## 6 Conclusions  
This study aimed to propose a path-planning method considering characteristics of passenger tolerance to approaching pedestrians in crowded environments to realize efficient autonomous navigation without increasing passenger discomfort. First, data collection and data analysis were done to clarify the characteristics of passenger tolerance. Next, considering the characteristics, a path-planning method that can achieve short travel time by suppressing avoidance behavior to tolerable pedestrians was proposed. Finally, the usefulness of the proposed method was evaluated based on numerical simulations under multiple pedestrian density conditions. As a result of the above, the following findings were obtained. * The curvature radius of the pedestrian trajectory and passing distance between the pedestrian, predicted from the passenger's perspective, affect passenger tolerance. When the PMV does not perform avoidance behavior, the passenger can tolerate an approaching pedestrian if the passing distance is long, and the pedestrian's trajectory is straight. * Considering the characteristics of passenger tolerance, the proposed path-planning method for autonomous navigation has the potential to reduce the travel time to reach the destination without increasing passenger discomfort. Furthermore, by selecting paths that do not obstruct pedestrian flow, the number of collisions with pedestrians can also be reduced, and safety can be improved. This study conducted experiments using young healthy participants to understand basic passenger tolerance characteristics, minimizing the influence of differences in visual and cognitive performance. However, because visual acuity and cognitive function deteriorate with age, there may be differences between young and older passengers, who represent the primary user group of PMVs, in the way they feel discomfort and in their tolerance characteristics toward approaching pedestrians. Furthermore, while this study demonstrated that efficient autonomous navigation could be achieved by considering passenger tolerance in the targeted environments, various environmental factors, such as urban layouts and pedestrian densities, influence the path planning of the proposed method. For example, in environments with more complex shapes, such as corners, pedestrian movements are expected to be more dynamic compared to straight corridors. This could increase the likelihood of situations where the PMV needs to perform avoidance maneuvers for surrounding pedestrians. Thus, expanding the conditions for validation to consider various factors is essential to evaluate the range of applicability in real-world environments. Additionally, although the impact of the proposed method on passenger comfort was estimated with the PS invasion ratio in the simulation, it has not been directly assessed on how passengers feel about the proposed method. For autonomous navigation in real-world environments, addressing computational resource limitations is also essential. The proposed method accounts for the movement of all surrounding pedestrians. Then, if the process cannot keep up with considering all pedestrians in crowded scenarios, this issue should be addressed by narrowing the range of pedestrians recognized and considered in the path planning. Thus, our future work for social implementation includes investigating passenger tolerance characteristics among a larger size of participants, involving older individuals, and examining the applicability of the proposed method through more experiments with different conditions considering various environmental factors in real-world environments while ensuring safety. Conceptualization, M.O., H.Y., and M.S. ; methodology, software, M.O. ; validation, formal analysis, investigation, M.O. ; resources, M.O., H.Y., and M.S. ; data curation, M.O. ; writing--original draft preparation, M.O. ; writing--review and editing, H.Y. and M.S. ; visualization, M.O. ; supervision, H.Y. and M.S. ; project administration, M.S.