Moving Beyond the Trolley Problem for Autonomous Vehicle Ethics

Friday - December 1 2023, 23:14 UTC - 11 months ago

Researchers have developed an experiment to better understand people's ethical judgments in a variety of traffic scenarios. By creating a virtual reality environment, they are able to collect data on how humans perceive and make moral decisions in low-stakes traffic situations. This data can ultimately help inform autonomous vehicle development and public policy.

Researchers have developed a new experiment to better understand what people view as moral and immoral decisions related to driving vehicles, with the goal of collecting data to train autonomous vehicles how to make "good" decisions. The work is designed to capture a more realistic array of moral challenges in traffic than the widely discussed life-and-death scenario inspired by the so-called "trolley problem." The paper, "Moral judgment in realistic traffic scenarios: Moving beyond the trolley paradigm for ethics of autonomous vehicles," is published open access in the journal AI & Society.

"The trolley problem presents a situation in which someone has to decide whether to intentionally kill one person (which violates a moral norm) in order to avoid the death of multiple people," says Dario Cecchini, first author of a paper on the work and a postdoctoral researcher at North Carolina State University.

"In recent years, the trolley problem has been utilized as a paradigm for studying moral judgment in traffic," Cecchini says. "The typical situation comprises a binary choice for a self-driving car between swerving left, hitting a lethal obstacle, or proceeding forward, hitting a pedestrian crossing the street.

"However, these trolley-like cases are unrealistic. Drivers have to make many more realistic moral decisions every day. Should I drive over the speed limit? Should I run a red light? Should I pull over for an ambulance?" .

"Those mundane decisions are important because they can ultimately lead to life-or-death situations," says Veljko Dubljević, corresponding author of the paper and an associate professor in the Science, Technology & Society program at NC State.

"For example, if someone is driving 20 miles over the speed limit and runs a red light, then they may find themselves in a situation where they have to either swerve into traffic or get into a collision. There's currently very little data in the literature on how we make moral judgments about the decisions drivers make in everyday situations." .

To address that lack of data, the researchers developed a series of experiments designed to collect data on how humans make moral judgments about decisions that people make in low-stakes traffic situations. The researchers created seven different driving scenarios, such as a parent who has to decide whether to violate a traffic signal while trying to get their child to school on time.

Each scenario is programmed into a virtual reality environment, so that study participants engaged in the experiment have audiovisual information about what drivers are doing when they make decisions, rather than simply reading about the scenario.

For this work, the researchers built on something called the Agent Deed Consequence (ADC) model, which posits that people take three things into account when making a moral judgment: the agent, which is the character or intent of the person who is doing something; the deed, or what is being done; and the consequence, or the outcome that resulted from the deed.

Researchers created eight different versions of each traffic scenario, varying the combinations of agent, deed and consequnce. They then recruited 180 people to participate in the virtual reality experiment and rate how moral they perceived each action.