| 基于细节层次模型的公共自行车调度方法 |
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| 引用本文： | 胡正华,周继彪,周涵林,张敏捷.基于细节层次模型的公共自行车调度方法[J].交通信息与安全,2022,40(4):148-156. |
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| 作者姓名： | 胡正华 周继彪 周涵林 张敏捷 |
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| 作者单位： | 1.宁波工程学院建筑与交通工程学院 浙江 宁波 315211 |
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| 基金项目： | 国家自然科学基金项目52002282浙江省自然科学基金项目LQ18D010008浙江省哲学社会科学规划课题项目21NDJC163YB浙江省哲学社会科学规划课题项目22NDQN279YB |
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| 摘 要： | 公共自行车系统作为城市公共交通的重要组成部分，对于缓解城市交通拥堵和建设低碳、环保的出行体系起到了积极的作用。然而，由于公共自行车系统的借还车需求在时间和空间分布上存在不均衡性，在使用公共自行车时，经常遇到“借车难”或者“还车难”的问题，使得出行者不得不放弃使用公共自行车出行。为了有效地提升出行者借还公共自行车的成功率，研究了1种基于细节层次模型的自行车调度方法。基于公共自行车站点之间的相似度，采用谱聚类算法对站点进行层次划分，形成基于空间范围（即公共自行车站点所占据的地理空间区域）的站点簇；在每个划分层级上统计不同簇之间的自行车借/还需求，结合遗传算法对调度车辆的运输路径进行求解；将不同层级上的调度方案叠加，形成1种调度粒度由粗到细的自行车调度方案。通过对比实验证明:基于细节层次模型的公共自行车调度方法较传统方法减少了42.70%的调度路径，进而减少了相应的调度时间。
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| 关 键 词： | 交通工程 调度策略 公共自行车 层次调度 |
| 收稿时间： | 2021-12-15 |
A Dispatch Strategy for Shared Bicycles Based on a Levels-of-Detail Model |
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| Affiliation: | 1.School of Civil and Transportation Engineering, Ningbo University of Technology, Ningbo 315211, Zhejiang, China2.College of Information Science & Electronic Engineering, Zhejiang University, Hangzhou 310027, China3.School of Transportation Engineering, Tongji University, Shanghai 201804, China |
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| Abstract: | As an important part of urban public transportation, the shared bicycles have played a positive role in relieving traffic congestion and promoting a low-carbon, environmentally friendly travel system. However, people often encounter difficulties with borrowing or returning a bicycle when tending to use shared bicycles, due to the uneven temporal and spatial distributions of the demands of borrowing and returning bicycles. Such difficulties sometimes make travelers give up using shared bicycles. In order to effectively improve the success rate of borrowing and returning bicycles, a dispatch strategy based on a levels-of-detail model is proposed. First, based on the similarity among bicycles stations, a spectral clustering algorithm is adopted to hierarchically classify the areas where stations locate. Thus, station clusters are formed based on station scopes (i.e., the geographic spatial area of a public station occupied). Second, the total demand of borrowing/returning bicycles among different station clusters at each level is counted, and a genetic algorithm is adopted to solve the transport route for dispatch vehicles. Third, the dispatch strategies at each level are overlaid to form a dispatch strategy for shared bicycles with the granularity from coarse to fine. Compared with the traditional methods, the proposed strategy reduces the total length of dispatch path by 42.70%, and therefore the corresponding dispatch time can also be shortened accordingly. |
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