Anonymous Tolling for Traffic Networks with Mixed Autonomy

Road networks are used inefficiently when drivers selfishly choose their own routes rather than being directed on routes to minimize the social cost, which is the total travel delay experienced by all users. In the setting of mixed autonomy, when there are multiple types of vehicles which affect congestion differently, this inefficiency can increase greatly beyond the setting of only a single vehicle type. In the single vehicle type setting, well-known optimal tolls completely eliminate this inefficiency. However, the difficult qualities of mixed autonomy makes it such that optimal tolls are unknown in this setting, absent very restrictive assumptions. In this work we provide the first optimal tolls for the mixed autonomous setting in general networks with multiple source-destination pairs, where road latencies are affine functions of vehicle flow. These optimal tolls are differentiated, meaning that the different vehicle types must be given different toll values. Administering differentiated tolls may be difficult - to address this, we also provide anonymous tolls which may reduce inefficiency in this setting. We quantify the limits of such tolls and compare the performance of our tolls to these bounds.