Free-floating carsharing (FFCS) systems are characterised by volatile fleet distribution as well as customers’ heterogeneous price sensitivity and spatiotemporal flexibility. There is thus an opportunity for operators to employ dynamic pricing to manage various aspects of fleet allocation: which customer is provided which vehicle, at what time and price, and the agreed pick-up and drop-off location. While there are emerging examples of dynamic pricing in FFCS, there is as yet no general framework for the interaction of consumer and operator behaviours in this context, most particularly consumer response to the inherent risks and uncertainties in the journey characteristics noted above. In this study, we propose a choice-based framework for modelling the supply/demand interaction, drawing on behavioural models of decision-making in risky choice contexts and empirical stated-choice data of user preferences in a dynamically priced FFCS market. In addition to the ‘spot market’ mechanism of dynamic pricing, the proposed framework is capable of evaluating operator strategies of allowing (at an agreed price) customers to make guaranteed advance reservations. We demonstrate that this approach allows the system operator to set an optimal pricing strategy regardless of whether user risk preferences are risk-seeking or risk-averse. We also demonstrate the applicability of the proposed framework when the operator seeks to maximise revenue (as with a private operator) vs social welfare (as with a public operator). In the case study which employs empirical user preferences, we show that users’ risk preferences have a relatively small impact on revenue, however the impacts are much larger if there is a mismatch between users’ actual risk preferences and the system operator’s assumptions regarding users’ risk preferences.

自由浮动的汽车共享（FFCS）系统的特点是车队分布不稳定，以及客户的异构价格敏感性和时空灵活性。因此，运营商就有机会采用动态定价来管理车队分配的各个方面：向哪个客户提供哪种车辆，什么时间和价格，以及约定的接送地点。尽管在FFCS中出现了动态定价的新例子，但在这种情况下，尚无用于消费者和运营商行为互动的通用框架，尤其是消费者对上述行程特征中固有风险和不确定性的反应。在这项研究中，我们提出了一种基于选择的框架来建模供需交互，利用动态选择的FFCS市场中风险选择情况下的决策行为模型和用户偏好的经验性陈述选择数据。除了动态定价的“现货市场”机制外，提出的框架还能够评估运营商的策略，以允许（按约定的价格）客户进行有保证的提前预订。我们证明了这种方法使系统操作员可以设置最佳定价策略，而不管用户风险偏好是寻求风险还是避免风险。当运营商寻求最大限度地提高收入（如私人运营商）与社会福利（如公共运营商）时，我们还将证明所提议框架的适用性。在采用经验用户偏好的案例研究中，