Scenarios of automated driving based on a switchboard for driving forces - an application to the Netherlands - Maaike Snelder; Koen de Clercq; Gonçalo Homem de Almeida Correia; Maarten 't Hoen; Irene Martinez; Shadi Sharif Azadeh; Bart van Arem (European Journal of Transport and Infrastructure Research)
Over the past decade many developments have taken place in the field of automation of cars, trucks and public transport. The penetration rate of Level 2 partially automated vehicles in mixed traffic is increasing, Level 3 conditional automation is now supported by legislation, and different experimental and commercial applications of Level 4 high automation in mixed traffic exist. This shows that automated driving developments should be considered when making decisions about investments in physical and digital infrastructure. However, there are still many uncertainties regarding future penetration rates, the level of connectivity, the operational design domain, and the expected impacts of automated driving. This paper proposes four scenarios for automated driving developments in the Netherlands in 2040 and 2060: 1) Late transition, 2) Automated vehicles on main roads, 3) Car-topia, and 4) Share-topia. To derive these scenarios, a new “switchboard” method is introduced in which multiple driving forces for automated driving can be varied. The main driving forces were identified based on expert surveys. For each scenario, a modelling approach is used to compute the impact of automated driving on vehicle kilometres driven and congestion. The switchboard method offered more flexibility than existing scenario methods. The model-based impact assessment provided more conservative and probably more accurate insights into the expected impacts of automated driving on vehicle kilometres driven and congestion than expert estimates from the literature. The results show that in all scenarios automation leads to an increase in the number of trips, vehicle kilometres driven and congestion. In the scenarios with autonomous vehicles, congestion is expected to increase up to 17%. The higher the penetration rates of connected automated vehicles, the smaller the increase in congestion (1.5% -11%). The results indicate that investments in digital infrastructure are needed to prevent capacity reduction due to autonomous driving. The scenarios “car-topia” and “share-topia” may require additional physical infrastructure on motorways and regional roads.