Modelling Driver Decisions to Improve Port Traffic Management During Critical Situations

EasyChair Preprint no. 5784

Abstract

According to Flach & Voorhorst (2020) effective management of real-world situations can be achieved by treating human decisions according to meaning processing approaches to cognition. We describe a System Theoretic Process Analysis (STPA) of traffic management in a busy port area of the Netherlands. Reflecting on the meaning processing approach to cognition, we then generate and test a new set of prompts that the STPA analyst can use as they generate scenarios that to explain why human actors would carry out unsafe control actions. Then new prompts help the analyst consider the human controller as an individual embedded and in a dynamic ecology, with perceptions and actions emerging from interactions with that ecology. They help consider people as perceivers of affordances rather than whole processes; and as aware of the meaning of actions for several valued goals. On applying the new prompts to the port traffic management case, new insight was generated concerning how truck drivers will act to perceive (and not just perceive to act), seek out "workarounds" in the face of terminal closures, and attend to information that helps them decide whether diverting or ignoring diversions is most likely to lead to punctual delivery. While extending STPA analysis to account for the meaning processing approach, demands greater resource and understanding, there will be occasions when a less superficial approach to human control is desired by STPA practitioners.

Keyphrases: human adaptive control, meaning processing, port, STPA, System Theoretic Process Analysis, truck driver

@Booklet{EasyChair:5784,
  author = {Ross Phillips and Samaneh Rezvani and Ben Rutten},
  title = {Modelling Driver Decisions to Improve Port Traffic Management During Critical Situations},
  howpublished = {EasyChair Preprint no. 5784},

  year = {EasyChair, 2021}}