Towards a quantitative method to analyze the long-term innovation diffusion of automated vehicles technology using system dynamics

Abstract

This paper presents a novel simulation model that shows the dynamic and complex nature of the innovation system of vehicle automation in a quantitative way. The model simulates the innovation diffusion of automated vehicles (AVs) on the long-term. It looks at the system of AVs from a functional perspective and therefore categorizes this technology into six different levels. Each level is represented by its own fleet size, its own technology maturity and its own average purchase price and utility. These components form the core of the model. The feedback loops between the components form a dynamic behavior that influences the diffusion of AVs. The model was applied to the Netherlands both for a base and an optimistic scenario (strong political support and technology development) named "AV in-bloom". In these experiments, we found that the system is highly uncertain with market penetration varying greatly with the scenarios and policies adopted. Having an 'AV in bloom' ecosystem for AVs is connected with a great acceleration of the market take-up of high levels of automation. As a policy instrument, a focus on more knowledge transfer and the creation of an external fund (e.g. private investment funds or European research funds) has shown to be most effective to realize a positive innovation diffusion for AVs. Providing subsidies may be less effective as these give a short-term impulse to a higher market penetration, but will not be able to create a higher market surplus for vehicle automation.

Patterns of knowledge development and diffusion in the global autonomous vehicle technological innovation system: a patent-based analysis

“…The innovation system and functional perspective has recently begun to be used in studies of AV technology (e.g., Yun et al, 2016;Nieuwenhuijsen et al, 2018). Quite a few authors have tried to characterise the dynamics of knowledge development or diffusion within an AV TIS.…”

“…Third, previous studies have only examined single aspects of knowledge development. Regarding knowledge diffusion, although Yun et al (2016) and Nieuwenhuijsen et al (2018) have studied how AV innovation flows from the technology domain into the market, there is a lack of empirical analysis of patterns of knowledge diffusion within the AV TIS. Fourth, existing studies on AV patents have mostly adopted a static perspective, without investigating how AV patents evolved over time.…”

Technology: A Necessary but Not Sufficient Condition for Future Personal Mobility

“…On freeways, platooning could be a mode of cooperation with high potential, as AVs could drive at high speeds with very small spacings (as if they were a road train) without compromising safety. Similarly to single AVs, platoons require their own management strategies, especially in a mixed-traffic situation [47,48]. Some initiatives have already been outlined, but have not been completely defined.…”

Finding the relevance of staff-based vehicle relocations in one-way carsharing systems through the use of a simulation-based optimization tool

“…Therefore, in one-way systems rebalancing is necessary. The introduction of automated vehicles in the future has the potential to facilitate this task and reduce operational costs (Correia & Arem, 2016;Milakis, Arem, & Wee, 2017), although this is still an emerging technology (Nieuwenhuijsen, Correia, Milakis, Arem, & Daalen, 2018). This study considers the carsharing vehicles' technology currently in use by carsharing companies, which is mostly nonautomated.…”