电动载货自行车通勤者的运动模式——来自实地实验和轨迹分析的初步见解

A. Keler, Lisa Kessler, Fabian Fehn, K. Bogenberger
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引用次数: 1

摘要

摘要除了SERVUS项目之外,在“电动货运自行车-配套研究”项目中,通过有针对性的科学应用潜力分析,确定了对新型、敏捷的城市电动货运自行车的需求。然后在SERVUS项目的敏捷开发和生产过程中实现这些发现。在这个过程中建造了几个原型。这种新型的电子货运自行车应该既可以私人使用,也可以商业使用。它们将在活动中首次呈现给用户(IAA 2021),并由用户评分。此外,将单车长期分配给选定的使用者,可与现有的电子货运单车模式进行交叉比较。最后,以慕尼黑为例,对机动个人交通的替代潜力进行了估计和预测。收集关于特定电动载货自行车类型能力的进一步信息的关键是使用各种传感器设置的跟踪实验,其中第一次尝试在本研究中提出。此外,通过使收集的GNSS数据具有一定的空间精度,我们能够将这些车辆类型的选定机动与慕尼黑交通基础设施的选定类型相匹配。除了机动的轨迹形状外,我们还能够根据每次被检查的机动在选定城市位置的调查区域和时间(例如,在有和没有交通信号灯的不同十字路口几何形状),将旅行时间和延迟变化纳入其中。另一个方面是自行车基础设施的存在及其与使用混合交通模式的选择的关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Movement Patterns of Electric Cargo Bike Commuters – First Insights from Field Experiments and Trajectory Analyses
Abstract. In addition to and parallel to the SERVUS project, the requirements for a new, agile, urban cargo bicycle with electric drive are identified through a targeted, scientific application potential analysis in the project "E-Cargo Bike - Accompanying Research" described here. These findings are then implemented in the SERVUS project in an agile development and production process. Several prototypes are built in the process. The new e-cargo bicycles should be able to be used both privately and commercially. They will be presented to users for the first time at events (IAA 2021) and rated by them. In addition, the longer-term allocation of the bikes to selected users enables a cross-comparison with existing e-cargo bicycle models. Finally, the substitution potential of journeys in motorized individual transport is estimated and projected using the example of Munich. A key for gathering further information on the abilities of specific electric cargo bike types is tracking experiments with various sensor setups of which the first attempts are presented in this research. Additionally, and by enabling a certain spatial accuracy of gathered GNSS data, we are able to match selected maneuvers of these vehicle types to selected types of the Munich transportation infrastructure. Besides trajectory shapes of maneuvers, we are able to incorporate travel time and delay variations depending on investigation areas and times of the day at selected urban locations for every inspected maneuver (at for examples differing intersection geometries with and without traffic light signals). Another aspect is the presence of bicycle infrastructure and its relation to the option of using mixed traffic modes.
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