How Do Waymo Self-Driving Cars Impact Traffic Flow? Evidence from Empirical Data

This paper studies the behaviors of Level-4 autonomous vehicles based on the large-scale data of Waymo self-driving cars (SDCs). Through a careful and rigorous treatment of the data, we have identified the stationary traffic states and used them to obtain the spacing-speed relationship, which is then used to derive the flow-density relationship. We have analyzed the Waymo SDCs and human-driven vehicles (HDVs) in the traffic stream. It was found that the SDCs maintain a linear spacing-speed relationship, like their human counterparts, but the SDCs are more conservative (characterized by a larger spacing), which results in a significant downgrade of roadway capacity ( about 18% on arterials with a 40-mph speed limit). Moreover, HDVs behave differently (more conservative) when they are near the SDCs, leading to an additional capacity downgrade and suggesting an induced effect of the SDCs. Lastly, in (near-) stopped conditions, SDCs maintain a much larger jam spacing than that of HDVs, suggesting a potential reduction of roadway storage capacity. These findings have important implications for traffic operations, network management, and transportation planning as AV deployment continues to expand.