“Hello human…” : thinking about communication with autonomous vehicles
Robots are expected to make more data-informed decisions than humans who may be influenced by their cognitive biases. Yet, there are many barriers to robot acceptance in all sectors. From personal cars to delivery vehicles, in the automotive sector, the development of autonomous vehicles raises many fears. The fear linked to the loss of control and pleasure for the driver who delegates driving to the car (Hegner, Beldad & Brunswick, 2019). But today, fully autonomous vehicles are more widely experimented for public transport or product delivery.
Not-so autonomous vehicles
When we think of autonomous vehicles, we imagine the driver (who is not really a driver anymore but a passenger) busy reading, sleeping, etc. while the car drives itself. Actually, they are 5 levels of vehicle automation:
Level 0 : No automation at all, the driver is fully responsible and has a complete control of the vehicle.
Level 1 : Driver assistance by the vehicle which can take control on the vehicle’s speed, cruise control or lane guidance.
Level 2 : Partial automation the vehicle is capable to combine automated functions but the driver has to monitor the environment at all times.
Level 3 : Conditional automation the driver monitoring is no more required. But he has to be ready to take control of the vehicle when noticed.
Level 4 : High automation the vehicle is in full control of all driving functions under certain conditions. The driver may have the option to control the vehicle
Level 5 : Full automation the vehicle is in full control of all driving functions under all conditions. The driver may also have the option to control it.
The level 5 with fully autonomous vehicles is not available for consumers, but is already being tested in some cities by transport operators for short distances or in the form of pick-up and delivery robots (Mourad, Puchinger & Van Woensel, 2021). Human-machine collaboration still important to use those vehicles. But also to communicate with those vehicles in urban environments.
Vehicle-to-City communications
Indeed, the acceptability of these vehicles is based on the consumer’s perceived usefulness and confidence in the vehicle and its ability to act with others, in the case of mixed traffic. With technical progress, but also for ecological and economic reasons, urban mobility is in full transition. Thus, (more or less) autonomous vehicles must cohabit with each other, with other shared modes (public transport) or individual modes (bicycle, scooter, etc.) and with pedestrians.
Thinking of the autonomous vehicle means thinking of a vehicle capable of communicating with its owner, with other vehicles or other modes of mobility, but also with pedestrians (Lee & Park, 2020; Zeadally, Guerrero & Contreras, 2021).
There are great opportunities for research in social sciences, such as the work of Emeline Ah-Tchine in education sciences for road safety and accident prevention between pedestrians and autonomous vehicles (see Ah-Tchine & de Vries, 2018, August; Ah-Tchine & de Vries, 2018).
For every innovation, social acceptance is a process. Rogers’ innovation diffusion curve is one of the best known to synthesize the main profiles according to their degree of acceptance and how they can promote this acceptance by society (positive word-of-mouth, ambassador …).
But this time, maybe we should look at the past. In its podcast “Build for Tomorrow”, Jason Feifer looks back at the arrival of the automobile in American society (see episode “The first self-driving car was a horse”, 03/02/2017). At the time, horses clogged and soiled the streets. The streets of New York were known to be filthy and the automobile was immediately considered a solution for “clean” streets (!).
But today, driving a car is a waste of time, energy and is not safe (depending on the driver’s state of fatigue, attention, etc.). The autonomous car signs the return of the “horse” in town. Before the arrival of the automobile, the horse, trained to follow a route, brought back its tired master at the end of the work day, without any effort on his part. To create the future, we need to know the past!
And if you’re afraid of losing driving skills with autonomous cars, see this short article : Do we lose skills because of technology ?
Sources:
Ah-Tchine, E., & de Vries, E. (2018, August). Photos in 360° view matter in road crossing decisions in front of traditional and autonomous cars. In EARLI Special Interest Group 2 “Text and Graphics Comprehension meeting.
Ah-tchine, E., & de Vries, E. (2018). Studying initial conceptions of the autonomous car as the groundwork for designing road safety training. BOOK OF EXTENDED SUMMARIES, 1.
Hegner, S. M., Beldad, A. D., & Brunswick, G. J. (2019). In automatic we trust: investigating the impact of trust, control, personality characteristics, and extrinsic and intrinsic motivations on the acceptance of autonomous vehicles. International Journal of Human–Computer Interaction, 35(19), 1769–1780.
Lee, J. M., & Park, S. W. (2020). Drivers’ User-interface Information Prioritization in Manual and Autonomous Vehicles. International Journal of Automotive Technology, 21(6), 1355–1367.
Mourad, A., Puchinger, J., & Van Woensel, T. (2021). Integrating autonomous delivery service into a passenger transportation system. International Journal of Production Research, 59(7), 2116–2139.
Zeadally, S., Guerrero, J., & Contreras, J. (2020). A tutorial survey on vehicle-to-vehicle communications. Telecommunication Systems, 73(3), 469–489.
