Will we start trusting artificial intelligence for our future mobility soon?
Will we start trusting artificial intelligence for our future mobility soon?
( Source: Andrey Popov stock.adobe.com)

PUBLIC ACCEPTANCE Trust is key for autonomous mobility

Author / Editor: Ricco Magdsick, Victoria Baum / Florian Richert

Future mobility starts today, and automated and autonomous driving will be possible soon. But innovations are always accompanied by concerns and rejection. Artificial intelligence will fundamentally change our mobility, and acceptance is an essential prerequisite for this.

The automotive industry is on the cusp of a fundamental change: the delegation of the driving task to artificial intelligence. But is society ready for this development? Supporting customers in building confidence in automated and autonomous driving will be a fundamental challenge for automotive manufacturers as well as for cities and municipalities as these technologies are gradually integrated into existing and future mobility solutions. Therefore, a variety of different measures must be taken to anticipate uncertainties and thus pave the way for the acceptance of this technology.

Distrust as a widespread phenomenon

National and international studies show that acceptance and trust in highly automated vehicles remains at a low level. This phenomenon is especially understandable in Europe since autonomous pilot projects currently focus almost exclusively on the use of highly automated shuttles in clearly defined areas with mostly fixed routes. In contrast to technology companies such as Waymo (USA) or pony.ai (China), whose self-driving vehicles already carry passengers, this technology is hardly tangible in Europe, except for Yandex (Russia). However, trust can only be created if citizens are informed (at least generally) about how the technology works and have experienced it themselves. After all, a new technology is always unfamiliar at the beginning – only after repeated use and a certain degree of familiarity is acceptance likely to increase.

Critical success factors open up a concrete solution space

Some success factors for acceptance of autonomous driving in society can be derived and used to identify confidence-building measures: reliability, transparency, familiarity, and experience.

Reliability refers to safe and dependable Advanced Driver Assistance Systems (ADAS) and immediate provision of necessary support if needed. Of course, this requires an infeasible number of road-testing miles to be driven and simulated. The technology will only be accepted by potential users when reliability of an autonomous vehicle is perceived to be at least as high as their own driving behavior.

Transparency is another success factor for automobile manufacturers or cities and communities and would refer to permanent information regarding functionality and next steps performed by the ADAS. For example, every operator of an autonomous shuttle should, from our point of view, visualize object detection and recognition on screens during the journey. This would help passengers to understand how the environment is perceived by a shuttle’s lidars, radars or cameras. For instance, the in-car screens in Waymo vehicles not only display a route’s cartography to the passengers, but also show road users and road signs recognized by the sensors. In addition to that, another potential measure before and during the journey would be to explain the algorithms’ functioning as well as the principle and application of redundancy during an autonomous ride. In our view, the more people know about the technology and the more they understand how it works, the more likely it is that trust will develop.

Ricco Magdsick, Expert Autonomous Mobility at P3 Group
Ricco Magdsick, Expert Autonomous Mobility at P3 Group
(Source: P3 Group)

Familiarity as a success factor should also be viewed in the context of building trust with driving functions and driver support based on already known services. The more you know about a technology, the more you can potentially trust it. An exemplary measure for private customers (i.e. privately owned autonomous vehicles) should clarify this: As a first step, car dealers’ sales staff need to gain adequate knowledge of the vehicles’ automated and autonomous functions through standardized functional and technical training with the aim of communicating this knowledge to the customer. Furthermore, users must be sensitized to integrating ADAS into their daily rides. Once sales staff disposes of required knowledge, potential initiatives for car dealers could be, for in-stance, a driverless handover process during car pick-up at the car dealer (including the presentation of relevant features and driving simulation), comprehensive test drives or a training supported by virtual reality. This results in familiarity with the technology before the users actually begin their journey. From our point of view, this increases the probability that highly automated driving functions will be integrated into daily rides. The more a user trusts automated driving functions, the more likely he or she is to get into a robotaxi later where there is no control of the driving task anymore.

Victoria Baum, Expert Autonomous Mobility at P3 Group
Victoria Baum, Expert Autonomous Mobility at P3 Group
(Source: P3 Group)

Experience is yet another success factor that refers to user experience and personalized/detailed support while but also before driving. For instance, potential measures before boarding the vehicle are trust events initiated by car manufacturers or suppliers including test drives with real drivers as well as virtual drivers to see the difference – if there is any. Moreover, user experience might include a technical but ‘personal companion’ to build a personal relationship through direct approach by the systems. More precisely, potential measures include real time information and driving recommendations (e.g. audible support, in-car videos) to make technology self-explanatory. Transparency and experience can therefore be considered together.

Distrust may lead to economic and social risks

One thing seems clear: if you do not trust a technology, you will neither pay for it nor use it. In this context, we see risks for car manufacturers and suppliers on the one hand and for cities and municipalities on the other. Private customers should not be expected to be willing to pay extra for systems they do not understand or use, and which are not required by law (e.g. Lane Keeping Assistant from 2022). They may therefore reject the technology. Moreover, customers who do not trust level 2 systems are not likely to accept level 3 to 5 systems either and, as a result, will probably not ever get into an autonomous driving vehicle. Cities, in turn, would be confronted with other difficulties. Often, autonomous (shared) cabs are considered a climate-friendly, efficient and cost-effective means of transport, which could also lead to an improvement in traffic flow. However, in the case of distrust of autonomous driving and a lack of acceptance (also of shared mobility in general), “the benefits would be lost, and individual transport would continue to be in the foreground besides public transport. However, municipalities and rural areas seem to be particularly affected by a lack of trust. Already today, pilot projects with highly automated shuttles intend to integrate rural regions into the public transport network at relatively low cost and to re-integrate communities (especially passengers of restricted mobility) that have been partially excluded from mobility so far. A lack of trust among citizens would mean that some regions would continue to miss out on adequate transport connections.

Trust is key for autonomous driving

Even today’s ADAS have strong acceptance problems from the customers’ side due to a lack of knowledge as well as distrust. Therefore, confidence in safety, usefulness, and reliability of autonomous systems has to be created to reduce the danger of future economic damage.

What is imperative is that automotive industry companies as well as cities and municipalities recognize trust issues early on and take measures to familiarize the customer with the functionalities and benefits that come with autonomous systems.

Various success factors offer a concrete framework for action to identify and implement a holistic trust concept with relevant measures - because trust is key.

* Ricco Magdsick joined P3 automotive GmbH in 2018, where he consults both MaaS and TaaS providers in the area of autonomous driving. In the past years, Mr. Magdsick has focused on customer acceptance in automated and autonomous driving, global market intelligence, and pilot projects with highly automated shuttle busses.

* Victoria Baum is Senior Consultant at P3 were she conducted various projects in the area of Autonomous Mobility and Cost Management with a focus on pilot projects for Mobility as a Service applications, profitability analysis & business cases, total cost of ownership calculations, efficiency programs, process analysis & optimization and project management in general.