Social Cohesion in Autonomous Driving

TL;DR

This paper proposes a method for autonomous cars to improve safety and social acceptance by mimicking human drivers' behavior, leveraging social cohesion principles and validated through scenario analysis and user studies.

Contribution

It introduces a socially cohesive driving algorithm that aligns autonomous vehicle behavior with human drivers, enhancing safety and social acceptability.

Findings

People tolerate some mistakes by cohesive cars for safety benefits.

Socially cohesive cars can adapt to complex traffic scenarios.

User attitudes are generally positive towards socially cohesive driving.

Abstract

Autonomous cars can perform poorly for many reasons. They may have perception issues, incorrect dynamics models, be unaware of obscure rules of human traffic systems, or follow certain rules too conservatively. Regardless of the exact failure mode of the car, often human drivers around the car are behaving correctly. For example, even if the car does not know that it should pull over when an ambulance races by, other humans on the road will know and will pull over. We propose to make socially cohesive cars that leverage the behavior of nearby human drivers to act in ways that are safer and more socially acceptable. The simple intuition behind our algorithm is that if all the humans are consistently behaving in a particular way, then the autonomous car probably should too. We analyze the performance of our algorithm in a variety of scenarios and conduct a user study to assess people's attitudes towards socially cohesive cars. We find that people are surprisingly tolerant of mistakes that cohesive cars might make in order to get the benefits of driving in a car with a safer, or even just more socially acceptable behavior.