A quantitative analysis of potential impacts of automated vehicles in Austria using a dynamic integrated land use and transport interaction model

Abstract

ObjectiveDigitisation and automation are expected to change the transport system and settlement structures in a disruptive way. Due to new developments in sensor and communication technology different business models of automated vehicles (AV) - such as private AV, car-sharing-AV, ride-sharing-AV and public transport-AV – are likely to enter the transport market. Further, different penetration rates of AVs, extension of user groups (elderly and young, people without driving licenses etc.), different cost scenarios of AV veh-kms, parking regimes/fees, etc. will have significant impact on future transport demand. The objective of the work presented in this paper was to develop a simulation-based approach to analyse the potential impacts of different vehicle automation scenarios in Austria. MethodA multitude of complex cause-effect-chains and feedback loops characterise the relationship between AV take up, travel demand and environmental effects. The method of System Dynamics (SD) is designed to deal with such complexities. As a first step the qualitative method of Causal Loop Diagrams (CLD) was used to identify all potential automation related factors influencing the attractiveness of car and public transport use. In a second step the identified factors were coded into an operational version of the Stock-Flow based land use and transport interaction model MARS (Metropolitan Activity Relocation Simulator). As a third step sensitivity tests and scenarios were defined and simulated. Finally the resulting quantitative impacts were assessed and discussed. ResultsIn this paper we describe briefly how MARS was adapted to be able to simulate the effects of different AV-take up rates on the national level of Austria. Simulation results are presented for the scenario elements road capacity, remote parking, value of travel time, access for new user groups in the business models private car, car-sharing and ride-sharing and automation of the first and last mile in public transport. The results show that with a fleet share of 90% of private AVs in 2050, the nationwide changes in veh-kms travelled are between −2% (impact on road capacity) and +22 percent (new user groups in the case of AVs as private cars). Policy implicationsAn uncontrolled market take-up of AVs into the transport system will very likely increase the dependency on motorized transport, veh-kms driven and related emissions. Compensating policies have to be implemented in parallel to avoid un-sustainable developments.