User interfaces and services of consumer electronics and smartphones are developing rapidly. In the automotive market, this results in customers having high expectations for HMIs (human-machine interfaces). At the same time, customers have growing expectations for cars, automotive variety and the number of new mobility solutions. Customizing menus and controls to their users is a key element for optimizing the automotive customer experience. However, this optimization requires that important framework conditions be considered.
Cloud-based services, vehicle to vehicle (V2V) communication, the integration of smartphones into the operating systems of cars and increasingly intelligent driver assistance systems – these developments characterize the state of the art in the automotive market. The above solutions offer drivers more and more support, convenience and information. At the same time, these solutions risk making vehicle operation and its systems more complex.
Furthermore, tech- and computer-savvy drivers have an entirely different set of expectations for user interfaces than first-time and inexperienced users. Interfaces that can be easily handled by one driver might be too much for another. However, this does not comply with the requirement not to distract drivers from their driving task.
In addition, the conditions under which people use cars change increasingly – for example, due to car sharing. Likewise, the decision to buy a particular car model is no longer enough to derive who uses it and how it is used. A station wagon or SUV used by a family is mainly used to drive the kids to school, sports practice and music lessons – whereas sports-oriented singles use the same model to transport their surfboards or mountain bikes.
This results in a number of challenges for OEMs and user interface developers. One solution to this can be to personalize operating concepts. This customization with the aim of a customer experience that focuses on the driver offers clear advantages: The operating concepts in the vehicle can be designed to meet the exact requirements of the user. At the same time, this basis allows automobile manufacturers to improve their systems – through remote updates to existing systems and future systems in the pre-development stage.
Localization and car model differentiation already require customization solutions
When it comes to their vehicles’ localization, OEMs have long been looking for ways to customize user interfaces. The comprehensive, market-oriented adaptation of, for example, the language of display menus and messages, audio indications given by the navigation system and voice commands often proves to be more complex than first expected. It is not enough to merely translate the terms. The adaptation must also consider other factors such as country-specific characteristics. Even within one country, there may be distinct regional differences – as is the case in Spain or China.
Another dimension of customization is to distinguish between brand-specific characteristics such as sports and standard models of a vehicle type or between the individual brands of a group of companies. Sometimes, such adaptations are made even within the same vehicle, as for switchable day/night or sports modes. OEMs whose HMIs support such distinctions have already laid the foundation for driver-specific customization. This also provides a good opportunity to tailor vehicles to specific target groups – to sports-, convenience- or family-oriented buyers. In this context, customer addressing can also apply concepts and customer habits from other markets such as nutrition, fitness or consumer goods.
User profiles as a basis for personalization
From the software’s perspective, such personalization is based on the management of user profiles. They are defined by different parameters such as the driver’s age, gender and/or role (driver or passenger). In the simplest case, only settings such as the position of the seat and mirrors or the space allocation of radio stations need to be customized. However, this customization increasingly includes other aspects such as personalized access and service subscriptions in the infotainment system. If a driver uses multiple vehicles of the same brand, transferring the driver’s profile between the vehicles becomes relevant. This involves, for instance, personalized special services that can be booked on-demand that the customer can use in other cars from the same manufacturer. There are hardly any limits to the creativity of service providers. Linking identified patterns and usage habits allows them to develop attractive services. For example, if the system detects that the whole family regularly attends football games on Saturdays, special services could provide family members who are less sports-minded with interesting shopping options near the football stadium. Building blocks such as a trip to the mountains on the weekend and the information that it rained during the trip could result in a discount for a car wash.
In addition, the option of personalizing brand-specific car sharing offers plays an increasingly important role. The customer experience can be significantly improved if the driver finds a personalized environment in the booked vehicle and is welcomed personally.
Different options for identification
However, this quickly raises the question of how the driver is identified by the vehicle. Manual logins are inconvenient. Current solutions mostly use the detection of components such as the car key or a token. Wearables such as smartwatches and, of course, smartphones are alternative solutions that can be considered. However, identification by smartphone involves problems if several vehicle occupants carry their own smartphones or, vice versa, several family members share one phone. More recent approaches include biometric technologies such as voiceprint, fingerprint or facial recognition. Depending on the requirements, it is also possible to combine several identification solutions. For example, the seat, mirrors and other default settings could adjust to the customer when the vehicle key or token approaches the car, whereas access to personal services is not enabled before the driver is recognized by the biometric system.
However, this results in a conflict of aims between convenience and privacy. Biometric data and personal preferences are very sensitive data – and longer use produces large amounts of it. Therefore, a security-conscious and responsible approach is key to handling such data. In addition, the system design should take into account that the needs and habits of users can change – for example, they move to a new house, take on a new job or their preferences simply change with age. One approach to this is to anonymize sensitive data. From a legal perspective, it is also recommended that, using an opt-in feature, drivers expressly agree to the use of their data for personalization.
Self-learning HMIs allow better personalization
The possibilities outlined above apply to all elements of multimodal user interfaces – haptic controls, on-screen menus, touchscreens, indicators and head-up displays, gesture-based control and voice recognition.
To customize the above parameters as closely as possible to users’ needs, the HMI should have a certain degree of learning ability. This enables the software to recognize frequently used functions or usage patterns and give preference to the associated options it provides to the user. Based on big data analyses, it is even possible to predict probable user actions, for example, by comparing the usage data of similar demographic groups. In the future, it might also be possible to include other data sources from the Internet of Things – from networked refrigerators to sports and activity trackers. This could bring benefits to both vehicle manufacturers and users, provided that this data is sufficiently anonymized.
