范文博,陈香,刘涛

• 1:西南交通大学
• 2:交通运输与物流学院

摘要(Abstract)：

本文针对基于模块化自动驾驶车的穿梭公交系统，研究其在过饱和状态下的服务频率、编组方案和车队规模的联合优化问题。首先，利用连续近似建模方法，构造了以系统总成本（包含乘客等待时间、车辆购置和运营成本）最小为目标的数学优化模型；其次，通过最优条件分析得到了最优服务频率和编组方案的解析解，并进一步得到最优车队规模；然后，利用离散化方法将以上最优解转化为具体的时刻表和满足整数约束的车辆编组方案；最后，通过数值实验和灵敏度分析，对模型和求解方法的有效性进行验证。实验结果表明所建立的连续近似优化模型具有较高的求解精度，与离散后的模型结果相比，系统总成本误差不超过3.24%。实验结果也揭示了不同离散方法的优劣与适用情况。与传统公交（固定车辆尺寸）对比表明模块化自动驾驶穿梭公交的系统总成本更低，且在低需求水平下优势更明显。

关键词(KeyWords)： 城市交通;模块化自动车;服务频率;车辆编组;车队规模;时刻表

Abstract:

Keywords:

基金项目(Foundation): 四川省科技计划项目（2020YFH0038）;; 国家自然科学基金项目（72271206,61903311）

作者(Author): 范文博,陈香,刘涛

DOI: 10.19961/j.cnki.1672-4747.2022.12.001

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