Abstract: To address the issue of insufficient matching between current vehicle drive cycle standards and the actual traffic operation characteristics of local areas, this study focuses on a typical bus route in Taiyuan (route 849) and proposes a method for constructing localized drive cycle by considering road segment complexity (congested sections, slopes, etc.). Actual operational data are collected using GPSpro equipment, and based on the short-trip segmentation theory, 529 valid kinematic segments are extracted. Fifteen characteristic parameters, including average speed and acceleration standard deviation, are used to construct a feature matrix. Principal component analysis is applied for dimensionality reduction of the features, and the K-means clustering algorithm is used to classify the segments into three typical driving patterns: congested, normal, and smooth. Finally, by combining 12 representative short trips, a localized drive cycle curve conforming to the operational characteristics of urban buses in Taiyuan is constructed. Verification shows that the relative errors of various characteristic parameters between the constructed drive cycle and the original test data are all below 8%, indicating that this method can effectively reflect the real operational status of regional buses and provide data support for vehicle selection, energy consumption assessment, and route optimization.

Key words: drive cycles; principal component analysis; cluster analysis; bus routes; localization modeling

摘要： 针对现行汽车行驶工况标准与地方交通实际运行特征匹配度不足的问题，研究以太原 市典型公交线路（849 路）为对象，结合路段复杂性（拥堵区段、坡道等），提出一种本地化 行驶工况构建方法。通过 GPSpro 设备采集实际运行数据，基于短行程划分理论提取 529 个有 效运动学片段，并选取平均车速、加速度标准差等 15 项特征参数构建特征矩阵。采用主成分 分析对特征维度进行降维，并运用 K-means 聚类算法将片段划分为拥堵、一般与通畅三类典 型行驶模式。最终，通过组合筛选出的 12 个代表性短行程，构建出符合太原市区公交运行特 征的本地化工况曲线。经验证，构建工况与原始试验数据在各项特征参数上的相对误差均低 于 8%，表明该方法能有效表征区域公交真实运行状态，可为车辆选型、能耗评估及线路优化 提供数据支持。

关键词: 行驶工况；主成分分析；聚类分析；公交线路；本地化建模