Title: Altruistic Autonomy: Beating Congestion on Shared Roads

Abstract: Today the emergence of autonomous cars on public roads has become a reality. Autonomous vehicles on roads shared with human-driven cars can create a variety of challenges including influencing traffic flow when the transportation network is under heterogeneous use: when cars of differing levels of autonomy co-exist on the same road. In this talk, we will address some of the challenges of mixed-autonomy traffic networks via leveraging the power of autonomous vehicles. Specifically we will focus on two main approaches that use autonomous cars to positively influence congestion. First we discuss how local interactions between the vehicles can affect the global behavior of a traffic network. We will examine a high-level queuing framework to study the capacity of a mixed-autonomy transportation network, and then outline a lower-level control framework that leverages local interactions between cars to achieve a more efficient traffic flow via intelligent reordering of the cars. We provide theoretical bounds on the capacity that can be achieved by the network for given autonomy level. Second, we formalize the notion of altruistic autonomy—autonomous vehicles that are incentivized to take longer routes in order to alleviate congestion on mixed-autonomy roads. We then study the effects of altruistic autonomy on roads shared between human drivers and autonomous vehicles. We develop a formal model of road congestion on shared roads based on the fundamental diagram of traffic, and discuss algorithms that compute optimal equilibria robust to additional unforeseen demand, and plan for optimal routings when users have varying degrees of altruism. We find that even with arbitrarily small altruism, total latency can be unboundedly lower than without altruism.