The understanding of rider/vehicle interaction modalities remains an issue, specifically in the case of bend-taking. This difficulty results both from the lack of adequate instrumentation to conduct this type of study and from the variety of practices of this population of road users. Riders have numerous explanations of strategies for controlling their motorcycles when taking bends. The objective of this paper is to develop a data-driven methodology in order to identify typical riding behaviors in bends by using clustering methods. The real dataset used for the experiments is collected within the VIROLO++ collaborative project to improve the knowledge of actual PTW riding practices, especially during bend taking, by collecting real data on this riding situation, including data on PTW dynamics (velocity, normal acceleration, and jerk), position on the road (road curvature), and handlebar actions (handlebar steering angle). A detailed analysis of the results is provided for both the Anderson–Darling test and clustering steps. Moreover, the clustering results are compared with the subjective data of subjects to highlight and contextualize typical riding tendencies. Finally, we perform an in-depth analysis of the bend-taking practices of one subject to highlight the differences between different methods of controlling the motorcycle (steering handlebar vs. rider’s lean) using the rider action measurements made by pressure sensors.

中文翻译：

---

深入的两轮骑行行为聚类分析

骑手/车辆交互方式的理解仍然是一个问题，特别是在弯道时。造成这种困难的原因既有缺乏进行这类研究所需的仪器，也有这种道路使用者的做法多种多样。骑手在弯道时对摩托车控制策略的解释很多。本文的目的是开发一种数据驱动的方法，以通过使用聚类方法来识别弯道中的典型骑行行为。在VIROLO ++合作项目中收集了用于实验的真实数据集，以通过收集有关这种骑行状况的真实数据（包括有关PTW动力学数据（速度，法向加速度和混蛋），在道路上的位置（道路曲率）和车把动作（车把转向角）。为安德森–达林检验和聚类步骤提供了对结果的详细分析。此外，将聚类结果与受试者的主观数据进行比较，以突出并关联典型的骑行倾向。最后，我们对一个主题的弯道练习进行了深入分析，以强调使用压力传感器进行的骑手动作测量来控制摩托车的不同方法之间的差异（转向把手与骑手的倾斜）。将聚类结果与受试者的主观数据进行比较，以突出并关联典型的骑行倾向。最后，我们对一个主题的弯道练习进行了深入分析，以强调使用压力传感器进行的骑手动作测量来控制摩托车的不同方法之间的差异（转向把手与骑手的倾斜）。将聚类结果与受试者的主观数据进行比较，以突出并关联典型的骑行倾向。最后，我们对一个主题的弯道练习进行了深入分析，以强调使用压力传感器进行的骑手动作测量来控制摩托车的不同方法之间的差异（转向把手与骑手的倾斜）。