How the impacts of shared autonomous vehicles vary across different service designs and pricing strategies
by Lotte Notelaers | Gaurav Malik | Jeroen Verstraete | Chris Tampère | KU Leuven | KULeuven | KU Leuven | KU Leuven
Abstracte ID: 56
Topic: Modellen in transitie
Presenter Name:
Keywords: Mobility-on-Demand, Multi-Modal Transportation, Shared Autonomous Vehicles, Shared Mobility

Although vehicle automation presents unique opportunities, governments are concerned automated mobility services (AMS) might attract people from more sustainable modes, such as walking and biking, and people might start traveling more.

Most existing studies on the impacts of AMS are largely driven by a technology push: what happens if a particular type of AMS enters a given region as a one-size-fits-all solution. Most studies presume that the selected AMS will be used by a specific submarket of travel demand or, even more naïve, for all trips and hence neglect the competition with other available modes. Furthermore, all studies merely evaluated the performance of AMS in terms of operational efficiency or sustainability based on KPIs, without considering the reactions and optimization behavior of the operators and/or government in actually stimulating, or counteracting the deployment within the market. To develop successful policies aimed at realizing the advantages of vehicle automation, a better understanding of how AVs may be deployed in a certain context is necessary.

This research contributes to this gap by exploring a case study in which a station-based SAV service would be deployed in Leuven, Belgium. To enable the adequate modeling of the scenario, a simulation framework is developed consisting of a multi-modal equilibrium assignment integrated with the Demand Responsive Transport module of PTV Visum. This allows us to estimate the market share of SAVs depending on their level of service and competition with other modes. Moreover, within this simulation framework also the behavior of the SAV service provider and government are modeled. The price setting of the SAV service is endogenously optimized while the government can decide on taxing or subsidizing the SAV service. While analyzing the results, special focus is given to investigating the heterogeneity of modal shifts and SAV uptake as a result of the design of the service. These insights provide a better understanding of how a service design could be refined to obtain a socially more preferable implementation of SAVs in terms of modal shifts and how policymaking could play a role in this.