The Impact of Autonomous Vehicles' Headway on the Social Delay of Traffic Networks

Through vehicle platooning, autonomous vehicles are capable of maintaining variable longitudinal headway, which can be shorter than the usual headway of human-driven vehicles. Thus, autonomous vehicles are expected to be capable of increasing road capacities. In this work, we consider a scenario where a centralized authority is able to specify the target inter-vehicle headway in autonomous vehicle platoons on the roads and as a consequence, adjust roadways' flow capacities in mixed (human-driven/autonomous) network traffic. We employ a variable, capacity asymmetry degree, which is the ratio between the road capacity when all vehicles are human-driven and the road capacity when all vehicles are autonomous, to characterize and reflect autonomous vehicles' shorter headway compared to human-driven vehicles. We then consider a routing game with inelastic demands on traffic networks with a homogeneous capacity asymmetry degree across the network. We study the impact of the variable capacity asymmetry degree on the overall delay of the network at the Wardrop routing equilibrium. We show that for networks with a single origin-destination pair, we can always decrease the overall or social network delay by decreasing the capacity asymmetry degree (reducing the headway for the autonomous vehicle platoons). Specifically, for series parallel networks with a single origin-destination pair and affine delay functions, we upper bound the improvement on the social delay by reducing the headway for the autonomous vehicle platoons.