Duration-based parking toll for autonomous vehicles: Theories and preliminary results

The emerging autonomous driving technology is believed to bring about big changes to trip-making, e.g., autonomous vehicles (AVs) can drop off passengers before parking. The paper focuses on the morning commute problem with parking in a 100% AV environment. First, using a two-tandem bottleneck model, the paper discusses complete four phases user equilibrium (UE) morning commute patterns considering fixed parking fee. A duration-based parking tolling scheme is then introduced to induce changes in commuters' departure time choices and parking decisions, so as to better utilize the parking facilities around the central business district (CBD). Numerical results show that the proposed scheme can effectively alleviate traffic congestions caused by excessive demand for morning commute and drop-offs, while reducing both individual and system travel cost. Compared to fixed parking toll, the proposed scheme can reduce queuing period in the morning peak by 60% at the upstream bottleneck and 11% at the downstream bottleneck. The maximum individual queuing delay at the upstream bottleneck and downstream bottleneck will also be reduced from 11 and 23 minutes to 7 and 20 minutes, respectively.