Altruistic Autonomy: Beating Congestion on Shared Roads

TL;DR

This paper models how altruistic autonomous vehicles can significantly reduce traffic congestion on shared roads, demonstrating through algorithms and simulations that even minimal altruism improves overall traffic flow.

Contribution

It introduces a formal model of altruistic autonomy in traffic, providing algorithms for optimal routing and analyzing the impact of altruism on congestion reduction.

Findings

Even small altruism greatly improves total latency.

Optimal equilibria outperform selfish ones significantly.

Simulations show a fourfold decrease in latency with altruistic AVs.

Abstract

Traffic congestion has large economic and social costs. The introduction of autonomous vehicles can potentially reduce this congestion, both by increasing network throughput and by enabling a social planner to incentivize users of autonomous vehicles to take longer routes that can alleviate congestion on more direct roads. We formalize the effects of altruistic autonomy on roads shared between human drivers and autonomous vehicles. In this work, we develop a formal model of road congestion on shared roads based on the fundamental diagram of traffic. We consider a network of parallel roads and provide algorithms that compute optimal equilibria that are robust to additional unforeseen demand. We further plan for optimal routings when users have varying degrees of altruism. We find that even with arbitrarily small altruism, total latency can be unboundedly better than without altruism, and that the best selfish equilibrium can be unboundedly better than the worst selfish equilibrium. We validate our theoretical results through microscopic traffic simulations and show average latency decrease of a factor of 4 from worst-case selfish equilibrium to the optimal equilibrium when autonomous vehicles are altruistic.