Discusses the derivation of current changeover improvement methodologies from the work of the Japanese engineer/consultant Shigeo Shingo. Argues that under the interpretation and widespread adoption of the single minute exchange of dies (SMED) philosophy, substantive design‐based solutions are being overlooked in favour of incremental, low cost, team‐based approaches which emphasize organizational changes to the changeover. Identifies difficulties which can arise with existing approaches to changeover improvement and the relative merits of emphasis on design or organization are discussed. Pays particular attention to the problems which have been observed in sustaining levels of improvement.

To reduce the number of collision fatalities at crossroads intersections, many countries have started replacing intersections with non-signalized roundabouts, forcing the drivers to be more situationally aware and to adapt their behaviors according to the scenario. A non-signalized roundabout adds to the autonomous vehicle planning challenge, as navigating such interaction-dependent scenarios safely, efficiently, and comfortably has been a challenge even for human drivers. Unlike traffic signal-controlled roundabouts, where the merging order is centrally controlled, driving a non-signalized roundabout requires the individual actor to make the decision to merge based on the movement of other interacting actors. Most traditional autonomous planning approaches use rule-based speed assignment for generating admissible motion trajectories, which work successfully in non-interaction-based driving scenarios. They, however, are less effective in interaction-based scenarios as they lack the necessary ability to adapt the vehicle's motion according to the evolving driving scenario. In this paper, we demonstrate an adaptive tactical behavior planner (ATBP) for an autonomous vehicle that is capable of planning human-like motion behaviors for navigating a nonsignalized roundabout, combining naturalistic behavior planning and tactical decision-making algorithm. The human driving simulator experiment used to learn the behavior planning approach and the ATBP design is described in this paper. Index Terms-Adaptive tactical behaviour planner, adaptive control, human factors, naturalistic driving, trajectory planning. I. INTRODUCTION C URRENTLY autonomous or self-driving vehicles are at the heart of academia and industry research because of their multi-faceted advantages that include improved safety, reduced congestion, lower emissions, greater mobility etc. Significant advancement in digital technology (sensing, processing etc.) has pushed the autonomous technology in ground vehicle Manuscript

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