles need to drive and drive and drive, vacuuming up hours of real-life encounters on the road to make their algorithms smarter and safer.
But there’s one thing in relative short supply: cities willing to have test cars on their streets. Portland is trying to change that and be what it says would be the first to issue permits for driverless vehicles, with the goal of getting them on its roads this year.
“The technology is coming,” says Mayor Ted Wheeler. “Either the technology will happen to us, or we are going to shape the playing field.”
Wheeler and Transportation Commissioner Dan Saltzman are directing the Portland Bureau of Transportation to create a policy to open up the city’s streets to self-driving cars.
For years, the mantra in the world of business software and enterprise IT has been “data is the new gold.” The idea was that companies of nearly every shape and size, across every industry imaginable, were essentially sitting on top of buried treasure that was just waiting to be tapped into. All they needed to do was to dig into the correct vein of their business data trove and they would be able to unleash valuable insights that could unlock hidden business opportunities, new sources of revenue, better efficiencies and much more.
Big software companies like IBM, Oracle, SAP and many more all touted these visions of data grandeur, and turned the concept of big data analytics, or just Big Data, into everyday business nomenclature.
Analytics is hard, and there’s no guarantee that analyzing huge chunks of data is going to translate into meaningful insights.
Even now, analytics is also playing an important role in the Internet of Things, on both the commercial and industrial side, as well as on the consumer side. On the industrial side, companies are working to mine various datastreams for insights into how to improve their processes, while consumer-focused analytics show up in things like health and fitness data linked to wearables, and will soon be a part of assisted and autonomous driving systems in our cars.
The truth is, analytics is hard, and there’s no guarantee that analyzing huge chunks of data is going to translate into meaningful insights. Challenges may arise from applying the wrong tools to a given job, not analyzing the right data, or not even really knowing exactly what to look for in the first place. Regardless, it’s becoming clear to many organizations that a decade or more into the “big data” revolution, not everyone is hitting it rich.
Television crews from as far away as the Netherlands and Japan had come to film this moment, when the oldest plant of the nation’s largest automaker turned out its last.
Janesville, Wis., lies three-fourths of the way from Chicago to Madison along Interstate 90. The county seat of 63,500 people is the home town of House Speaker Paul D. Ryan (R) — an old United Auto Workers town in a state led by a new generation of conservative, Gov. Scott Walker (R). It is a Democratic town still, though the economic blow that befell Janesville is the kind of reversal of fortune that drove many working-class Americans to support Donald Trump for president.
The assembly plant began turning out Chevrolets on Valentine’s Day 1923, and, for 8½ decades, the factory, like a mighty wizard, ordered the city’s rhythms. The radio station synchronized its news broadcasts to the shift change. Grocery prices went up along with GM raises. People timed their trips across town to the daily movements of freight trains hauling in parts and hauling away finished cars, trucks and SUVs.
And so, when the plant stopped in the midst of the Great Recession, the people of Janesville — even as they began to reinvent themselves and their town — clung to a faith that GM would reopen the plant so their future could be like their past. Over time, though, people began to confront a question they had not considered before: What choices to make when there were no more good choices left?
The fast-food giant plans to roll out mobile ordering and payment at all 14,000 US locations in the fourth quarter of 2017. According to analysts, beating out the competition and becoming the first to debut mobile ordering nationally would be a major win for McDonald’s.
“Among the hamburger players, we believe that MCD is establishing a first-mover advantage with digital that can drive sustainable share gains in late 2017 and beyond,” analyst Jeff Farmer wrote in a note to clients Monday, CNBC reported.
Wendy’s seems likely to follow McDonald’s in achieving national mobile ordering, with plans to roll out mobile order and pay across half of its locations by the end of 2017, according to Farmer. Burger King and Jack in the Box are lagging behind, as their programs are still being tested.
I’m not too good at reading minds, much less corporate minds, but one thing stands out: For all practical purposes, domestic airlines in the US today are monopolies. They have left just enough market share at their primary hubs to avoid the threat of federal action, and this limited capacity means that open skies treaties won’t significantly increase competition.
When your orientation says “monopoly,” you act like a monopoly. In particular, without the threat of the marketplace, you have a lot of flexibility in the levels of service you provide — your quality — and in what you can charge. Play this game well and you can maximize the amount of money to be paid out to the the people who control the organization and to those who can fire them.
However, as Tom Peters once pointed out, in Thriving on Chaos as I recall, after some point, it’s impossible to order cost cuts without also damaging the customer experience.
Back in the pre-Toyota US auto industry, they had a similar orientation: Customers didn’t appreciate quality and wouldn’t pay for improvements in quality over what Detroit was already producing. As I said, that was pre-Toyota. But weren’t Toyotas cheaper than their American competitors? They were indeed less expensive, but their quality in terms of manufacturing defects and ride experience, was much higher. Detroit claimed “Dumping!” but extensive studies showed that Toyota had evolved a manufacturing system that reduced waste thereby lowering costs organically, rather than just arbitrarily cutting costs by leaving out things.
The company was granted approval by the California Department of Motor Vehicles to test autonomous driving technology on public roads, according to a notice on the DMV’s website on Friday. This is the first time Apple has received approval to test its technology on public streets.
Apple will soon begin testing self-driving car software with existing vehicles, according to a person familiar with the matter. The Cupertino, California-based company started developing a self-driving car to take on Google and Tesla Inc. a few years ago before it pulled back and focused on first developing underlying autonomous technology last year, Bloomberg News has reported.
The tests are the clearest, public sign yet that Apple is serious about a nascent field that could, in time, transform mobility and upend the auto industry. A quarter of all miles driven in the U.S. may happen in shared, self-driving electric cars by the end of the next decade, Boston Consulting Group said this month. Apple wants a piece of this action, but it’s got a lot of competition: 29 other companies have autonomous vehicle testing permits in California.
A 22-year-old Silicon Valley engineer, who was paid by a venture capitalist to skip college, has launched a start-up which aims to solve one of the toughest technical challenges in autonomous driving.
Austin Russell founded Luminar Technologies in 2012, when he was just 17, to create a new version of the laser-based imaging sensor that is known in the automotive industry as Lidar. Backed by investors including the well-known venture capitalist Peter Thiel, Mr Russell unveiled Luminar on Thursday after five years of secretive development, claiming a 50-fold improvement in resolution compared with existing Lidar products.
Lidar sensors have become a key enabler of self-driving cars because they allow vehicles to “see” the world around them, allowing vehicles to navigate and avoid obstacles. Uber and Alphabet’s self-driving car unit, Waymo, are locked in a bitter legal battle over allegations of stolen Lidar designs.
As start-ups, automotive manufacturers and tech companies rush into autonomous driving, supplies of existing Lidar systems from manufacturers such as Velodyne have become so scarce that the devices have a waiting list several months long.
At the same time, limitations in existing Lidar systems such as struggling to see through rain or snow have been seen as a barrier to widespread deployment of autonomous vehicles outside sunny areas such as California.
Mr Russell says that he can solve these supply and quality problems and in doing so, “make autonomous vehicles both safe and ubiquitous” — although crucially he has not disclosed the price he will charge for his Lidar systems.
After tinkering with photonics projects that included laser-powered drones and augmented-reality glasses in his teens, Mr Russell settled on creating high-resolution, long-range Lidar sensors as a way into the nascent autonomous vehicle market, which even then he believed “would eventually become vital to transportation”.
In this blog post, I discuss the vulnerabilities of the Bosch Drivelog Connector OBD-II dongle found by the Argus Research Team. The vulnerabilities allowed us to stop the engine of a moving vehicle using the Drivelog platform.
On February 20th, 2017, in accordance with Argus’ responsible disclosure policy, upon uncovering the vulnerabilities we informed Bosch of our findings. On February 21st, 2017, Bosch’s Product Security Incident Response Team (PSIRT) contacted Argus and began addressing the issue.
In summary, the following two vulnerabilities were found:
Running our autonomous vehicle program as a start-up is giving us the speed we need to continue to stay at the forefront of development of these technologies and the market applications,” she said.
The move comes as traditional automakers are rushing to partner with and acquire technology companies amid a global race to develop cars capable of driving themselves safely with little input from passengers.
In February, Ford Motor said it planned to invest $1 billion over the next five years in Argo AI, an artificial intelligence company, as part of its own push to develop self-driving cars. Ford has also vowed to begin production of a fully automated car — with no steering wheel and no pedals — by 2021. Similar efforts are underway at Audi, BMW and other car companies.
The automotive giants are competing with technology companies that appear to be leading the self-driving race. Google’s automated car subsidiary, Waymo, has racked up more than 200 million miles of driving with various test vehicles, while Tesla already offers its semi-automated Autopilot system in its electric vehicles.
In the United States, the past decade has been marked by booming cities, soaring rents, and a crush of young workers flocking to job-rich downtowns. Although these are heady days for pavement-pounding urbanists, a record 2.6% of American employees now go to their jobs without ever leaving their houses. That’s more than walk and bike to work combined.
These numbers come from a Quartz analysis of data from the US census and the American Community Survey. The data show that telecommuting has grown faster than any other way of getting to work—up 159% since 2000. By comparison, the number of Americans who bike to work has grown by 86% over the same period, while the number who drive or carpool has grown by only 12%. We’ve excluded both part-time and self-employed workers from these and all results.
Yurong You, Xinlei Pan, Ziyan Wang, Cewu Lu
(Submitted on 13 Apr 2017)
Reinforcement learning is considered as a promising direction for driving policy learning. However, training autonomous driving vehicle with reinforcement learning in real environment involves non-affordable trial-and-error. It is more desirable to first train in a virtual environment and then transfer to the real environment. In this paper, we propose a novel realistic translation network to make model trained in virtual environment be workable in real world. The proposed network can convert non-realistic virtual image input into a realistic one with similar scene structure. Given realistic frames as input, driving policy trained by reinforcement learning can nicely adapt to real world driving. Experiments show that our proposed virtual to real (VR) reinforcement learning (RL) works pretty well. To our knowledge, this is the first successful case of driving policy trained by reinforcement learning that can adapt to real world driving data.
Subjects:
As David Welch pointed out in his excellent piece for Bloomberg, “GM expects to earn more than $9 billion this year and analysts predict Ford will generate adjusted profit of about $6.3 billion. On that basis, Tesla is expected to lose more than $950 million.”
Read that back again slowly. And no, that’s not all, it gets even worse than that. Welch goes on to quote Alexander Potter, an analyst at Piper Jaffray Cos., who said the following: “Tesla engenders optimism, freedom, defiance, and a host of other emotions that, in our view, other companies can’t replicate.”
Wait a minute, is this is a financial analyst talking, or one of Elon Musk’s unpaid shills who dot the landscape and crawl out of the woodwork wielding pitchforks the moment someone has the temerity to slam their esteemed leader for his smoke-and-mirrors act? Well, both actually. Yes, Potter is not only an analyst who upgraded the stock on Monday, but also an analyst who has owned a Tesla for seven months and who added, “As they scramble to catch up, we think Tesla’s competitors only make themselves appear more desperate.”
Catch up to what, exactly? Remember, folks, we’re talking about a car company that sold around 80,000 vehicles last year. For the record, GM sold more than 10 million. In the immortal words of Vince Lombardi, “What the hell’s going on out here?!?!”
If you’ve wondered why Tesla continues to be the darling of certain factions on Wall Street, against all rational measures of evaluation, I might add, you only have to re-read Potter’s telling quote to understand the madness. The valuation has nothing to do with any rational measure or reasoned perspective, it’s the Silicon Valley True Believers populating Wall Street who are completely intoxicated by the vapor trail left by the Muskian Vision of bunny rabbits and rainbows being propelled across the sky.
In other words, the Wall Street analysts buying into Tesla have veered off into the land of Cray-Cray, where the sky is bluer and the grass is greener, and The Future will be forged by the visionary brilliance of Elon Musk, and all of those dirty, nasty – and old – smokestack car companies that form the industrial fabric of this nation will be relegated to the scrap heap once and for all, replaced by clean, incandescent factories made up of equal parts magic and group hugs.
During SXSW, there was a brief outage of service from both Fasten and RideAustin. If those names don’t sound familiar to you, it’s because you don’t live in Austin—you are presumably more familiar with the ride-hailing services provided from major international players like Uber and Lyft. In May 2016, when a local ordinance that would have repealed the city’s regulations on those kinds of services—backed by the two titans of the app-based ride-hailing industry—failed at the ballot box, and Uber and Lyft quickly left town.
Since then, Austin has more or less recovered. Off-brand companies like Fasten, Fare, Wingz, GetMe, and InstaRyde, as well as the non-profit RideAustin, popped up and quickly developed a pecking order. Fasten and RideAustin are at the top, offering tens of thousands of rides a week, while the others provide services in a more limited capacity.
We are living in an age in which the behavioral sciences have become inescapable. The findings of social psychology and behavioral economics are being employed to determine the news we read, the products we buy, the cultural and intellectual spheres we inhabit, and the human networks, online and in real life, of which we are a part. Aspects of human societies that were formerly guided by habit and tradition, or spontaneity and whim, are now increasingly the intended or unintended consequences of decisions made on the basis of scientific theories of the human mind and human well-being.
From today, we’re dropping Google adverts from GroundUp. The Google advertising model is broken: not for Google of course, which is massively profitable, but for us, the publishers who have to put up with poor quality, misleading adverts in exchange for small change.
Not too many years ago, newspapers could make real money from advertising. Then along came the Internet, followed by Gumtree, and Google Ads, which with a few minor competitors became the backbone of online advertising. As readers moved to freely available news on the web, so too did advertising revenue.
Deutsche Post DHL Group continues to focus consistently on electro-mobility and its self-developed StreetScooter electric van. In light of the strong customer demand and the vehicles required for the company’s own operations in Germany and the rest of Europe, the logistics provider will double the production capacity of its own electric vehicles from 10,000 to as many as 20,000 by the end of the year. For this purpose, the company will commission another production location in North Rhine-Westphalia. The Group will announce further details in due course.
In addition, the company is now also selling its own electric vehicles – which have so far been optimized for postal operations and delivery purposes – to third parties. At least half of this year’s annual production is planned for external prospective buyers of the vehicles. Deutsche Post DHL Group sees municipal authorities, strategic partners and large fleet customers in Germany and the rest of Europe in particular as potential buyers for starters. The company aims to at least double – from the current number of about 2,500 vehicles – its own StreetScooter fleet for letter and parcel deliveries this year.
Automation has become one of the major ongoing stories regarding the future of the American economy.
What began with the rise of robots – and loss of jobs – across manufacturing industries is now a full blown threat to traditional jobs across all industries, salary bands, and education requirements.
The effects are wide-reaching, no job may be safe.
On the surface, trucking seems to fit perfectly into this national narrative.
Autonomous vehicles are one of the hottest developments in technology across the country, and an automated truck already delivered 50,000 cans of beer within Colorado last fall.
In the early 1980s Chinese leader Deng Xiaoping returned from visits to Japan and the US with a vision of China’s economic future. Seeing a connection between big car industries and economic prosperity, Deng laid out a strategy for transforming China from automotive pauper to automotive powerhouse:
1. Form joint ventures with American, German and Japanese carmakers.
2. Lock in Chinese control over the joint ventures.
3. Get the know-how to build our own high quality Chinese cars.
Thirty five years later, that master plan has come a long way, but is still incomplete. Yes, China has formed joint ventures with all of the world’s top foreign automakers. Yes, Chinese has kept tight control over the joint ventures. And, yes, Chinese brands already control the commercial bus and truck industry, taking more than 90% of sales.
Up until now, however, Chinese automakers have struggled to match the quality of cars made by the global majors. Foreign models produced in China still account for the majority of car sales. Drive the streets of Shanghai and you’ll be struck by the number of VWs, Buicks, Chevys, Hondas, Toyotas and Audis.
We’ve seen a lot of this type of maneuvering already, with GM buying Cruise Automation, Intel acquiring Mobileye, and Ford giving $1 billion to some AI company that no one has ever heard of. Big companies are buying little startups and then leveraging their technology and expertise to round out the much larger-scale enterprise of developing, testing, validating, producing, and distributing self-driving cars.
YOU PROBABLY WON’T BE BUYING A SELF-DRIVING CAR AT A DEALERSHIP
Early on, most highly automated vehicles will be available through mobility services like ride-sharing and car-sharing, Abuelsamid predicts. In other words, you probably won’t be buying a self-driving car at a dealership, but rather riding in one that you hail through an app-based service like Uber or Lyft. These vehicles will be part of a fleet owned by a manufacturer, like Ford or GM. Fleet ownership will help manufacturers manage the issues self-driving vehicles are likely to encounter early on, like accidents. And there will be accidents.
“With all of that in mind, it’s far easier for a manufacturer to replicate the sort of logistics platform that Uber or Lyft have than it is for those companies to invest in and create the development, manufacturing, and service infrastructure that [original equipment manufacturers] have,” Abuelsamid said. “That’s exactly what’s already happening as all the leading OEMs already invested in or developing their own services
Car parts supplier and integrator Delphi Automotive on Thursday announced investments and partnerships in three privately held companies to help carmakers profit from the increasing amount of data produced by the growing number of vehicles connected to the internet.
As cars are equipped with new capabilities, from staying in lanes to driving themselves, they are using and producing vast amounts of information, including where they drive. Delphi said automakers need a single strategy for handling the data as cars become more complex.
Delphi’s chief technology officer, Glen DeVos, told reporters in a briefing that Delphi wanted to partner with data-related companies in three key areas: inside the car itself; as data moves from the car to the cloud; and organizing that data in the cloud so it can be used to generate revenue.
Experienced COBOL programmers can earn more than $100 an hour when they get called in to patch up glitches, rewrite coding manuals or make new systems work with old.
For their customers such expenses pale in comparison with what it would cost to replace the old systems altogether, not to mention the risks involved.
Antony Jenkins, the former chief executive of Barclays PLC, said for big financial institutions – many of them created through multiple mergers over decades – the problems banks face when looking to replace their old technology goes beyond a shrinking pool of experts.
“It is immensely complex,” said Jenkins, who now heads startup 10x Future Technologies, which sells new IT infrastructure to banks. “Legacy systems from different generations are layered and often heavily intertwined.”
Some bank executives describe a nightmare scenario in which a switch-over fails and account data for millions of customers vanishes.
An officer pulls someone over on the side of the highway. The cop sits in the car a moment, runs the plates—they’re fine—and gets out of the car. As he or she approach the driver’s side window, the driver pulls out a gun, shoots the officer, and flees.
This is something close to what happened in Long Island earlier this year, when a Suffolk County police officer was shot during a traffic stop. Unlike the recent traffic-stop shooting in Hattiesburg, Mississippi, the suspect in the New York case, police told CBS, was a “known gang member.”
Robotic cars are great at monitoring other cars, and they’re getting better at noticing pedestrians, squirrels, and birds. The main challenge, though, is posed by the lightest, quietest, swerviest vehicles on the road.
“Bicycles are probably the most difficult detection problem that autonomous vehicle systems face,” says UC Berkeley research engineer Steven Shladover.
Nuno Vasconcelos, a visual computing expert at the University of California, San Diego, says bikes pose a complex detection problem because they are relatively small, fast and heterogenous. “A car is basically a big block of stuff. A bicycle has much less mass and also there can be more variation in appearance — there are more shapes and colors and people hang stuff on them.”
There was not much to see when I arrived at the entrance to the small business park in the sleepy Silicon Valley town of San Carlos. Signage for three of its units were blank but, upon closer inspection, I could just make out the word Zoox on a door. I had tracked the company to this location using visa and property records, and was hoping to get a glimpse of what it was up to.
The name Zoox probably does not mean much to its neighbors, or even to electric vehicle fans seeking the birthplace of Tesla Motors, which started in this very building in 2004. But behind these glass walls and shuttered garages is one of the most buttoned-up and most valuable autonomous vehicle startups in the world.
Forget getting kicked out of Austin — Uber just got banned from an entire country.
The ride-hailing service is now blocked in Italy after a judge ruled Friday that it created unfair competition.
Unlike rulings in other European countries, where the use of UberX or the European version (UberPop) has been limited, Italy’s ruling blocks all of Uber’s services: UberBLACK, UberLUX, UberX, UberXL and UberSelect among them.
Since 2010, buyers of quali ed plug-in electric-drive vehicles have been eligible for a federal tax credit of up to $7,500. These credits are available for the rst 200,000 customers of each auto company producing eligible vehicles. To date, Tesla has sold nearly 100,000 vehicles, which would put the company near the halfway point of its 200,000 federal tax credit allotment assuming its customers received the credit. Nissan, which is expected to debut a second-generation Leaf next year, is about halfway through its credit allotment. General Motors, which has the Bolt and Volt among others, is expected to run out of credits at some point in late 2018 or 2019.
Federal tax credits for EVs are a part of broader set of EPA policies, which require congressional approval to adjust. So the Trump administration may
not eliminate them prematurely but is unlikely to extend these credits. Without these credits, this market is likely to crash. While President Trump did not address federal EV tax credits speci cally in his 2018 budget blueprint released last month, he proposed the elimination of funding for the Department of Energy’s Advanced Technology Vehicles Manufacturing (ATVM) loan program, which would have assisted future EV production.
Without these credits, this market is likely to crash.
Uber has devised a “clever and sophisticated” scheme in which it manipulates navigation data used to determine “upfront” rider fare prices while secretly short-changing the driver, according to a proposed class-action lawsuit against the ride-hailing app.
When a rider uses Uber’s app to hail a ride, the fare the app immediately shows to the passenger is based on a slower and longer route compared to the one displayed to the driver. The software displays a quicker, shorter route for the driver. But the rider pays the higher fee, and the driver’s commission is paid from the cheaper, faster route, according to the lawsuit.
Unfortunately it made no difference. Two months after launching the platform we started to learn that our core hypotheses were just not correct.
Trucks have much less available space than the Eurostat data leads to believe. Firstly the data only considers cargo weight. So lightweight cargo skews the data. Secondly reporting the data to Eurostat is an annoyance for the trucking companies — so who knows what’s in those reports.
Even if the trucks have spare space and are close to the pickup location of the cargo they more often than not are not willing to pick up the loads in reality. That was a big and nasty surprise. The trucks are running on such a tight schedule for their existing clients that they just cannot afford to spend time on extra loads. They might miss a deadline and lose a loyal customer.
Even when the trucks were willing to pick up the loads they quoted prices higher than regular logistics operators such as DSV or Dachser. Basically trucking companies were willing to drive thousands of kilometers partially empty instead of filling up the truck by offering a competitive price. Literally it was cheaper for the shipper to contract DSV who dispatches one truck to bring the freight to a terminal, a second truck to do a terminal to terminal line haul and a third truck to make the last mile delivery. The risk of losing time by sending a big truck to pick up partial loads from unknown loading places pushed up the price.
This week’s report about a stagnation in U.S. vehicle sales may be a sign that the auto industry is about to head back down the mountain at a rapid pace after a peak last year.
Deutsche Bank said March’s weak sales, coming amid rising interest rates and a slide in used-vehicle prices, make for a potentially slippery outlook. Industrywide deliveries last month slowed to a seasonally adjusted annual pace of 16.6 million vehicles, contradicting analyst expectations that the rate would accelerate to 17.2 million. Automakers set a record in the U.S. last year, with 17.6 million vehicles sold.
“Somewhat ominously, today’s market increasingly resembles one we described in ‘A Triple Threat’ (Feb. 20, 2004),” Deutsche Bank analysts Rod Lache, Mike Levine and Robert Salmon wrote in a note on Tuesday. “In that report we highlighted the risks to the industry from rising rates, rising negative equity in vehicle loans and used vehicle-price deflation. This could lead to deteriorating affordability, delayed trade-in cycles, consumer shifts from new to used, diminishing credit availability and deteriorating mix/pricing.”
A key concern is that fewer cars are being taken off the road — scrappage has declined to about 11 million a year from about 13 million to 14 million a decade ago. While net new drivers jumped to 4 million in 2015, that may not be enough. Total vehicles in the U.S. have increased to 270 million, from 249 million at the end of 2012.
“This has led us to question whether the U.S. is broadly oversupplied, and whether trend demand in the 17 million range is fundamentally supported,” the analysts wrote. “If it is not, the oversupply should be self-correcting — the U.S. market will experience declining used-vehicle prices, pressuring new vehicle sales.”
Bonds comprised of subprime auto loans were a bright spot for the securitization industry following the housing bust. In recent weeks, however, analysts and investors have been debating what impact rising delinquencies may have on the sector. “Credit performance for both prime and subprime auto loan ABS is expected to continue to deteriorate, although at a moderate pace,” analysts at Bank of America Merrill Lynch said in a report last week.
Deutsche Bank also noted the following:
• Used-vehicle price declines accelerated to 7.7 percent in February, from an average fall of 3.5 percent in the first nine months of 2016.
• Sales have bifurcated, with significant declines for passenger cars, while trucks hold at a 10 million-11 million a year pace
• Ford Motor Co. and General Motors may need to cut their car production again in the second quarter and add additional incentives to keep inventories manageable
• A few select market segments have a positive outlook, with pickup demand up 6 percent so far this year, and the analysts view American Axle & Manufacturing Holdings Inc. and Dana Inc. as “compelling” thanks to their exposure to the market segment.
• Delphi Automotive, BorgWarner Inc. and Goodyear Tire & Rubber Co. have a positive long-term outlook.
Brazil’s lower house of Congress voted on Tuesday to give cities greater power to regulate ride-hailing app Uber and other transportation apps, paving the way for local governments to charge taxes, require insurance and pension benefits for drivers.
In a symbolic vote, a majority of lawmakers approved the main text of the bill and voted on specific items that still need to be cleared in the Senate. One of the approved amendments would require cities to authorize Uber services.
That amendment, which makes ride-hailing services a public interest activity, could interrupt Uber services in cities that lack regulation, Daniel Coelho, one of the lawmakers in charge of drafting the legislation, told reporters after the vote.
Navigant Research Leaderboard Report:
Automated vehicles are quickly nearing a level of maturity that will enable initial deployments for consumers. A large group of companies are actively developing complete automated driving systems and the components that go into those systems, including automotive OEMs, suppliers, non-automotive technology companies, and startups. Several of these companies entered this market recently but rapidly moved into contention through acquisitions, investments, and strategic hiring of key personnel. Others have been working on automated driving technology for decades.
This Navigant Research Leaderboard Report examines the strategy and execution of 18 leading companies developing automated driving systems. These players are rated on 10 criteria: vision; go-to market strategy; partners; production strategy; technology; sales, marketing, and distribution; product capability; product quality and reliability; product portfolio; and staying power. Using Navigant Research’s proprietary Leaderboard methodology, companies are profiled, rated, and ranked with the goal of providing an objective assessment of their relative strengths and weaknesses in the global market for automated driving systems.
The secretive ride-hailing giant Uber rarely discusses internal matters in public. But in March, facing crises on multiple fronts, top officials convened a call for reporters to insist that Uber was changing its culture and would no longer tolerate “brilliant jerks.”
Notably, the company also announced that it would fix its troubled relationship with drivers, who have complained for years about falling pay and arbitrary treatment.
“We’ve underinvested in the driver experience,” a senior official said. “We are now re-examining everything we do in order to rebuild that love.”
The secretive ride-hailing giant Uber rarely discusses internal matters in public. But in March, facing crises on multiple fronts, top officials convened a call for reporters to insist that Uber was changing its culture and would no longer tolerate “brilliant jerks.”
Notably, the company also announced that it would fix its troubled relationship with drivers, who have complained for years about falling pay and arbitrary treatment.
“We’ve underinvested in the driver experience,” a senior official said. “We are now re-examining everything we do in order to rebuild that love.”
And yet even as Uber talks up its determination to treat drivers more humanely, it is engaged in an extraordinary behind-the-scenes experiment in behavioral science to manipulate them in the service of its corporate growth — an effort whose dimensions became evident in interviews with several dozen current and former Uber officials, drivers and social scientists, as well as a review of behavioral research.
Uber’s innovations reflect the changing ways companies are managing workers amid the rise of the freelance-based “gig economy.” Its drivers are officially independent business owners rather than traditional employees with set schedules. This allows Uber to minimize labor costs, but means it cannot compel drivers to show up at a specific place and time. And this lack of control can wreak havoc on a service whose goal is to seamlessly transport passengers whenever and wherever they want.