Identifying user classes for shared and automated mobility services

Konstanze Winter,Bart Van Arem,Karel Martens,Oded Cats

doi:10.1186/s12544-020-00420-y

Abstract

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.

Highlights

The progress in the development of new vehicle technology and digital communication technology is leading to the emergence of new types of vehicles and mobility services
This study contributes to building up a better understanding of the potential migration from the current modes to the new, shared transport services enabled by the developments in digital communication technology
4.1 Preferences for shared modes While stated choice experiments are an opportunity to capture preferences about novel alternatives, they bear the risk that uncertainty, expectations and current risk perception are influencing the choices made and respondents might develop a different attitude towards these modes once they become more familiar with them [25]

Summary

Introduction

The progress in the development of new vehicle technology and digital communication technology is leading to the emergence of new types of vehicles and mobility services. With the development of vehicle automation progressing rapidly and shared mobility gaining market shares, the question arises how the broad implementation of such concepts may change the transport service landscape. This study contributes to building up a better understanding of the potential migration from the current modes to the new, shared transport services enabled by the developments in digital communication technology. SAV can be described as a form of FFCS, in which vehicles travel autonomously, i.e. with no driver on board, transporting at least one passenger to its final destination. For FFCS and SAV, the act of vehicle sharing is a sequential one, as a ride is not shared with unknown passengers. These modes offer the same level of privacy as the private car. SAV bear a resemblance to current taxi services and ride-sourcing services in the way they are operated and are referred to as autonomous taxis or aTaxi [18]

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Conclusion