Routing for Traffic Networks with Mixed Autonomy
This work provides theoretical performance guarantees for selfish routing in mixed-autonomy networks, which is important for transportation planners and policymakers managing the transition to autonomous vehicles.
The paper proposes a macroscopic model for routing in mixed-autonomy traffic networks, capturing platooning effects of autonomous vehicles, and bounds the Price of Anarchy (PoA) and bicriteria measures. The bounds depend on the polynomial degree of road cost functions and the asymmetry between human-driven and autonomous traffic, recovering classical bounds when asymmetry is absent and being order-optimal with respect to asymmetry.
In this work we propose a macroscopic model for studying routing on networks shared between human-driven and autonomous vehicles that captures the effects of autonomous vehicles forming platoons. We use this to study inefficiency due to selfish routing and bound the Price of Anarchy (PoA), the maximum ratio between total delay experienced by selfish users and the minimum possible total delay. To do so, we establish two road capacity models, each corresponding to an assumption regarding the platooning capabilities of autonomous vehicles. Using these we develop a class of road delay functions, parameterized by the road capacity, that are polynomial with respect to vehicle flow. We then bound the PoA and the bicriteria, another measure of the inefficiency due to selfish routing. We find these bounds depend on: 1) the degree of the polynomial in the road cost function and 2) the degree of asymmetry, the difference in how human-driven and autonomous traffic affect congestion. We demonstrate that these bounds recover the classical bounds when no asymmetry exists. We show the bounds are tight in certain cases and that the PoA bound is order-optimal with respect to the degree of asymmetry.