Manufacturers and consumers alike are interested in software-defined vehicles (SDVs) and the promise of upgrades via continuous over-the-air (OTA) updates. For consumers, SDVs will deliver new features, functionality and enhanced personalized experiences. For manufacturers (and even dealers and Tier 1s), SDVs will open new revenue opportunities and business models.
Industries outside the automotive sector have already realized this vision. Mobile-device and other tech companies regularly capture and analyze usage data to define and deliver future enhancements. To make a similar leap, automotive manufacturers not only need to embrace a software-engineering mindset, but also sufficiently provision in-vehicle hardware that – when combined with the cloud – enables long-term innovation.
This mindset is a paradigm shift and different from traditional auto engineering, which relies on hardware designed to minimize cost. A new philosophy is to over-provision, in reasonable steps, the computer hardware so manufacturers can use that capacity to create new value from software. Leveraging a customer base to help create continuously better software is the mastery of digital innovation. To realize these developmental and financial benefits, manufacturers must make bold hardware decisions today that will drive their sales performance tomorrow.
An Optimal User Experience FROM Humans, Not Just FOR Them
Driver-assistance technology has doubtlessly saved thousands of lives, and the promise of automated driving is enticing. Yet in today’s stark reality, many legally mandated or optional comfort-assistance technologies distract drivers with frequent malfunctions, make robot-like decisions and feel synthetic. Today’s traffic is complex, and the ask for an in-vehicle robotized assistance system that blends safely and seamlessly is too tall.
Tech-enabled functionality must feel natural. Until recently, human interaction with tech was more limited: button presses and barking commands. Today’s systems are more intelligent, but creating real human-like experiences requires more input, analysis, and iteration. This process is well established in tech platforms like Windows (Insider), social media, gaming, and entertainment. Vehicles are a different story.
Generations of automotive engineers, like many in non-tech sectors, are ingrained with a “launch requirements” mindset. Any additional capacity or functionality is considered a waste of resources. As a result, vehicles tend to roll off the assembly line with the tech specs they need to deliver a positive driver experience on Day One. What about Day 730? The software may be updatable, but do the assembly-line hardware specifications truly allow the innovation that OEMs aspire to deliver?
Driver-assist technology like adaptive cruise control, lane-change warnings or merging needs to seem smooth, human, and natural, not jerky, stilted and awkwardly reactive. Improving these features means analyzing and accounting for how humans drive. Computer simulations alone aren’t sufficient because they use technology inputs rather than real-world inputs.
For feature development to realize a natural/human feel, automotive systems must incorporate constant learning from driver actions to improve the experience over time. One option to enable this adaptation is gathering and analyzing data from an entire fleet’s sensors and systems. Infotainment and in-car marketplace experiences must also be able to evolve alongside market and user expectations. In both instances, growth can be driven by software, but only if the hardware enables it.
Why Softwarization Matters to OEMs and Dealers
Swam-based learning is the principle of observing and collecting data on how people interact with technology. In the automotive industry, collecting human driving data and combining it across the fleet of a brand can be used to improve future functionality. Data collection and analysis in conformance with data-privacy regulations improve the driving and customer experience, thus making the vehicle stay relevant and modern over time. But driving-experience data capture must be enabled from the design stage by future-proofing the vehicles’ compute capacity and connectivity elements.
This is beneficial for consumers, of course, but for manufacturers and dealers, this data-centric design can drive new revenue. Over time, data capture and analysis will enable the updates and innovation that ultimately improve a vehicle’s long-term residual value. The higher a fleet’s long-term residual values, the lower the finance rates an OEM can offer through their dealerships, which attracts new buyers, increases sales and potentially opens new markets. This applies both to traditional dealerships and new agency models alike.
Technology and Human Input Lead to Larger, More-Lucrative Markets
The automotive industry is moving toward a human-led, software-defined reality. This transformation necessitates a focus on both hardware and software, as the two are intricately connected. Incorporating user inputs and innovating accordingly will make traditional OEMs more feature-competitive with upstart brands, but it requires their engineers to dramatically change how they think of their vehicles.
Creating a car that gets better every day delivers higher value for users, OEMs and dealers alike, as it cultivates customer loyalty and opens new revenue opportunities. Automakers must build extra capacity into their vehicles to accommodate the development of new data-driven features and human-like functionality. This capacity is not wasteful; it’s an investment in the future. It is time to shift from the decades-old auto-engineering mindset. Automobiles can no longer be static products; they must be adaptable platforms capable of growth.
Thomas Mueller
VP, CTO and Automotive Lead, Wipro Engineering
Thomas is a Vice President in Wipro Engineering and has more 30 years of experience across the automotive, cloud, and financial sectors. He is currently responsible for Wipro’s automotive engineering and innovation services, which encompasses everything from software-defined vehicles and autonomous driving to 5G and cloud-native engineering.
