Fully automated vehicles (AVs) have the potential to drive empty (without a passenger). For privately-owned AVs, such empty repositioning has the potential benefit of avoiding parking costs at their destination. AV owners could have their vehicle drop them off at their destination, then drive elsewhere to park. Although previous studies have considered the congestion effects of AVs repositioning to park at their owner’s residence, this study models the choice of parking location when AVs reposition away from the traveler’s destination. We model this behavior through a modified static traffic assignment with a logit model for destination choice, in which AV passenger-carrying trips can create a second empty repositioning trip to an alternate parking zone. The traffic assignment is formulated as a variational inequality. Numerical results on the Chicago sketch network show the effects of AV market penetration, fuel costs, and parking fees on the number of repositioning trips, as well as the impacts of repositioning trips on network congestion. Next, we study the problem of adjusting zone-specific parking costs to influence the repositioning behavior. In particular, when zones have asymmetric parking infrastructure costs, optimized parking fees combined with empty repositioning can encourage AVs to park at cheaper locations, thus reducing the land used for parking at zones with high land value. This network design problem is formulated as a bi-level program. Since it is bi-level and non-convex, a genetic algorithm is used to find a good solution. Results on the Sioux Falls test network show that the adjusted parking costs are effective at reducing the congestion caused by empty repositioning and encouraging more optimal parking choices for repositioning AVs.

全自动驾驶汽车（AV）有潜力空载（无乘客）。对于私有的AV，这种空的重新定位具有避免在目的地停车的潜在好处。视听车主可以将自己的车辆放到目的地，然后开车到其他地方停车。尽管先前的研究已经考虑了将自动驾驶汽车重新安置在其所有者住宅中的拥堵效应，但本研究对当自动驾驶汽车重新放置于远离旅行者目的地时停车位置的选择进行了建模。我们通过修改后的静态交通分配和用于目的地选择的logit模型对这种行为进行建模，其中，AV乘客出行可以创建第二个空的重新定位出行到备用停车区。交通分配被表述为变分不等式。芝加哥草图网络上的数值结果显示了影音市场的渗透，燃油成本和停车费对重新安置行程的数量的影响，以及重新安置行程对网络拥堵的影响。接下来，我们研究调整区域特定停车成本以影响重新定位行为的问题。特别是，当区域的停车基础设施成本不对称时，优化的停车费加上空置的重新安置可以鼓励AV车辆停在更便宜的位置，从而减少用于高土地价值区域停车的土地。此网络设计问题被表述为双层程序。由于它是双层且非凸的，因此使用遗传算法来找到一个好的解决方案。