GM’s China studio created a sporty EV concept for local market appeal.
Sketches show a grille-less SUV with arrow cues and wraparound glass.
The design may inspire future Chevrolet models for Chinese customers.
The world’s largest automotive market has become a linchpin for General Motors, a place where nearly all its brands are striving to secure a stronger presence. To that end, GM’s China Advanced Design studio has unveiled another fresh concept study, a “sporty EV” created specifically with Chinese buyers in mind.
The exploration sketches and renderings were made by GM designer Charles Huang at the company’s Shanghai facilities. They show what looks like a small crossover – some might even see shades of a future Bolt – with oversized wheels and a contrasting bi-tone paint scheme.
At the front, the concept trades a traditional grille for a clean, enclosed surface with split LED headlights and a Chevrolet emblem that may light up. The bodywork is restrained, defined by crisp lines and minimal decorative detailing.
The most striking element is the wraparound glasshouse, framed by a thick C-pillar that seems to clasp the rear of the vehicle. The contrast between the deep blue and black tones amplifies this visual tension.
GM Design / Instagram
According to the designer, the profile is inspired by a “released arrow”, an idea most evident in the early sketches. The later, photorealistic renderings dial the drama back, edging closer to something feasible for production.
In fact, it’s easy to picture this crossover parked in a Chevrolet showroom, fitted with regular mirrors and door handles, of course, assuming those still have a place in modern EV design.
The presentation on the GM Design Instagram profile doesn’t include any sketches of the interior. We don’t have any specs, either, although a rear-mounted electric motor and a medium-sized battery pack would probably do the job.
The EV seems to have a similar length to the Chinese-spec Chevrolet Tracker RS and the US-spec Bolt. That puts it below the Trailblazer, Trax, Equinox EV, and Blazer currently sold in the States.
While the Chevrolet concept is just a design study with no production intent, GM is working on multiple affordable EVs for the future. It is safe to assume that at least some of them will adopt an SUV bodystyle, possibly similar to the “sporty EV” depicted in the sketches.
Though GM describes the project as a design study with no immediate production intent, it arrives at a time when the company is actively developing several affordable EVs for many markets. It’s likely that some of those models will borrow cues from this study, especially the SUV silhouete.
GM Design revealed two new Buick concept vehicles created in China.
One of them is a family-oriented compact SUV with modern styling.
The other is a sleek crossover with a sporty estate stance and suicide doors.
Buick is enjoying solid momentum in China, with consistent demand for the Envision SUV, LaCrosse sedan, and GL8 minivan keeping showrooms busy. Even so, the design team continues to push forward, developing fresh ideas and refining future models.
Two of these design studies just appeared on the General Motors Design Instagram account: one is a family compact SUV, the other a sportier crossover estate. Different takes, but both look unusually ready for production.
Both concepts were developed at the GM Advanced Design studio in Shanghai, China. One is designed by Sangmin Kim, while the other is designed by Yixuan Feng.
GM Design / Instagram
Starting with the more conventional concept, it’s described as “a fun, family-oriented premium Buick design study” created around the theme “driving in comfort.”
Up front, split LED headlights feature futuristic internal graphics, compensating neatly for the absence of a traditional grille. Along the sides, large bi-tone alloy wheels fill the arches, framed by glossy black cladding and muscular fenders.
The thick C-pillars flow into a rear spoiler that wraps around the back window, where the taillights are integrated beneath the glass. The rear also features a wide tailgate and a sculpted bumper with a discreet diffuser. Despite modest ground clearance, the upright front end, roof rails, and protective cladding lend it an SUV stance reminiscent of the Kia Niro.
Buick hasn’t revealed technical details, but the proportions seem to place this concept between the 171.4 inches (4,355 mm) of the Encore GX and the 182.7 inches (4,645 mm) of the Envision.
GM Design / Instagram
The next concept is described as a “small, expressive premium Buick design study” built around the idea of “driving pleasure.” It adopts an aerodynamic crossover hatchback or estate profile, complete with suicide doors and a split tailgate.
The front end features an illuminated grille, slim headlights, and ADAS sensors hidden in the bumper intakes. The forged aluminum wheels have shiny chrome accents, while the surfacing in front of the toned rear shoulders looks inspired by Lexus.
Other highlights include the panoramic sunroof, the flying buttresses, the swooping rear glass, and the reflective taillights. Overall, the model appears to be smaller in size compared to the Electra-L Shooting Brake concept from 2024.
What’s Next For Buick?
Buick’s design language is shifting toward New Energy Vehicles (NEV), and both of these concepts seem well-suited to fully electric or range-extender setups.
While the models are labeled as design studies, they could easily pass for production vehicles, as they don’t have any wildly futuristic features. Buick is reportedly working on an electric subcompact crossover, which is set to arrive before 2029, followed by a new generation of the Encore GX.
Peugeot is giving us a sneak look at its future with the Polygon concept.
The exterior design and new i-Cockpit interior hint at the next 208 hatch.
Its square steering wheel is connected to the driving wheels virtually.
Peugeot has followed up on last week’s tease of its Polygon concept by giving us a proper look at the futuristic hatch, and now we’re even more pumped for the arrival of the next 208.
Though the French brand doesn’t specifically mention the 208 in its concept blurb, it’s clear that what we’re looking at gives us some strong pointers to both the design and technical makeup of the next-generation supermini due in 2027.
Sure, the extra-long gullwing doors will be swapped for four conventional ones by the time the production 208 appears. But the overall design language, the pinched waist, broad shoulders, large glass area and focus on recycled materials all hint at where the big-selling supermini – and all future Peugeots – are heading.
Details like charging port and LED charge status indicator in the C-pillar (which reference the classic 205’s design) seem like strong candidates for the production treatment, as are the horizontally oriented reimagining of the brand’s now familiar three-claw light signature.
But it’s the Polygon’s interior that Peugeot really wants us to focus on. It gets a next-generation take on the i-Cockpit interior, which for a decade has been placing the instruments above the steering wheel to make them more visible to drivers.
Here, the entire windshield becomes a gauge cluster and infotainment screen that’s equivalent to having a 31-inch display.
The focal point, though, is the Hypersquare rectangular steering wheel, something Peugeot began teasing on concepts a couple of years ago.
Each of the four circles within the wheel is a pod containing key controls, and steer-by-wire tech means the wheel’s gearing can be increased at parking speeds, reducing the number of turns to less than one.
Peugeot says it’s no mere show-car fantasy, either. Both the wheel and the steer-by-wire tech that “connects” it to the driving wheels will be on a production Peugeot by 2027, the company says, meaning the next 208.
Skoda designers reimagine the classic 1000 MBX coupe as a modern EV.
It features a 2+2 cabin, rear suicide doors, and added cargo versatility.
The concept envisions EV power with height-adjustable air suspension.
Skoda continues its digital concept series that reimagines past icons through a modern lens. Following reinterpretations of the Felicia Fun pickup, the Favorit hatchback, and the 110 R coupe, the automaker now revisits the 1000 MBX coupe from the 1960s, transforming it into something reminiscent of a Mazda RX-8 in form, though powered by electricity.
The new concept was created by Skoda designers Antti Mikael Savio on the exterior and David Stingl on the interior. Development took around three to four weeks, beginning with rough sketches on scraps of paper and concluding with a complete 3D digital model.
What Inspired the Look?
The project draws inspiration from the classic 1000 MBX, which was introduced in 1966 as the two-door coupe version of the 1000 MB sedan. Skoda produced a total of 2,517 units, making it a rare sight today.
The modern interpretation keeps a similar bodystyle but adds an extra pair of rear-hinged doors for easier access to the 2+2 cabin, giving the whole design a hint of the now-discontinued Mazda RX-8.
As with earlier concepts in the series, Skoda avoided leaning into retro pastiche. Even so, it nods to the original through carefully chosen details that align with the brand’s Modern Solid design philosophy.
The LED front lighting signature echoes the chrome grille of the classic, while the headlights rise slightly from the hood in a familiar gesture. The C-pillar shape and tail contours also recall the past. A central fin topped with a rearview camera replaces the traditional rear window, lending a futuristic twist.
Antti Savio, who was responsible for the exterior design, explained: “Our concept is sportier overall, yet, still has a friendly look. Modern sports cars often appear overly aggressive, while those from the ’60s and ’70s carried a certain elegance, even endearing charm – and that’s what I wanted to preserve.”
Inside the Cabin
The interior has a 2+2 layout with a front bench seat made possible by the flat floor of the EV architecture, and two individual tip-up seats at the back. The latter can easily move out of the way, creating an open space that can be used to transport a bicycle or other sports equipment.
At the front, a transparent oval-shaped dashboard replaces the traditional setup, and there’s no central console, a design choice inspired by classic interiors.
Interior designer David Stingl said, “This car should encourage its crew to go exploring without a moment of hesitation. It’s not meant to be just a fun weekend coupé or a second car in the family, but a vehicle with genuine everyday usability.”
Electric Vision
Skoda didn’t get into specifics about the fully electric powertrain of the concept, though the designers imagined it with adaptive air suspension capable of adjusting ride height for either a low, sporty stance or greater clearance on rougher ground.
While Skoda fans might wish for a production version of this compact coupe, Skoda has no such plans. The “Icons Get a Makeover” concepts are designed as creative tributes, celebrating the brand’s history while allowing its designers the freedom to explore new ideas without the limits of production requirements.
2026 Leaf gains driving dynamics expertise drawn from the Z sports car.
New motor mounts and suspension boost comfort while minimizing vibration.
Dual charging ports enhance convenience with a starting MSRP of $29,990.
The latest Leaf has arrived, and Nissan wants drivers to see it as something more than another electric hatchback. It represents years of accumulated know-how from across the brand’s lineup, from mainstream cars to the Z sports car’s precision DNA.
Now, Christian Spencer, Nissan’s senior manager of Marketability and a long-time engineer, explains to Carscoops how the new Leaf embodies what it means to drive a Nissan.
A Familiar Feel or Something New?
Spencer has worked across nearly every segment, including trucks, sedans, SUVs, and sports cars. In his view, making a car drive like a Nissan isn’t about one singular type of experience but rather an attitude that begins at the design phase.
“We have people who stick around this company for a very long time, and they really like it because it’s a hands-on company,” he said. “That doesn’t mean you make a Z drive like a LEAF, or a LEAF drive like a Pathfinder, but you carry the passion through and make sure the customer experience is right.”
Engineers applied Z-inspired strategies like steering precision and controllability to the Leaf, adapting them to an EV platform without overcomplicating the car.
“You can still enjoy driving the car even though it’s not a high-performance sports car,” Spencer said. “We want it to be enthusiastic, fun, and intuitive for the customer.”
Comfort and Quality Above the Segment
The 2026 LEAF’s rear multilink suspension comes from the larger Ariya, reducing impact stiffness by nearly 30%. Redesigned motor mounts soak up vibration, the floor is 80% stiffer, and the doors are better insulated, giving the EV a quieter, more refined ride.
“It really was more luxurious with more refinement than [other options] at the price point it was,” Spencer said. This pursuit of comfort is intentional. The team focused on creating an accessible EV that feels high-quality without overcomplicating features.
“We wanted it to be simple, efficient, and around $30,000, with 300 miles of range,” he explained. “That was how we kept the costs down while still giving the customer a premium-feeling product.”
On top of that, the LEAF integrates both NACS and J1772 charge ports. In other words, owners can use both Tesla Superchargers and traditional home units. Spencer emphasized the importance of prioritizing what the customer actually needs over copying competitors.
“If we were going to bet on how you’re going to charge the car, our solution is probably going to be the best for you today as the customer.”
Now, the question is whether or not these big changes will lead to big sales. What’s unquestionable is that Nissan has taken a bold new tack in the design of this Leaf.
BMW teamed up with Sipaboards to design an electric paddleboard.
The board includes a built-in 300-watt motor for assisted riding.
It offers up to 3.5 hours of battery-assisted water cruising time.
BMW is in the midst of a dramatic overhaul of its line-up, preparing to launch 40 new or heavily updated models over the next two years. Yet, even with that packed schedule, the Bavarian automaker has found time to collaborate with a Slovenian manufacturer of electric stand-up paddleboards, bringing its Neue Klasse design language to a completely different kind of mobility.
While we suspect only a tiny fraction of BMW owners have even the slightest interest in stand-up paddleboarding, the company probably saw its partnership with SipaBoards as an opportunity to extend its design influence beyond the road.
Known simply as the BMW x Sipaboards, the motorized paddleboard is fitted with a compact 300-watt electric motor and a specially developed propeller. It can reach speeds of up to 4 knots, or roughly 7.5 km/h.
This motor does more than just propel the board forward, which can be particularly useful when paddling into a headwind or against a current. It also inflates the board automatically, sparing riders the usual pre-launch workout.
The board, which measures 3.65 meters in length and 0.82 meters in width, weighs just 14.9 kg (32.8 lbs) with the motor and is capable of carrying two people.
Apparently, BMW Group Designworks used Neue Klasse influences when designing the board. However, this doesn’t mean the board has features like the newly-designed lights or signature kidney grilles. Instead, the Neue Klasse influence appears to be limited to the large X motif across the base of the board.
Each board comes with a lightweight carbon fiber paddle with a Bluetooth remote control built directly into it. This allows the rider to choose between different power levels, light effects, and haptic feedback. A smartphone application has also been developed and includes GPS tracking.
Range and Pricing
Initially, the board will be sold exclusively with a pair of 90 Wh battery modules that offer up to 3.5 hours of riding time. Next year, a version with two 180 Wh batteries will become available, allowing for rides lasting as long as seven hours.
The price for this Neue Klasse-inspired board? €3,990 (about $4,633). After all, it’s still a BMW product, so it’s priced like one, even if it trades the highway for open water.
Mercedes says early EV adopters wanted cars that looked different.
The EQS, EQC, and EQE were styled to stand apart from ICE models.
Future EVs like the C-Class will share styling with combustion models.
For years, many legacy carmakers believed the best way to sell electric vehicles was to make them stand apart from their combustion-powered counterparts. Even today, several brands still cling to that idea. But those days are drawing to a close at Mercedes-Benz, where the next generation of electric and ICE models will share a near-identical look.
The German company explains that early EV buyers wanted their cars to look distinct, which led to designs like the EQS, EQC, and EQE appearing radically different from their combustion equivalents such as the GLC and E-Class.
Lessons From the Jellybean Era
Design chief Gorden Wagener defended the “jellybean” or “egg-shaped” aesthetic earlier this year as “purposeful and very progressive,” though he later conceded that the car “was launched ten years too early” and that the marketing approach hadn’t helped.
Now that early adopters have already made the switch to electric, Mercedes thinks it can turn its attention to mainstream buyers who prefer their EVs to blend in rather than stand out.
“Early adopters wanted to be different,” chief technology officer Markus Schäfer told WhichCar? in Australia. “They wanted to show that they were driving an electric car, and now we’re entering the mainstream and mass adoption, and customers don’t want to show that they’re driving an EV. They want the same shape, no matter the drivetrain.”
Same Looks, Different Platforms
This new approach is most evident in the all-electric GLC. Unveiled in full last month, it serves as a replacement to the slow-selling EQC and looks very similar to the ICE variant. Similarly, the new CLA looks the same, regardless of whether it has a battery pack and an electric motor or a combustion engine.
Although its future EVs will continue this trend and share familiar styling with combustion models, Mercedes-Benz continues to insist on using dedicated EV and ICE platforms, rather than developing a single platform that can be used by all of its models, regardless of powertrain.
“In future, the top hat will be the same. The MB.UX intelligence will be the same, but the platform is different,” Schäfer said. Why are we doing this? Eventually you’re compromising when you try to squeeze different drivetrain types into one platform”.
He went on to explain that accommodating everything from six- and eight-cylinder engines to hybrids can eat into battery space, reducing range.
“Fitting both drivetrains to the same platform ultimately ends up with compromise, and we don’t want to offer compromised cars,” he added
The upcoming C-Class will follow the same approach, built on the MB.EA platform with 800-volt technology and a 94-kWh battery pack for the electric version. Teased earlier this year, it’s expected to launch in 2026 as Mercedes’ answer to BMW’s new i3.
On May 6, MIT AgeLab’s Advanced Vehicle Technology (AVT) Consortium, part of the MIT Center for Transportation and Logistics, celebrated 10 years of its global academic-industry collaboration. AVT was founded with the aim of developing new data that contribute to automotive manufacturers, suppliers, and insurers’ real-world understanding of how drivers use and respond to increasingly sophisticated vehicle technologies, such as assistive and automated driving, while accelerating the applied insight needed to advance design and development. The celebration event brought together stakeholders from across the industry for a set of keynote addresses and panel discussions on critical topics significant to the industry and its future, including artificial intelligence, automotive technology, collision repair, consumer behavior, sustainability, vehicle safety policy, and global competitiveness.
Bryan Reimer, founder and co-director of the AVT Consortium, opened the event by remarking that over the decade AVT has collected hundreds of terabytes of data, presented and discussed research with its over 25 member organizations, supported members’ strategic and policy initiatives, published select outcomes, and built AVT into a global influencer with tremendous impact in the automotive industry. He noted that current opportunities and challenges for the industry include distracted driving, a lack of consumer trust and concerns around transparency in assistive and automated driving features, and high consumer expectations for vehicle technology, safety, and affordability. How will industry respond? Major players in attendance weighed in.
In a powerful exchange on vehicle safety regulation, John Bozzella, president and CEO of the Alliance for Automotive Innovation, and Mark Rosekind, former chief safety innovation officer of Zoox, former administrator of the National Highway Traffic Safety Administration, and former member of the National Transportation Safety Board, challenged industry and government to adopt a more strategic, data-driven, and collaborative approach to safety. They asserted that regulation must evolve alongside innovation, not lag behind it by decades. Appealing to the automakers in attendance, Bozzella cited the success of voluntary commitments on automatic emergency braking as a model for future progress. “That’s a way to do something important and impactful ahead of regulation.” They advocated for shared data platforms, anonymous reporting, and a common regulatory vision that sets safety baselines while allowing room for experimentation. The 40,000 annual road fatalities demand urgency — what’s needed is a move away from tactical fixes and toward a systemic safety strategy. “Safety delayed is safety denied,” Rosekind stated. “Tell me how you’re going to improve safety. Let’s be explicit.”
Drawing inspiration from aviation’s exemplary safety record, Kathy Abbott, chief scientific and technical advisor for the Federal Aviation Administration, pointed to a culture of rigorous regulation, continuous improvement, and cross-sectoral data sharing. Aviation’s model, built on highly trained personnel and strict predictability standards, contrasts sharply with the fragmented approach in the automotive industry. The keynote emphasized that a foundation of safety culture — one that recognizes that technological ability alone isn’t justification for deployment — must guide the auto industry forward. Just as aviation doesn’t equate absence of failure with success, vehicle safety must be measured holistically and proactively.
With assistive and automated driving top of mind in the industry, Pete Bigelow of Automotive News offered a pragmatic diagnosis. With companies like Ford and Volkswagen stepping back from full autonomy projects like Argo AI, the industry is now focused on Level 2 and 3 technologies, which refer to assisted and automated driving, respectively. Tesla, GM, and Mercedes are experimenting with subscription models for driver assistance systems, yet consumer confusion remains high. JD Power reports that many drivers do not grasp the differences between L2 and L2+, or whether these technologies offer safety or convenience features. Safety benefits have yet to manifest in reduced traffic deaths, which have risen by 20 percent since 2020. The recurring challenge: L3 systems demand that human drivers take over during technical difficulties, despite driver disengagement being their primary benefit, potentially worsening outcomes. Bigelow cited a quote from Bryan Reimer as one of the best he’s received in his career: “Level 3 systems are an engineer’s dream and a plaintiff attorney’s next yacht,” highlighting the legal and design complexity of systems that demand handoffs between machine and human.
In terms of the impact of AI on the automotive industry, Mauricio Muñoz, senior research engineer at AI Sweden, underscored that despite AI’s transformative potential, the automotive industry cannot rely on general AI megatrends to solve domain-specific challenges. While landmark achievements like AlphaFold demonstrate AI’s prowess, automotive applications require domain expertise, data sovereignty, and targeted collaboration. Energy constraints, data firewalls, and the high costs of AI infrastructure all pose limitations, making it critical that companies fund purpose-driven research that can reduce costs and improve implementation fidelity. Muñoz warned that while excitement abounds — with some predicting artificial superintelligence by 2028 — real progress demands organizational alignment and a deep understanding of the automotive context, not just computational power.
Turning the focus to consumers, a collision repair panel drawing Richard Billyeald from Thatcham Research, Hami Ebrahimi from Caliber Collision, and Mike Nelson from Nelson Law explored the unintended consequences of vehicle technology advances: spiraling repair costs, labor shortages, and a lack of repairability standards. Panelists warned that even minor repairs for advanced vehicles now require costly and complex sensor recalibrations — compounded by inconsistent manufacturer guidance and no clear consumer alerts when systems are out of calibration. The panel called for greater standardization, consumer education, and repair-friendly design. As insurance premiums climb and more people forgo insurance claims, the lack of coordination between automakers, regulators, and service providers threatens consumer safety and undermines trust. The group warned that until Level 2 systems function reliably and affordably, moving toward Level 3 autonomy is premature and risky.
While the repair panel emphasized today’s urgent challenges, other speakers looked to the future. Honda’s Ryan Harty, for example, highlighted the company’s aggressive push toward sustainability and safety. Honda aims for zero environmental impact and zero traffic fatalities, with plans to be 100 percent electric by 2040 and to lead in energy storage and clean power integration. The company has developed tools to coach young drivers and is investing in charging infrastructure, grid-aware battery usage, and green hydrogen storage. “What consumers buy in the market dictates what the manufacturers make,” Harty noted, underscoring the importance of aligning product strategy with user demand and environmental responsibility. He stressed that manufacturers can only decarbonize as fast as the industry allows, and emphasized the need to shift from cost-based to life-cycle-based product strategies.
Finally, a panel involving Laura Chace of ITS America, Jon Demerly of Qualcomm, Brad Stertz of Audi/VW Group, and Anant Thaker of Aptiv covered the near-, mid-, and long-term future of vehicle technology. Panelists emphasized that consumer expectations, infrastructure investment, and regulatory modernization must evolve together. Despite record bicycle fatality rates and persistent distracted driving, features like school bus detection and stop sign alerts remain underutilized due to skepticism and cost. Panelists stressed that we must design systems for proactive safety rather than reactive response. The slow integration of digital infrastructure — sensors, edge computing, data analytics — stems not only from technical hurdles, but procurement and policy challenges as well.
Reimer concluded the event by urging industry leaders to re-center the consumer in all conversations — from affordability to maintenance and repair. With the rising costs of ownership, growing gaps in trust in technology, and misalignment between innovation and consumer value, the future of mobility depends on rebuilding trust and reshaping industry economics. He called for global collaboration, greater standardization, and transparent innovation that consumers can understand and afford. He highlighted that global competitiveness and public safety both hang in the balance. As Reimer noted, “success will come through partnerships” — between industry, academia, and government — that work toward shared investment, cultural change, and a collective willingness to prioritize the public good.
Across a career’s worth of pioneering product designs, Doug Field’s work has shaped the experience of anyone who’s ever used a MacBook Air, ridden a Segway, or driven a Tesla Model 3.
But his newest project is his most ambitious yet: reinventing the Ford automobile, one of the past century’s most iconic pieces of technology.
As Ford’s chief electric vehicle (EV), digital, and design officer, Field is tasked with leading the development of the company’s electric vehicles, while making new software platforms central to all Ford models.
To bring Ford Motor Co. into that digital and electric future, Field effectively has to lead a fast-moving startup inside the legacy carmaker. “It is incredibly hard, figuring out how to do ‘startups’ within large organizations,” he concedes.
If anyone can pull it off, it’s likely to be Field. Ever since his time in MIT’s Leaders for Global Operations (then known as “Leaders in Manufacturing”) program studying organizational behavior and strategy, Field has been fixated on creating the conditions that foster innovation.
“The natural state of an organization is to make it harder and harder to do those things: to innovate, to have small teams, to go against the grain,” he says. To overcome those forces, Field has become a master practitioner of the art of curating diverse, talented teams and helping them flourish inside of big, complex companies.
“It’s one thing to make a creative environment where you can come up with big ideas,” he says. “It’s another to create an execution-focused environment to crank things out. I became intrigued with, and have been for the rest of my career, this question of how can you have both work together?”
Three decades after his first stint as a development engineer at Ford Motor Co., Field now has a chance to marry the manufacturing muscle of Ford with the bold approach that helped him rethink Apple’s laptops and craft Tesla’s Model 3 sedan. His task is nothing less than rethinking how cars are made and operated, from the bottom up.
“If it’s only creative or execution, you’re not going to change the world,” he says. “If you want to have a huge impact, you need people to change the course you’re on, and you need people to build it.”
A passion for design
From a young age, Field had a fascination with automobiles. “I was definitely into cars and transportation more generally,” he says. “I thought of cars as the place where technology and art and human design came together — cars were where all my interests intersected.”
With a mother who was an artist and musician and an engineer father, Field credits his parents’ influence for his lifelong interest in both the aesthetic and technical elements of product design. “I think that’s why I’m drawn to autos — there’s very much an aesthetic aspect to the product,” he says.
After earning a degree in mechanical engineering from Purdue University, Field took a job at Ford in 1987. The big Detroit automakers of that era excelled at mass-producing cars, but weren’t necessarily set up to encourage or reward innovative thinking. Field chafed at the “overstructured and bureaucratic” operational culture he encountered.
The experience was frustrating at times, but also valuable and clarifying. He realized that he “wanted to work with fast-moving, technology-based businesses.”
“My interest in advancing technical problem-solving didn’t have a place in the auto industry” at the time, he says. “I knew I wanted to work with passionate people and create something that didn’t exist, in an environment where talent and innovation were prized, where irreverence was an asset and not a liability. When I read about Silicon Valley, I loved the way they talked about things.”
During that time, Field took two years off to enroll in MIT’s LGO program, where he deepened his technical skills and encountered ideas about manufacturing processes and team-driven innovation that would serve him well in the years ahead.
“Some of core skill sets that I developed there were really, really important,” he says, “in the context of production lines and production processes.” He studied systems engineering and the use of Monte Carlo simulations to model complex manufacturing environments. During his internship with aerospace manufacturer Pratt & Whitney, he worked on automated design in computer-aided design (CAD) systems, long before those techniques became standard practice.
Another powerful tool he picked up was the science of probability and statistics, under the tutelage of MIT Professor Alvin Drake in his legendary course 6.041/6.431 (Probabilistic Systems Analysis). Field would go on to apply those insights not only to production processes, but also to characterizing variability in people’s aptitudes, working styles, and talents, in the service of building better, more innovative teams. And studying organizational strategy catalyzed his career-long interest in “ways to look at innovation as an outcome, rather than a random spark of genius.”
“So many things I was lucky to be exposed to at MIT,” Field says, were “all building blocks, pieces of the puzzle, that helped me navigate through difficult situations later on.”
Learning while leading
After leaving Ford in 1993, Field worked at Johnson and Johnson Medical for three years in process development. There, he met Segway inventor Dean Kamen, who was working on a project called the iBOT, a gyroscopic powered wheelchair that could climb stairs.
When Kamen spun off Segway to develop a new personal mobility device using the same technology, Field became his first hire. He spent nearly a decade as the firm’s chief technology officer.
At Segway, Field’s interests in vehicles, technology, innovation, process, and human-centered design all came together.
“When I think about working now on electric cars, it was a real gift,” he says. The problems they tackled prefigured the ones he would grapple with later at Tesla and Ford. “Segway was very much a precursor to a modern EV. Completely software controlled, with higher-voltage batteries, redundant systems, traction control, brushless DC motors — it was basically a miniature Tesla in the year 2000.”
At Segway, Field assembled an “amazing” team of engineers and designers who were as passionate as he was about pushing the envelope. “Segway was the first place I was able to hand-pick every single person I worked with, define the culture, and define the mission.”
As he grew into this leadership role, he became equally engrossed with cracking another puzzle: “How do you prize people who don’t fit in?”
“Such a fundamental part of the fabric of Silicon Valley is the love of embracing talent over a traditional organization’s ways of measuring people,” he says. “If you want to innovate, you need to learn how to manage neurodivergence and a very different set of personalities than the people you find in large corporations.”
Field still keeps the base housing of a Segway in his office, as a reminder of what those kinds of teams — along with obsessive attention to detail — can achieve.
Before joining Apple in 2008, he showed that component, with its clean lines and every minuscule part in its place in one unified package, to his prospective new colleagues. “They were like, “OK, you’re one of us,’” he recalls.
He soon became vice president of hardware development for all Mac computers, leading the teams behind the MacBook Air and MacBook Pro and eventually overseeing more than 2,000 employees. “Making things really simple and really elegant, thinking about the product as an integrated whole, that really took me into Apple.”
The challenge of giving the MacBook Air its signature sleek and light profile is an example.
“The MacBook Air was the first high-volume consumer electronic product built out of a CNC-machined enclosure,” says Field. He worked with industrial design and technology teams to devise a way to make the laptop from one solid piece of aluminum and jettison two-thirds of the parts found in the iMac. “We had material cut away so that every single screw and piece of electronics sat down into it an integrated way. That’s how we got the product so small and slim.”
“When I interviewed with Jony Ive” — Apple’s legendary chief design officer — “he said your ability to zoom out and zoom in was the number one most important ability as a leader at Apple.” That meant zooming out to think about “the entire ethos of this product, and the way it will affect the world” and zooming all the way back in to obsess over, say, the physical shape of the laptop itself and what it feels like in a user’s hands.
“That thread of attention to detail, passion for product, design plus technology rolled directly into what I was doing at Tesla,” he says. When Field joined Tesla in 2013, he was drawn to the way the brash startup upended the approach to making cars. “Tesla was integrating digital technology into cars in a way nobody else was. They said, ‘We’re not a car company in Silicon Valley, we’re a Silicon Valley company and we happen to make cars.’”
Field assembled and led the team that produced the Model 3 sedan, Tesla’s most affordable vehicle, designed to have mass-market appeal.
That experience only reinforced the importance, and power, of zooming in and out as a designer — in a way that encompasses the bigger human resources picture.
“You have to have a broad sense of what you’re trying to accomplish and help people in the organization understand what it means to them,” he says. “You have to go across and understand operations enough to glue all of those (things) together — while still being great at and focused on something very, very deeply. That’s T-shaped leadership.”
He credits his time at LGO with providing the foundation for the “T-shaped leadership” he practices.
“An education like the one I got at MIT allowed me to keep moving that ‘T’, to focus really deep, learn a ton, teach as much as I can, and after something gets more mature, pull out and bed down into other areas where the organization needs to grow or where there’s a crisis.”
The power of marrying scale to a “startup mentality”
In 2018, Field returned to Apple as a vice president for special projects. “I left Tesla after Model 3 and Y started to ramp, as there were people better than me to run high-volume manufacturing,” he says. “I went back to Apple hoping what Tesla had learned would motivate Apple to get into a different market.”
That market was his early love: cars. Field quietly led a project to develop an electric vehicle at Apple for three years.
Then Ford CEO Jim Farley came calling. He persuaded Field to return to Ford in late 2021, partly by demonstrating how much things had changed since his first stint as the carmaker.
“Two things came through loud and clear,” Field says. “One was humility. ‘Our success is not assured.’” That attitude was strikingly different from Field’s early experience in Detroit, encountering managers who were resistant to change. “The other thing was urgency. Jim and Bill Ford said the exact same thing to me: ‘We have four or five years to completely remake this company.’”
“I said, ‘OK, if the top of company really believes that, then the auto industry may be ready for what I hope to offer.’”
So far, Field is energized and encouraged by the appetite for reinvention he’s encountered this time around at Ford.
“If you can combine what Ford does really well with what a Tesla or Rivian can do well, this is something to be reckoned with,” says Field. “Skunk works have become one of the fundamental tools of my career,” he says, using an industry term that describes a project pursued by a small, autonomous group of people within a larger organization.
Ford has been developing a new, lower-cost, software-enabled EV platform — running all of the car’s sensors and components from a central digital operating system — with a “skunk works” team for the past two years. The company plans to build new sedans, SUVs, and small pickups based on this new platform.
With other legacy carmakers like Volvo racing into the electric future and fierce competition from EV leaders Tesla and Rivian, Field and his colleagues have their work cut out for them.
If he succeeds, leveraging his decades of learning and leading from LGO to Silicon Valley, then his latest chapter could transform the way we all drive — and secure a spot for Ford at the front of the electric vehicle pack in the process.
“I’ve been lucky to feel over and over that what I’m doing right now — they are going to write a book about it,” say Field. “This is a big deal, for Ford and the U.S. auto industry, and for American industry, actually.”
“So many things I was lucky to be exposed to at MIT,” Doug Field says, were “all building blocks, pieces of the puzzle, that helped me navigate through difficult situations later on.”
Car design is an iterative and proprietary process. Carmakers can spend several years on the design phase for a car, tweaking 3D forms in simulations before building out the most promising designs for physical testing. The details and specs of these tests, including the aerodynamics of a given car design, are typically not made public. Significant advances in performance, such as in fuel efficiency or electric vehicle range, can therefore be slow and siloed from company to company.
MIT engineers say that the search for better car designs can speed up exponentially with the use of generative artificial intelligence tools that can plow through huge amounts of data in seconds and find connections to generate a novel design. While such AI tools exist, the data they would need to learn from have not been available, at least in any sort of accessible, centralized form.
But now, the engineers have made just such a dataset available to the public for the first time. Dubbed DrivAerNet++, the dataset encompasses more than 8,000 car designs, which the engineers generated based on the most common types of cars in the world today. Each design is represented in 3D form and includes information on the car’s aerodynamics — the way air would flow around a given design, based on simulations of fluid dynamics that the group carried out for each design.
Each of the dataset’s 8,000 designs is available in several representations, such as mesh, point cloud, or a simple list of the design’s parameters and dimensions. As such, the dataset can be used by different AI models that are tuned to process data in a particular modality.
DrivAerNet++ is the largest open-source dataset for car aerodynamics that has been developed to date. The engineers envision it being used as an extensive library of realistic car designs, with detailed aerodynamics data that can be used to quickly train any AI model. These models can then just as quickly generate novel designs that could potentially lead to more fuel-efficient cars and electric vehicles with longer range, in a fraction of the time that it takes the automotive industry today.
“This dataset lays the foundation for the next generation of AI applications in engineering, promoting efficient design processes, cutting R&D costs, and driving advancements toward a more sustainable automotive future,” says Mohamed Elrefaie, a mechanical engineering graduate student at MIT.
Elrefaie and his colleagues will present a paper detailing the new dataset, and AI methods that could be applied to it, at the NeurIPS conference in December. His co-authors are Faez Ahmed, assistant professor of mechanical engineering at MIT, along with Angela Dai, associate professor of computer science at the Technical University of Munich, and Florin Marar of BETA CAE Systems.
Filling the data gap
Ahmed leads the Design Computation and Digital Engineering Lab (DeCoDE) at MIT, where his group explores ways in which AI and machine-learning tools can be used to enhance the design of complex engineering systems and products, including car technology.
“Often when designing a car, the forward process is so expensive that manufacturers can only tweak a car a little bit from one version to the next,” Ahmed says. “But if you have larger datasets where you know the performance of each design, now you can train machine-learning models to iterate fast so you are more likely to get a better design.”
And speed, particularly for advancing car technology, is particularly pressing now.
“This is the best time for accelerating car innovations, as automobiles are one of the largest polluters in the world, and the faster we can shave off that contribution, the more we can help the climate,” Elrefaie says.
In looking at the process of new car design, the researchers found that, while there are AI models that could crank through many car designs to generate optimal designs, the car data that is actually available is limited. Some researchers had previously assembled small datasets of simulated car designs, while car manufacturers rarely release the specs of the actual designs they explore, test, and ultimately manufacture.
The team sought to fill the data gap, particularly with respect to a car’s aerodynamics, which plays a key role in setting the range of an electric vehicle, and the fuel efficiency of an internal combustion engine. The challenge, they realized, was in assembling a dataset of thousands of car designs, each of which is physically accurate in their function and form, without the benefit of physically testing and measuring their performance.
To build a dataset of car designs with physically accurate representations of their aerodynamics, the researchers started with several baseline 3D models that were provided by Audi and BMW in 2014. These models represent three major categories of passenger cars: fastback (sedans with a sloped back end), notchback (sedans or coupes with a slight dip in their rear profile) and estateback (such as station wagons with more blunt, flat backs). The baseline models are thought to bridge the gap between simple designs and more complicated proprietary designs, and have been used by other groups as a starting point for exploring new car designs.
Library of cars
In their new study, the team applied a morphing operation to each of the baseline car models. This operation systematically made a slight change to each of 26 parameters in a given car design, such as its length, underbody features, windshield slope, and wheel tread, which it then labeled as a distinct car design, which was then added to the growing dataset. Meanwhile, the team ran an optimization algorithm to ensure that each new design was indeed distinct, and not a copy of an already-generated design. They then translated each 3D design into different modalities, such that a given design can be represented as a mesh, a point cloud, or a list of dimensions and specs.
The researchers also ran complex, computational fluid dynamics simulations to calculate how air would flow around each generated car design. In the end, this effort produced more than 8,000 distinct, physically accurate 3D car forms, encompassing the most common types of passenger cars on the road today.
To produce this comprehensive dataset, the researchers spent over 3 million CPU hours using the MIT SuperCloud, and generated 39 terabytes of data. (For comparison, it’s estimated that the entire printed collection of the Library of Congress would amount to about 10 terabytes of data.)
The engineers say that researchers can now use the dataset to train a particular AI model. For instance, an AI model could be trained on a part of the dataset to learn car configurations that have certain desirable aerodynamics. Within seconds, the model could then generate a new car design with optimized aerodynamics, based on what it has learned from the dataset’s thousands of physically accurate designs.
The researchers say the dataset could also be used for the inverse goal. For instance, after training an AI model on the dataset, designers could feed the model a specific car design and have it quickly estimate the design’s aerodynamics, which can then be used to compute the car’s potential fuel efficiency or electric range — all without carrying out expensive building and testing of a physical car.
“What this dataset allows you to do is train generative AI models to do things in seconds rather than hours,” Ahmed says. “These models can help lower fuel consumption for internal combustion vehicles and increase the range of electric cars — ultimately paving the way for more sustainable, environmentally friendly vehicles.”
“The dataset is very comprehensive and consists of a diverse set of modalities that are valuable to understand both styling and performance,” says Yanxia Zhang, a senior machine learning research scientist at Toyota Research Institute, who was not involved in the study.
This work was supported, in part, by the German Academic Exchange Service and the Department of Mechanical Engineering at MIT.
In a new dataset that includes more than 8,000 car designs, MIT engineers simulated the aerodynamics for a given car shape, which they represent in various modalities, including “surface fields.”
As a major contributor to global carbon dioxide (CO2) emissions, the transportation sector has immense potential to advance decarbonization. However, a zero-emissions global supply chain requires re-imagining reliance on a heavy-duty trucking industry that emits 810,000 tons of CO2, or 6 percent of the United States’ greenhouse gas emissions, and consumes 29 billion gallons of diesel annually in the U.S. alone.
A new study by MIT researchers, presented at the recent American Society of Mechanical Engineers 2024 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, quantifies the impact of a zero-emission truck’s design range on its energy storage requirements and operational revenue. The multivariable model outlined in the paper allows fleet owners and operators to better understand the design choices that impact the economic feasibility of battery-electric and hydrogen fuel cell heavy-duty trucks for commercial application, equipping stakeholders to make informed fleet transition decisions.
“The whole issue [of decarbonizing trucking] is like a very big, messy pie. One of the things we can do, from an academic standpoint, is quantify some of those pieces of pie with modeling, based on information and experience we’ve learned from industry stakeholders,” says ZhiYi Liang, PhD student on the renewable hydrogen team at the MIT K. Lisa Yang Global Engineering and Research Center (GEAR) and lead author of the study. Co-authored by Bryony DuPont, visiting scholar at GEAR, and Amos Winter, the Germeshausen Professor in the MIT Department of Mechanical Engineering, the paper elucidates operational and socioeconomic factors that need to be considered in efforts to decarbonize heavy-duty vehicles (HDVs).
Operational and infrastructure challenges
The team’s model shows that a technical challenge lies in the amount of energy that needs to be stored on the truck to meet the range and towing performance needs of commercial trucking applications. Due to the high energy density and low cost of diesel, existing diesel drivetrains remain more competitive than alternative lithium battery-electric vehicle (Li-BEV) and hydrogen fuel-cell-electric vehicle (H2 FCEV) drivetrains. Although Li-BEV drivetrains have the highest energy efficiency of all three, they are limited to short-to-medium range routes (under 500 miles) with low freight capacity, due to the weight and volume of the onboard energy storage needed. In addition, the authors note that existing electric grid infrastructure will need significant upgrades to support large-scale deployment of Li-BEV HDVs.
While the hydrogen-powered drivetrain has a significant weight advantage that enables higher cargo capacity and routes over 750 miles, the current state of hydrogen fuel networks limits economic viability, especially once operational cost and projected revenue are taken into account. Deployment will most likely require government intervention in the form of incentives and subsidies to reduce the price of hydrogen by more than half, as well as continued investment by corporations to ensure a stable supply. Also, as H2-FCEVs are still a relatively new technology, the ongoing design of conformal onboard hydrogen storage systems — one of which is the subject of Liang’s PhD — is crucial to successful adoption into the HDV market.
The current efficiency of diesel systems is a result of technological developments and manufacturing processes established over many decades, a precedent that suggests similar strides can be made with alternative drivetrains. However, interactions with fleet owners, automotive manufacturers, and refueling network providers reveal another major hurdle in the way that each “slice of the pie” is interrelated — issues must be addressed simultaneously because of how they affect each other, from renewable fuel infrastructure to technological readiness and capital cost of new fleets, among other considerations. And first steps into an uncertain future, where no one sector is fully in control of potential outcomes, is inherently risky.
“Besides infrastructure limitations, we only have prototypes [of alternative HDVs] for fleet operator use, so the cost of procuring them is high, which means there isn’t demand for automakers to build manufacturing lines up to a scale that would make them economical to produce,” says Liang, describing just one step of a vicious cycle that is difficult to disrupt, especially for industry stakeholders trying to be competitive in a free market.
Quantifying a path to feasibility
“Folks in the industry know that some kind of energy transition needs to happen, but they may not necessarily know for certain what the most viable path forward is,” says Liang. Although there is no singular avenue to zero emissions, the new model provides a way to further quantify and assess at least one slice of pie to aid decision-making.
Other MIT-led efforts aimed at helping industry stakeholders navigate decarbonization include an interactive mapping tool developed by Danika MacDonell, Impact Fellow at the MIT Climate and Sustainability Consortium (MCSC); alongside Florian Allroggen, executive director of MITs Zero Impact Aviation Alliance; and undergraduate researchers Micah Borrero, Helena De Figueiredo Valente, and Brooke Bao. The MCSC’s Geospatial Decision Support Tool supports strategic decision-making for fleet operators by allowing them to visualize regional freight flow densities, costs, emissions, planned and available infrastructure, and relevant regulations and incentives by region.
While current limitations reveal the need for joint problem-solving across sectors, the authors believe that stakeholders are motivated and ready to tackle climate problems together. Once-competing businesses already appear to be embracing a culture shift toward collaboration, with the recent agreement between General Motors and Hyundai to explore “future collaboration across key strategic areas,” including clean energy.
Liang believes that transitioning the transportation sector to zero emissions is just one part of an “energy revolution” that will require all sectors to work together, because “everything is connected. In order for the whole thing to make sense, we need to consider ourselves part of that pie, and the entire system needs to change,” says Liang. “You can’t make a revolution succeed by yourself.”
The authors acknowledge the MIT Climate and Sustainability Consortium for connecting them with industry members in the HDV ecosystem; and the MIT K. Lisa Yang Global Engineering and Research Center and MIT Morningside Academy for Design for financial support.
A new study by MIT researchers quantifies the impact of a zero-emission truck’s design range on its energy storage requirements and operational revenue.
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