Development and transport implications of automated vehicles in the Netherlands: scenarios for 2030 and 2050
By Dimitris Milakis, M. Snelder, B. van Arem, Bert van Wee, Gonçalo Homem de Almeida Correia. European Journal of Transport and Infrastructure Research, 2017
177 citations recorded by the source corpus.
Automated driving technology is emerging. Yet, little is known in the literature about when automated vehicles will reach the market, how penetration rates will evolve and to what extent this new transport technology will affect transport demand and planning. This study uses scenario analysis to identify plausible future development paths of automated vehicles in the Netherlands and to estimate potential implications for traffic, travel behaviour and transport planning on a time horizon up to 2030 and 2050. The scenario analysis was performed through a series of three workshops engaging a group of diverse experts. Sixteen key factors and five driving forces behind them were identified as critical in determining future development of automated vehicles in the Netherlands. Four scenarios were constructed assuming combinations of high or low technological development and restrictive or supportive policies for automated vehicles (AV …in standby, AV …in bloom, AV …in demand, AV …in doubt). According to the scenarios, fully automated vehicles are expected to be commercially available between 2025 and 2045, and to penetrate the market rapidly after their introduction. Penetration rates are expected to vary among different scenarios between 1% and 11% (mainly conditionally automated vehicles) in 2030 and between 7% and 61% (mainly fully automated vehicles) in 2050. Complexity of the urban environment and unexpected incidents may influence development path of automated vehicles. Certain implications on mobility are expected in all scenarios, although there is great variation in the impacts among the scenarios. Measures to curb growth of travel and subsequent externalities are expected in three out of the four scenarios.
Subfields: Automotive Engineering, Transportation
View Paper: https://www.semanticscholar.org/paper/8cef2a354eb5696833bc20cd58893387da616d8b
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Automotive Engineering
In Transportation
- Dimitris Milakis
- B. van Arem
- Araz Taeihagh
- Bert van Wee
- Frank Witlox
- J. De Vos
- Veronique Van Acker
- Tim Schwanen
Citations in the corpus
- Governing autonomous vehicles: emerging responses for safety, liability, privacy, cybersecurity, and industry risks (2018, background): “This is because while AVs potentially pose other risks such as to levels of congestion, the environment, land use, public infrastructure investment, government revenues or even organ shortage (Brodsky, 2016; Milakis et al., 2017; Bischoff & Maciejewski, 2016; Clements & Kockelman, 2017), these risks”
- Policy and society related implications of automated driving: A review of literature and directions for future research (2017, background): “Milakis et al. (2017) reported a possible VMT increase between 3% and 27% for various scenarios of development of automated vehicles in the Netherlands.”