GM’s Push to Build Trust in Eyes-Off Driving
For John Kaychi, Senior Group Product Manager for Automated Driving at General Motors, the future of mobility depends on more than sophisticated software, advanced sensors and artificial intelligence. It also depends on something much harder to engineer: customer trust.
As the automotive industry moves closer to higher levels of automated driving, Kaychi believes technology will only achieve its full potential when people feel comfortable relying on it. At GM, he leads a product team focused on eyes-off driving and, just as importantly, on how customers experience the technology in their everyday lives.
GM plans to take another major step in automated driving in 2028, beginning with the Cadillac ESCALADE IQ. The planned introduction represents an important transition for the company and the broader automated-driving industry, moving advanced capabilities beyond demonstrations and controlled environments and toward a production vehicle designed for everyday customers.
“You can have the best technology in the world,” Kaychi says, “but if customers don’t trust it, it won’t stick.”
That belief has become a central part of his approach to automated driving. His career has taken him through startups, autonomous vehicle development and robotaxi operations before bringing him to GM. Those experiences have given him a broad perspective on how the industry has evolved and what it will take to make automated driving a meaningful part of everyday transportation.
From Demonstrations to Everyday Driving
Kaychi views the development of autonomous vehicles as a progression through several important stages.
The first major wave was driven by ridesharing, which changed the way consumers thought about transportation and helped establish new expectations around mobility. The next stage came through robotaxis, which provided companies with opportunities to deploy autonomous vehicles in real-world environments and learn how automated systems respond to unpredictable conditions.
The next major test, according to Kaychi, will come through retail vehicles.
Bringing automated driving technology directly to consumers creates a fundamentally different challenge. A demonstration can prove that a system is technically capable of completing a particular task. A retail product, however, must perform consistently for customers over thousands of miles, different road conditions and countless everyday scenarios.
“That’s the edge we’re standing at today,” Kaychi says.
He believes the technology is now better understood, while many of the underlying hardware components are becoming increasingly standardized. At the same time, the retail automotive market provides an opportunity to bring automated driving to a much larger audience.
True autonomy has not yet become a universal reality, but Kaychi believes GM is well positioned to play an important role in the next phase of the industry.
The challenge is no longer simply proving that autonomous technology can work. It is about developing systems that can operate safely, reliably and predictably while giving customers a compelling reason to use them.
The Importance of Data
Moving from autonomous driving demonstrations to a mass-produced consumer product requires enormous amounts of testing and validation.
Real-world roads are unpredictable. Weather can change rapidly. Construction can alter familiar routes. Road markings can disappear. Other drivers can behave unexpectedly. Pedestrians and cyclists can create situations that are difficult to anticipate. These examples represent only a small part of what engineers refer to as the “long tail” of driving scenarios.
To address these challenges, GM is building its development and validation strategy around multiple sources of data.
The first source is the company’s existing fleet of production vehicles. Vehicles already being driven by customers can generate valuable real-world information and fleet telemetry, allowing engineers to better understand how vehicles encounter different environments and road conditions.
The second source comes from next-generation development vehicles. These vehicles are designed to collect highly detailed sensor information that can support the development and evaluation of future automated-driving systems.
The third source is synthetic data and high-fidelity simulation. Virtual environments allow engineers to reproduce difficult or rare situations that may not occur frequently enough in real-world driving to provide sufficient testing opportunities.
Together, these three sources create a continuous validation cycle.
Real-world vehicle information can help identify situations that need further investigation. Development vehicles can provide deeper information about those situations, while simulation can reproduce them repeatedly under controlled conditions. Engineers can then use the resulting insights to refine the technology and evaluate its performance again.
The approach is particularly important when dealing with unusual or difficult scenarios.
Retail vehicle data is collected with safeguards intended to protect customer privacy, while development efforts focus on collecting information in a disciplined and prioritized way. Rather than attempting to solve every possible driving scenario simultaneously, teams can concentrate on operational areas where improvements can deliver the greatest customer benefit.
Technology and the Human Experience
For Kaychi, automated driving is not solely an engineering problem.
A system can technically perform its intended driving functions while still creating an uncomfortable experience for the person inside the vehicle. Sudden movements, uncertain behavior or a lack of predictability can undermine confidence even if the vehicle technically remains within its operating parameters.
That makes the human experience an essential part of product development.
“It’s not just about how the system drives,” Kaychi emphasizes. “It’s about how it makes the driver feel. And we’re building for both.”
This philosophy reflects a broader challenge facing the automated-driving industry. Customers must understand what the technology can do, where it can operate and how it will behave. They also need confidence that the system has been tested thoroughly enough to justify placing greater responsibility in its hands.
Trust, therefore, cannot simply be added through marketing. It has to be earned through consistent performance.
Lessons From Zoox
Kaychi’s perspective has been shaped by his previous experience working at Zoox, where he helped launch the company’s first employee ridesharing service.
The experience gave him an opportunity to observe autonomous vehicles operating in one of the most demanding urban environments in the United States: San Francisco.
The city presents a difficult combination of steep streets, blind crests, dense traffic and complicated road layouts. Areas around landmarks such as Coit Tower and Lombard Street can challenge even experienced human drivers.
Operating autonomous vehicles in that environment provided Kaychi with a direct look at how people respond when encountering the technology for the first time.
“Getting to see the technology through the eyes of so many people who hadn’t experienced it before reminded me how groundbreaking this technology is,” he says.
The experience also demonstrated how close autonomous driving technology could be to becoming a practical reality while highlighting the complexity involved in operating safely in the real world.
For Kaychi, those lessons continue to influence his work at GM. The objective is not simply to demonstrate what automated vehicles can do but to determine how those capabilities can be developed into a scalable consumer product.
Bringing Startup Speed to Automotive Scale
Working at a startup and working for one of the world’s largest automakers require different approaches.
Startups often operate with a strong sense of urgency. Teams can move quickly, test ideas and adapt rapidly. Automotive manufacturers, meanwhile, have to consider production quality, regulatory requirements, safety standards, manufacturing consistency and the expectations associated with a major global brand.
At GM, Kaychi sees an opportunity to combine the best aspects of both environments.
The company can bring the urgency and innovation associated with autonomous-driving startups while applying the discipline required to develop technology for millions of customers.
“There’s a different kind of wisdom required when deploying at automotive scale,” Kaychi notes. “Every decision has to reinforce trust and quality. You don’t just chase speed—you protect the brand.”
That balance will be critical as GM prepares to introduce future automated-driving capabilities to retail customers.
Building on Super Cruise and Cruise
GM is not starting from scratch.
The company already has extensive experience with advanced driver assistance through Super Cruise, which has demonstrated the ability to bring sophisticated driving technology to production vehicles and accumulate millions of customer miles.
At the same time, Cruise has contributed expertise in autonomous-driving development, artificial intelligence and complex testing environments.
Bringing these capabilities together gives GM two complementary foundations for its next stage of automated driving.
Super Cruise provides experience with deploying technology to consumers at automotive scale. Cruise contributes experience in developing autonomous-driving systems and testing them against complex real-world scenarios.
The combination is intended to support GM’s effort to validate and refine the capabilities needed for future eyes-off driving.
Rather than attempting to introduce every capability at once, GM is taking a domain-by-domain approach. Each capability must be evaluated against real-world conditions before the company expands the technology into additional operating environments.
This gradual strategy is designed to ensure that growth in capability does not come at the expense of customer confidence.
The Real Value: Giving Time Back
Ultimately, Kaychi believes the most compelling benefit of eyes-off driving is not the technology itself.
It is time.
For many people, driving is an unavoidable part of everyday life. Commuting, traveling to appointments, picking up children or completing routine errands can consume significant portions of a person’s day.
Eyes-off driving could change the way people experience that time.
“Eyes-off driving fundamentally changes what routine travel feels like,” Kaychi explains. “It transforms time spent behind the wheel into personal bandwidth—giving people space to work, think, or simply relax.”
That potential is one of the strongest motivations behind GM’s work.
If automated driving can safely handle appropriate portions of a journey, passengers could potentially use that time in ways that were previously impossible while driving. The vehicle could become more than transportation; it could become an extension of a person’s daily living and working environment.
However, reaching that point requires more than technological capability. Customers must believe the system will behave as expected every time they use it.
That is why trust remains at the center of GM’s automated-driving strategy.
A New Chapter for Automated Mobility
The automotive industry has spent years demonstrating the potential of autonomous driving. The next challenge is turning that potential into products that ordinary consumers can use and understand.
For GM and Kaychi, that means combining data, artificial intelligence, real-world testing, simulation, production expertise and customer-focused product development.
The planned 2028 introduction of eyes-off driving beginning with the Cadillac ESCALADE IQ could represent an important milestone in that journey.
Success will ultimately be measured not only by how advanced the technology is, but by how naturally customers incorporate it into their lives.
The path toward automated driving may have begun with prototypes and robotaxis, but the next chapter will increasingly be written in driveways, highways, commutes and family road trips.
For Kaychi, earning customer trust is the bridge between technological possibility and everyday adoption. And as GM works toward bringing eyes-off driving to retail vehicles, that bridge may prove just as important as the technology itself.
Source Link:https://news.gm.com/
