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Autonomous vehicles (AVs) including artificial intelligence AI-powered driverless or self-driving cars have received significant attention as a potentially safer and more sustainable mode of transport. Some researchers believe that by 2050, highways will be unmanned and the global market for self-driving cars will reach about 400 billion U.S. dollars. Even though autonomous vehicles may be increasingly technologically advanced for widespread adoption, people may not be psychologically prepared for this change. As a result, some experts believe they will not become popular in the market until 2040 at the earliest or even later in 2060.
Automated vehicles hold the promise to make driving less tiring, more convenient, and safer, but there are several psychological barriers that will influence the adoption of self-driving cars as well as potential psychological effects if they are adopted more widely.
New research suggests that people who enjoy driving or have a mistrust of AI are least likely to relinquish driving to autonomous vehicles. The group that is most likely to adopt self-driving cars are those who expect it to be an enjoyable and convenient experience. There are additional safety issues, such as the fact that people feel safer and prefer when they are able to take over control of the vehicle if it malfunctions.
There are six levels of autonomous driving as defined by the SAE International (formerly Society of Automotive Engineers):
- Level 0: No Driving Automation
- Level 1: Driver Assistance (e.g., radar-based cruise control)
- Level 2: Partial Driving Automation — driving mode controls acceleration/deceleration and steering, but human controls dynamic aspects like changing lanes or turning
- Level 3: Conditional Driving Automation — automated driving system that monitors the environment, but expects human to respond if there is a request to intervene
- Level 4: High Driving Automation — system controls all aspects of driving including if driver does not respond appropriately to request to intervene
- Level 5: Full Driving Automation — full-time automated driving system with no expectation of human intervention
Researchers use varying technology acceptance models to determine whether self-driving cars will be accepted. These models examine variables like intention to use, emotional state, attitude, perceived usefulness, and perceived ease of use. These models are limited because they rely on people being able to imagine and report a future expected emotional experience of an autonomous vehicle.
There are also additional methods to measure the user experience of self-driving cars such as using biosensors to measure heart rate, muscle activity, eye movements, and brain waves on electroencephalography (EEG) of passengers during real-world or virtual reality simulations. One exploratory study of 38 participants used a real-world environment and compared the physical reactions of people in self-driving cars to being driven by a human in the same car. There were no differences between stress signals (“arousal”), but eye movements were different. Autonomous vehicle passengers showed much less variable eye movements. Expanding this area of research will shed light on the user experience of autonomous vehicles.
There are four main categories of psychological barriers to autonomous vehicles.
1. The Role of Trust
Trust is a major factor that determines whether people intend to use self-driving cars. One recent study found that people were more likely to feel safe as a passenger in the car of a human defensive driver than an autonomous vehicle, even though the driving behavior in the simulator was the same.
This raises the broader question of how to enhance trust with autonomous vehicles and AI. Trust is influenced by media portrayal of autonomous vehicles and AI more broadly. As people become more acclimated to AI as part of daily life, the acceptance of AI as part of the driving experience will likely increase.
2. Sense of Agency and Control
The sense of control associated with driving oneself will be challenging for some people to let go. People who feel independence and agency from driving may not readily hand this control over to an automated system, even if it is technically safer or more efficient.
People may be more willing to ease into a world of autonomous vehicles by adopting Level 3 or Level 4 automated vehicles, which collaborate with a human driver. But this will raise separate issues, such as research findings that cognitive awareness needed to supervise an automated car wanes with time. During the crossover transition period, there may be more traffic issues because humans currently maneuver based on anticipating how other humans drive, not automated systems.
There are also downstream effects of giving up driving control to full automation. Without driving, people will lose the cognitive, coordination, and spatial skills that come with driving. This will be similar to what has happened with spatial navigation. Researchers have confirmed that the increasing reliance on GPS systems for navigation has led to lower spatial memory and less ability to navigate independently.
3. Productivity and Usefulness
People who perceive autonomous vehicles to be useful will be most motivated to adopt them. Those who will prefer to use that driving time more productively doing other things will find self-driving cars more convenient and useful.
4. The Enjoyment Factor
Finally, enjoyment is an important factor. People who enjoy driving are least likely to transition to self-driving cars. Novelty-seekers who anticipate the experience of being in a self-driving car to be fun and entertaining will most likely be early adopters. However, it is unclear if enjoyment alone will be enough to overcome these other psychological barriers. The experience needs to be enjoyable beyond a one-time motivation from the novelty of a new experience in order to be sustained.
Marlynn Wei, MD, PLLC © Copyright 2023 All rights reserved.