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内罗毕摩托车运输比较数据集:燃油与电动汽车性能追踪(2023年)

Nairobi motorcycle transit comparison dataset: Fuel vs. electric vehicle performance tracking (2023).

作者信息

Mbutura Alois, Kitetu Martin, Stratford Halloran, Booysen M J

机构信息

EED Advisory Ltd, 50 Hamisi Rd, Nairobi 00100, Kenya.

Clean Air Taskforce, 114 State Street, 6th Floor, Boston, MA 02109, USA.

出版信息

Data Brief. 2025 Jun 19;61:111805. doi: 10.1016/j.dib.2025.111805. eCollection 2025 Aug.

DOI:10.1016/j.dib.2025.111805
PMID:40673186
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12266508/
Abstract

This dataset, titled "Nairobi Motorcycle Transit Comparison Dataset," was compiled to document a simulated transition of motorcycle taxis (boda bodas) in Nairobi, Kenya, from internal combustion engine (ICE) to electric motorcycles. The data collection spanned two distinct phases. The baseline phase, conducted from November 13-26, 2023, involved 120 ICE motorcycles. The transition phase, occurring from December 10-21, 2023, included 110 ICE motorcycles as a control group and 9 electric motorcycles as a treatment group. Data were gathered in Nairobi, a major urban center in East Africa, providing a geographically specific context for the data collection. Recognising the limited availability of data on such transitions in African cities, including historical insights from Kenyan urban transport systems [3,5,6], this dataset provides a unique resource for researchers and policymakers. The data collection process utilised multiple instruments and methods. Trip-level data were recorded using GPS tracking devices installed on each motorcycle, capturing location, speed, and distance at 10-second intervals. Financial data, such as revenue, maintenance costs, fuel costs (for ICE motorcycles), and electricity usage (for electric motorcycles), were collected via daily phone-based surveys administered to riders. Energy consumption for the electric motorcycles was measured using wall-plug meters connected to each battery charger. These methods ensured comprehensive tracking of both operational and economic metrics across the two motorcycle types. The dataset is organised into two primary directories: trip_data and daily_data. The trip_data directory contains CSV files with detailed trip-level metrics, including start and end times, distances travelled, and average speeds. The daily_data directory provides aggregated daily summaries in CSV format, encompassing total distance, revenue, and costs. To safeguard rider privacy, location data for the first and last trips of each day are excluded. The dataset is hosted on Mendeley, with a publicly accessible URL provided below, ensuring availability for researchers, editors, and reviewers. This dataset holds substantial reuse potential for various research domains. It offers a valuable resource for investigating urban mobility patterns, the adoption of e-mobility in developing cities, energy demand forecasting, and transportation economics. Researchers can leverage the data to explore operational differences between ICE and electric motorcycles, evaluate economic impacts on riders, or model energy consumption trends.

摘要

这个数据集名为“内罗毕摩托车交通比较数据集”,其编制目的是记录肯尼亚内罗毕的摩托车出租车(摩的)从内燃机(ICE)摩托车向电动摩托车的模拟转变情况。数据收集跨越两个不同阶段。基线阶段于2023年11月13日至26日进行,涉及120辆ICE摩托车。转变阶段于2023年12月10日至21日发生,包括110辆ICE摩托车作为对照组和9辆电动摩托车作为处理组。数据在内罗毕收集,内罗毕是东非的一个主要城市中心,为数据收集提供了特定的地理背景。鉴于非洲城市此类转变的数据有限,包括来自肯尼亚城市交通系统的历史见解[3,5,6],该数据集为研究人员和政策制定者提供了一个独特的资源。数据收集过程使用了多种工具和方法。行程级数据通过安装在每辆摩托车上的GPS跟踪设备记录,以10秒的间隔捕捉位置、速度和距离。财务数据,如收入、维护成本、燃料成本(针对ICE摩托车)和电力使用情况(针对电动摩托车),通过每天对骑手进行的基于电话的调查收集。电动摩托车的能源消耗使用连接到每个电池充电器的墙上插座电表进行测量。这些方法确保了对两种摩托车类型的运营和经济指标进行全面跟踪。该数据集被组织成两个主要目录:行程数据和每日数据。行程数据目录包含带有详细行程级指标的CSV文件,包括开始和结束时间、行驶距离和平均速度。每日数据目录以CSV格式提供汇总的每日摘要,包括总距离、收入和成本。为保护骑手隐私,每天第一次和最后一次行程的位置数据被排除。该数据集托管在Mendeley上,下面提供了一个可公开访问的URL,确保研究人员、编辑和审稿人都能获取。这个数据集在各个研究领域具有很大的重用潜力。它为调查城市交通模式、发展中城市电动出行的采用情况、能源需求预测和交通经济学提供了宝贵资源。研究人员可以利用这些数据探索ICE摩托车和电动摩托车之间的运营差异,评估对骑手的经济影响,或模拟能源消耗趋势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b7/12266508/d8863049b957/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b7/12266508/0511a3f21d15/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b7/12266508/d1ff1f9efd69/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b7/12266508/8ca8606709ae/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b7/12266508/d8863049b957/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b7/12266508/0511a3f21d15/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b7/12266508/d1ff1f9efd69/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b7/12266508/8ca8606709ae/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b7/12266508/d8863049b957/gr4.jpg

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