Development and transport implications of automated vehicles in the Netherlands: scenarios for 2030 and 2050

Dimitris Milakis · Maaike Snelder · Bart van Arem · Bert van Wee · Gonçalo Homem de Almeida Correia

220 citations0/0 files storedEuropean journal of transport and infrastructure research

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Transportation and Mobility Innovations Transportation Planning and Optimization Electric Vehicles and Infrastructure

Abstract

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.

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References

1995Scenario planning: a tool for strategic thinking 2014Public Opinion on Automated Driving: Results of an International Questionnaire Among 5,000 Respondents 2014The travel and environmental implications of shared autonomous vehicles, using agent-based model scenarios 2005The origins and evolution of scenario techniques in long range business planning 1996The Art of the Long View: Planning for the Future in an Uncertain World 2012A review of scenario planning 2015Autonomous Vehicle Implementation Predictions: Implications for Transport Planning 2016Autonomous Vehicle Technology: A Guide for Policymakers

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