Traffic congestion has large economic and social costs. The introduction of autonomous vehicles can potentially reduce this congestion by increasing road capacity via vehicle platooning and by creating an avenue for influencing people's choice of routes. We consider a network of parallel roads with two modes of transportation: (i) human drivers, who will choose the quickest route available to them, and (ii) a ride hailing service, which provides an array of autonomous vehicle route options, each with different prices, to users. We formalize a model of vehicle flow in mixed autonomy and a model of how autonomous service users make choices between routes with different prices and latencies. Developing an algorithm to learn the preferences of the users, we formulate a planning optimization that chooses prices to maximize a social objective. We demonstrate the benefit of the proposed scheme by comparing the results to theoretical benchmarks which we show can be efficiently calculated.

翻译：通过车辆排队和创造影响人们选择路线的渠道,采用自治车辆可以增加道路能力,从而减少这种堵塞。我们考虑建立一个平行道路网络,使用两种运输方式:(一) 人驾驶员,他们选择他们可以使用的最快路线,和(二) 乘车停靠服务,向使用者提供一系列自主车辆路线选择,每种选择的价格不同。我们正式确定了混合自治车辆流动模式,以及自主服务使用者如何选择价格和迟滞路线的模式。我们开发了一种算法,以了解用户的偏好,我们制定了一种规划优化,选择价格,以最大限度地实现社会目标。我们通过将结果与我们显示可以有效计算的理论基准进行比较,展示了拟议计划的益处。