重新审视自动驾驶汽车和动态瓶颈拥堵:车内活动如何决定总体出行模式

Xiaojuan Yu, Vincent A.C. van den Berg, E. Verhoef
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引用次数: 8

摘要

我们研究了自动驾驶汽车中通勤者的车内活动对总体出行模式的影响。与普通汽车相比,我们允许自动驾驶汽车影响在家和开车之间的效用差异,而不是上班和开车之间的效用差异。这影响了旅行延迟值、提前计划延迟值和延迟计划延迟值的相对重要性。因此,当自动驾驶汽车问世时,出行模式可能会发生多种变化。转向自动驾驶汽车可能会带来净负或正的外部性,因为它提高了自动驾驶汽车本身的边际外部成本,同时降低了普通汽车的边际外部成本。我们研究了三种供应制度:边际成本定价、次优定价和私人垄断的利润最大化定价。由于边际外部成本的增加,次优加价(高于边际成本)随着价格敏感性的提高而上升。令人惊讶的是,对于垄断企业来说,加价可能会随着价格敏感性而上升或下降,这取决于外部性和市场力量的相对强度,前者倾向于提高加价,后者倾向于降低加价。此外,随着需求对价格变得更加敏感,私人垄断和第二好的公共供应之间的价差会缩小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Autonomous Cars and Dynamic Bottleneck Congestion Revisited: How In-Vehicle Activities Determine Aggregate Travel Patterns
We investigate the impacts of in-vehicle activities of commuters in the autonomous car on aggregate travel patterns. We allow for an autonomous car to affect the utility difference between being at home and being in the vehicle differently than the utility difference between being at work and being in the vehicle, compared to the differences experienced with a normal car. This affects the relative importance of values of travel delays, schedule delays early, and schedule delays late. Hence multiple possible changes in travel patterns may occur when autonomous cars become available. Switching to an autonomous vehicle may impose a net negative or positive externality, by raising the marginal external cost of autonomous cars themselves while lowering that of normal cars. We examine three provision regimes: marginal cost pricing, second-best pricing and profit-maximizing pricing by a private monopoly. The second-best mark-up (over marginal cost) rises with the price sensitivity, due to the increasing marginal external cost. Surprisingly, for the monopoly, mark-up may rise or fall with the price sensitivity, depending on the relative strength of the externality and of market power, where the former tends to raise it, and the latter tends to reduce it. Furthermore, the difference of the mark-up between private monopoly and second-best public provision falls as the demand becomes more price-sensitive.
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