Lime Micromobility Vehicle Dataset – Scooters by App & Location

**Overview** This dataset is a sample micromobility records collected from shared mobility applications (e.g., scooters, bikes, or compact EV rentals). It contains detailed, structured information about each available vehicle at the time of extraction, including: - 🗺️ Geolocation & Positioning: Vehicle latitude and longitude, proximity center coordinates, auto-ring and proximity radii, remaining range in miles. - 💰 Pricing Information: Hire price, price per minute, and additional dynamic pricing metadata. - 🚗 Vehicle & App Attributes: Title, type, app/platform name, vehicle availability logic, and available actions. - 📊 Usage Context & Distance Logic: Distance remaining, distance to proximity center, and assigned range category. **Use Case Examples** - 🔍 Urban Mobility Analytics: Track availability and distribution of vehicles by zone, provider, and proximity logic. - 📈 Pricing Optimization: Analyze pricing strategies per distance, location, or time of day. - 🌍 Geospatial Modeling: Use in simulations, heatmaps, or coverage analysis for smart cities and transportation planning. - 🤖 Machine Learning Features: Feed into demand forecasting models, pricing recommendation engines, or geofencing behavior predictors. - 📡 Mobility Platform Benchmarking: Compare how different apps implement vehicle availability logic and pricing rules. **Sample Size & Customization** This sample features 1,000 records of Lime e-scooters available in the City of London. We offer full customization based on your project needs, including: - Data volume (up to full-scale vehicle availability datasets). - Update frequency (daily, weekly, or near real-time). - Schema adaptation or field selection. We can provide data from a wide range of shared mobility apps and services, including but not limited to: **Lime**, **Bolt**, **Spin**, **ofo**, **TIER Mobility**, **Voi Technology**, **Dott**, **micromobility.com**, **BinBin**, **Marty Technologies**, **Bird**, **Circ**, **Veo**, **Wheels**, **nextbike**, **HOP**, **NAVEE TECH**. Need a specific service or app not listed above? We can expand the source list to include additional platforms relevant to your project. 📩 Contact us to define your data needs — our team can create a custom listing tailored to your specific use case and schema preferences.**数据集概览** 本数据集为从共享出行应用（如电动滑板车、自行车或紧凑型电动车辆租赁服务）采集的微移动出行（micromobility）样本记录，包含采集时刻下各可用车辆的详细结构化信息，具体涵盖以下类别： - 📍 地理位置与定位信息：车辆纬度与经度、邻近中心坐标、自动鸣响（auto-ring）参数及邻近半径、剩余续航里程（单位：英里）。 - 💰 定价信息：租赁基础费用、每分钟计费标准及额外动态定价元数据。 - 🚗 车辆与应用属性：车辆名称、类型、所属应用/平台名称、车辆可用逻辑及可执行操作。 - 📊 使用场景与距离逻辑：剩余续航距离、至邻近中心的距离及分配的续航类别。 **典型应用场景** - 🔍 城市出行分析：按区域、服务商及邻近逻辑追踪车辆的可用状态与分布情况。 - 📈 定价优化：基于距离、地理位置或时段分析定价策略。 - 🌍 地理空间建模：可用于智慧城市与交通规划中的仿真、热力图绘制或覆盖范围分析。 - 🤖 机器学习特征：可输入至需求预测模型、定价推荐引擎或地理围栏行为预测器中。 - 📡 出行平台基准对比：对比不同应用实现车辆可用逻辑与定价规则的方式。 **样本规模与定制服务** 本样本包含伦敦市范围内1000条**Lime**电动滑板车的可用记录。我们可根据您的项目需求提供全流程定制服务，具体涵盖以下内容： - 数据规模（最高可提供全量车辆可用数据集）。 - 更新频率（每日、每周或近乎实时）。 - 适配自定义数据结构（schema）或选择指定字段。 我们可提供来自众多共享出行应用与服务的数据，包括但不限于：**Lime**、**Bolt**、**Spin**、**ofo**、**TIER Mobility**、**Voi Technology**、**Dott**、**micromobility.com**、**BinBin**、**Marty Technologies**、**Bird**、**Circ**、**Veo**、**Wheels**、**nextbike**、**HOP**、**NAVEE TECH**。 若您需要上述列表未涵盖的特定服务商或应用数据，我们可扩展数据源列表，纳入符合您项目需求的其他平台。 📩 请联系我们明确您的数据需求——我们的团队可根据您的特定应用场景与数据结构偏好，为您定制专属的数据清单。

搜集汇总

背景与挑战

背景概述

该数据集包含Lime共享电动滑板车的详细记录，涵盖地理位置、定价信息、车辆属性及使用上下文等关键数据，适用于城市交通分析、定价优化和地理空间建模等多种应用。数据集覆盖欧洲，每日更新，样本量为1,000条记录，并支持定制化需求。