A generic multi-level framework for microscopic traffic simulation with automated vehicles in mixed traffic

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13 Citations (Scopus)
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With an increasing number of automated vehicles (AV) appearing on roads and interacting with conventional traffic, there is a need for improved simulation approaches to replicate and forecast the resulting effects. Interactions between AVs and their drivers, and interaction with other human drivers involve new types of complex behavioural processes. There is an increasing necessity to explicitly incorporate these human factor processes in simulation, which cannot be properly accounted for with most current models. In this paper, we present an extended conceptual simulation framework based on human factors processes and applicable for automated driving that does this. The framework makes use of previously constructed constructs to include the effects of driver task demand, situation awareness and fundamental diagrams of task demand to extend to automated driving. This is especially considered for the case of transition of control (ToC), as an important aspect of vehicle-driver interaction. The framework is demonstrated in two experimental cases that consider different ToC situations and is found to be face valid within the applied assumptions. Challenges remain in regard to a lack of quantitative evidence from traffic psychology, automated vehicle dynamics & control and human-vehicle interaction. With increasing amounts of research on-going in these areas, the extended framework will act as a valuable approach to further study and quantify the effects of AVs in mixed traffic in the future.
Original languageEnglish
Article numberTRC2522
Pages (from-to)291-311
Number of pages21
JournalTransportation Research Part C: Emerging Technologies
Publication statusPublished - 2020


  • Automated driving
  • Human factors
  • Traffic simulation
  • Vehicle automation


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