The automotive industry is being rapidly transformed. Artificial intelligence and machine learning are driving change within the industry to improve user experience.
Maria Uvarova, product software manager at Stellantis, says automakers have always been learning from customer feedback. The trouble is that the customer feedback loop was never fast enough. Automakers have been reliant on sporadic survey and sales results data. Modernization with connected vehicles means that substantial and unbiased data can be used to make it plain about how customers are really using their vehicles, what they enjoy and what disappoints or frustrates them. “I wouldn't say that the connectivity made us completely change the approach but it certainly made us more attentive to the customer needs and allowed us to react to the changes in such needs a lot faster than before,” she suggests.
Actionable insights
Lukas Trampert, product line manager for Daimler Truck North America’s connectivity services, offers a commercial vehicle perspective and says connectivity offers truck owners the ability to consume vehicle data in way that offers them actionable insights. The data insights are vital to ensuring that commercial vehicles are properly maintained to maximize uptime, to address safety critical events and to optimize fleet operations.
He says the other important aspect is the provision of remote updates from each vehicle’s electronic control units (ECUs). This again is about reducing downtime to keep the trucks on the road. This includes the deployment of telematics devices, which Daimler Trucks began to do in 2017.
His colleague Vicente Torres, manager of the vehicle health and Detroit connect portal, says one of the key differentiators between the commercial and passenger vehicles sectors is in the type of solutions provided for each of them. In the passenger vehicle sector, the solutions are very much consumer oriented, focusing on both the driver and the car’s passengers.
Beyond the driver
Yet, in the commercial vehicle sector, the solutions go way beyond the driver as it is very much a business-to-business space. So, unlike in the car market, the driver often isn’t the primary user. In fact, they are often fleet managers and service managers and so the solutions must be tailored to more people than in the significantly larger consumer vehicle market.
In trucking, the focus is on suites of products for the logistics industry. Data platforms are often available where they can provide over-the-air updates remotely, including of firmware. There are also safety services, such as video capture and analytics, to improve both the safety and efficiency of their operations.
Product development
Uvarova adds that there is no need to start from scratch these days. Data insights can be used to, for example, develop a voice assistant for vehicles in a way that it will address customer demands much better than previously. With connectivity automakers have been able to collate more customer and vehicle data, which enables them to analyze customer behavior.
She elaborates: “We can test the prototype version of a new voice assistant with real customers, we can also analyze the data from an old version of the voice assistant in our existing car park. With all this data, we can be a lot more precise in our design of the new voice product. We can focus specifically on optimizing the voice queries that customers use more frequently and get them right instead of spreading efforts evenly on all types of queries (with probably mediocre results).”
Real-time information
In the commercial vehicle sector, Torres says fleets are demanding real-time information to mitigate safety issue, or to reduce unplanned maintenance events. He sees connected vehicles evolving over the next decade, with more intelligent solutions being added across the entire supply chain. Over that period, he foresees an evolution in connectivity through direct data feeds and APIs. This is because customers are wanting data to fully customize their alerts, and to tailor their operations. This will entail a switch from consuming data from a portal to requiring data to be fed directly to everyone concerned within the fleet operations.
However, he says trucks are getting smarter and so are customers. They have the ability to build their own solutions. Trampert explains: “Large customers have the resources to build proprietary solutions, while smaller ones are looking for out-of-the-box solutions. They are looking for data insights which are aggregated with proprietary data. You often need both to make a difference. Smaller fleets, however, often can’t afford. This is the big difference for commercial trucking, and our job is to support our customers to the best of our ability.”
Torres adds that in the consumer space, there is a need for a different skill set, differentiating primarily with luxury vehicles. “Every automaker has to consider the passenger car world, but our job is to help our commercial customers to run their businesses,” he says.
Overwhelming options
Yet, Uvarova warns that customers in the consumer market face being overwhelmed by the increasing number of choices available to them. “There are too many options, too many choices, too many things to be done in a limited time,” she suggests before advising the automotive industry to focus on simplifying the lives of its customers inasmuch as possible.
She highlights that customers think of their cars as being their third living space after home and work. So, their vehicles have to be both comfortable and practical. Automakers need to optimize vehicle interiors, provide an increasing amount of infotainment and connectivity options. They should also allow them to personalize the experience but in a way that is not overwhelming.
“The overall personalization trend will only grow stronger over the years, with the new artificial intelligence and machine learning technologies that enable the car to learn from customer behavior,” she comments before suggesting that customer want to get the time back. This means that connected and autonomous driving will become more sophisticated over the years to come. She also predicts a rise in ride-sharing and electric vehicles as not everyone will want or need a car all the time and some people may see these options as a means of becoming more environmentally sustainable.
Digital ecosystems
In the meantime, she says a digital ecosystem has been established. Automakers, she explains, see the benefits of building a mobility ecosystem to meet customers’ demand. This development also permits them to branch out to other business models as part of a mobility tech business, which includes the sharing economy, subscriptions for connected services, shopping from within the car, auto insurance that uses telematics data and much more besides.
Trampert adds that connected mobility is developing rapidly in the commercial vehicle sector too. In trucking, it involves open and closed digital ecosystems. This may involve vehicle maker’s offering their own services based on a proprietary cloud-to-cloud ecosystem, or by partnering with a third-party platform. The cornerstone of these services is data, which will need to be tightly integrated as that’s the future of mobility in his view. It won’t be just about the truck. It will also be about the trailer, the traction management, the infrastructure, and all the vital components that keep a fleet running.
AI and machine learning will enable automakers to address modernization and diverse customer needs. Software-define vehicles offer personalization opportunities, supported by both of these technologies. Uvarova concludes by saying many car controls, with the help of AI and ML, can be remotely controlled and personalized. This includes climate control from a mobile app, allowing the driver to cool or warm the vehicle before using it.
The same can occur for any entertainment option of for autonomous vehicle technologies. This means that automakers aren’t limited to a few hardware-only options. Instead, they can simplify vehicle manufacturing and create seamless customer experiences, depending on customer needs and sector demands, by offering customers more options and functionality that is powered by software, artificial intelligence, and machine learning.
