Hamstrung by lawsuits, the state can't officially keep its goal to ban new gas-powered car sales by 2035. But it's going to keep trying. It's been a weird and confusing few weeks for the auto industry--especially for those who hoped to see more batteries on the road in the coming decade. Just this month: Ford announced a retrenchment in its EV business, canceling some battery-powered vehicle plans and delaying others; the European Commission proposed to backtrack its goal to transition fully to zero-emission cars by 2035; the US government said it would loosen rules that would have required automakers to ratchet up the fuel economy of their fleets. BloombergNEF projects 14 million fewer EVs will be sold in the US by 2030 than it did last year--a 20 percent drop.

Jim O'Brien, general manager, Americas at RAVIN.AI, discusses how AI can be used as a tool to increase transparency in used car sales Consumers have turned the used car market into one of the hottest ever, with prices and sales volumes hitting record highs as new vehicles remain in short supply. But these sales of pre-owned vehicles are still challenging and complex for both buyers and dealers. So now is the time for AI technology, widely deployed in other parts of the auto industry from manufacturing to marketing to autonomous driving features, to play a larger role in making used car sales more efficient and transparent -- for both buyers and sellers. The explosion of used car sales means an explosion of opportunity for dealers -- and the salespeople that sell them. For those who do well, the rewards are great; the gross profit on a used car is between 12% and 15% of the total price, compared to about 7% for new cars.

Are you trying to predict time series but don't know where to start? This blog post will provide a comparison of the most prominent techniques and show you how to implement them. Time Series prediction can be used in a number of business areas. You can think of a number of areas and questions. Generally, a prediction problem involves using past observations to predict or forecast one or more possible future observations. The goal is to guess about what might happen in the future. Knowing the future can impact our decisions today so we have a great interest in predicting it.

We spend a lot of time talking to researchers here at WIRED Transport. Those are the gals and guys filling the spreadsheets, tapping out the algorithms, and splaying in fear as they ride yet another roller coaster for science. This week, we spoke to engineers and developers who have sacrificed mind and body to solve problems, ones like car sickness and unfair school bus schedules. They want to create tools that work for disabled farmers, and electric trucks that drive themselves. Hard stuff, sure, but there's fun to be had along the way.

PARIS – The Renault-Nissan-Mitsubishi alliance is gambling that mass-market drivers are going to pivot soon to electric cars, announcing plans Friday to produce 12 new electric models by 2022 and to make electric cars 30 percent of its overall output. The carmakers -- who collectively sold more vehicles than any other company in the world in the first half of this year -- also announced plans to make "robo-taxis," driverless public transport vehicles and autonomous cars aimed at middle-class consumers. The announcements are part of an overall strategic plan released Friday, aimed at taking advantage of the alliance's growing reach after taking in Mitsubishi Motors Corp. last year to consolidate its position and make electric and driverless cars more affordable. They also unveiled a new logo for the three-way alliance and renamed it Renault-Nissan-Mitsubishi. CEO Carlos Ghosn is betting that upcoming government restrictions on diesel and gasoline cars will push drivers to go electric instead. "We don't' know how much time it's going to take . . . Britain and France have decided to ban new diesel and gasoline car sales from 2040 and China is considering a similar move.

Ride-hailing startup Lyft announced last week that it's making its own self-driving car technology--a move that could help it meet an audacious goal of having autonomous vehicles chauffeur most of its passengers around by 2021. It sounds a bit far-fetched, considering that autonomous cars are still largely in the testing stages, but Lyft is just one of many companies saying that 2021 will be the year that these vehicles finally get out on the roads en masse. So, sure, it could happen. And going along with that positive line of thinking--assuming that we will, in fact, have self-driving cars in 2021--we wondered what other technological marvels and milestones await us in that magical year. According to an array of predictions from tech companies and market researchers, plenty of changes are coming, including many more developments in transportation, lots of people spending time in virtual reality, lab-grown chicken, and, just maybe, male birth control.

Gas powered Smart cars will no longer be sold in the United States and Canada after 2017, according to a letter written by Mercedes Benz CEO Dietmar Exler to car dealerships across the United States. In April, Daimler Chrysler, the parent company of Smart will stop production of gas powered Smart cars and only continue sales until they are sold out. The sales of Smart cars have been erratic since their development in 2008. They sold 24,622 cars in 2008 but only 5,927 in 2010. They have also seen a steady decline in sales since 2014.

The ability to engage service customers--and keep them engaged--is critical to a dealership's revenue and, more importantly, its ability to retain those customers through to the next buying cycle. And that buying cycle is worth a lot more than just one or two cars; according to dealership executive and author Carl Sewell, every customer is worth 517,000 over his or her lifetime. NADA's December 2015 stats report that, although the average new car sale yielded 3.58% gross, the average service yielded 72%. But contacting and engaging service customers takes time, effort, and close monitoring, and that's just not possible for the typical service team when there are hundreds or thousands of customers to work. Not surprisingly, good opportunities get dropped.