  Lane change is a very demanding driving task and number of traffic accidents
are induced by mistaken maneuvers. An automated lane change system has the
potential to reduce driver workload and to improve driving safety. One
challenge is how to improve driver acceptance on the automated system. From the
viewpoint of human factors, an automated system with different styles would
improve user acceptance as the drivers can adapt the style to different driving
situations. This paper proposes a method to design different lane change styles
in automated driving by analysis and modeling of truck driver behavior. A truck
driving simulator experiment with 12 participants was conducted to identify the
driver model parameters and three lane change styles were classified as the
aggressive, medium, and conservative ones. The proposed automated lane change
system was evaluated by another truck driving simulator experiment with the
same 12 participants. Moreover, the effect of different driving styles on
driver experience and acceptance was evaluated. The evaluation results
demonstrate that the different lane change styles could be distinguished by the
drivers; meanwhile, the three styles were overall evaluated as acceptable on
safety issues and reliable by the human drivers. This study provides insight
into designing the automated driving system with different driving styles and
the findings can be applied to commercial automated trucks.
