Regulating Highly Automated Robot Ecologies

Abstract

Highly automated robot ecologies (HARE), or societies of independent autonomous robots or agents, are rapidly becoming an important part of much of the world's critical infrastructure. As with human societies, regulation, wherein a governing body designs rules and processes for the society, plays an important role in ensuring that HARE meet societal objectives. However, to date, a careful study of interactions between a regulator and HARE is lacking. In this paper, we report on three user studies which give insights into how to design systems that allow people, acting as the regulatory authority, to effectively interact with HARE. As in the study of political systems in which governments regulate human societies, our studies analyze how interactions between HARE and regulators are impacted by regulatory power and individual (robot or agent) autonomy. Our results show that regulator power, decision support, and adaptive autonomy can each diminish the social welfare of HARE, and hint at how these seemingly desirable mechanisms can be designed so that they become part of successful HARE.

Emerging Privacy Issues and Solutions in Cyber-Enabled Sharing Services: From Multiple Perspectives

“…Real-time ridesharing or dynamic carpooling is a transportation service that allows commuters to share rides on very short notice through mobile apps [91], [92], [93], [94], [95]. Successful ridesharing platforms, such as Uber, are available in most major cities in the world.…”

Toward Understanding the Impact of User Participation in Autonomous Ridesharing Systems

“…In our work, we used Price of Anarchy (PoA) (Roughgarden 2005) as the indicator to quantify the extent to which passengers' uncoordinated behavior of ridesharing participation diminishes ARS' performance. The is because price of anarchy has been used as a measure to quantify how the efficiency of a system degrades due to uncoordinated behavior of its agents in many areas, including transportation systems (Youn et al 2008), smart buildings and power grids (Shen 2013;Shen et al 2017).…”

“…Despite much research on ridesharing, most of them focus on the dynamic assignment problem and the network infrastructure (Cordeau 2006;Santos and Xavier 2013;Shen et al 2016;Santi et al 2014;Alonso-Mora et al 2017). On the one hand, stakeholders of ARS might not be able to implement efficient policies to regulate the systems for societal benefits without knowing how users' individual behavior influences the systems' efficiency (Shen et al 2017). On the other hand, little attention has been paid to understanding how passengers' uncoordinated behavior on deciding whether to opt in ridesharing or not affects the systems' performance (e.g., total operational cost).…”