New forms of shared mobility such as free-floating car-sharing services and shared automated vehicles have the potential to change urban travel behaviour. In this paper, we identify potential user classes for these new modes. For this, a stated choice experiment on mode choice among a sample of the Dutch urban population has been conducted, which features free-floating car-sharing and shared automated vehicles next to private vehicles, bus, and taxi. The experimental design allows disentangling the effects of vehicle ownership, vehicle sharing and vehicle automation on the perceived utility of these modes. Further contributions lie in the identification of user classes for shared and automated mobility services and their potential migration from their current modes to the these services. Latent class choice models were estimated to capture the heterogeneity in these preferences among the respondents. The most explanatory mode choice model is obtained by estimating a 3-class nested logit model capturing the impact of vehicle ownership. The results show that higher educated and more time-sensitive respondents are more inclined than others to favour the (automated) car-sharing options. By simulating a scenario that directly compares car with free-floating car-sharing and taxi with shared automated vehicles, a migration analysis has been performed. This analysis shows that the preferences towards shared automated vehicles and free-floating car-sharing is highest for those currently combining car and public transport for their commute. Commuters using the car showed a high preference towards free-floating car-sharing, in particular as for the latter no parking fees are issued. Respondents currently commuting by public transport showed the lowest preference for the new modes.

中文翻译：

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识别共享和自动移动服务的用户类别

自由浮动的汽车共享服务和共享的自动驾驶汽车等新型的共享出行方式有可能改变城市出行行为。在本文中，我们确定了这些新模式的潜在用户类别。为此，已经进行了一项在荷兰城市人口样本中进行模式选择的既定选择实验，该实验的特点是自由浮动的汽车共享和共享自动驾驶汽车，旁边是私人车辆，公共汽车和出租车。实验设计允许解开车辆所有权，车辆共享和车辆自动化对这些模式的感知效用的影响。进一步的贡献在于识别共享和自动移动服务的用户类别，以及他们从当前模式到这些服务的潜在迁移。估计潜在的班级选择模型可以捕捉受访者在这些偏好方面的异质性。通过估计3类嵌套logit模型来获得最具解释性的模式选择模型，该模型捕获了车辆所有权的影响。结果表明，受教育程度较高和时间敏感的受访者比其他受访者更倾向于（自动）汽车共享选项。通过模拟直接将汽车与自由浮动汽车共享以及共享自动车与出租车进行比较的场景，进行了迁移分析。该分析表明，对于目前通勤结合了汽车和公共交通工具的人们，共享自动驾驶汽车和自由浮动汽车共享的偏好最高。使用汽车的通勤者非常喜欢自由浮动的汽车共享，特别是后者，不收取停车费。目前乘坐公共交通工具上下班的受访者对新模式的偏好最低。