基于公交需求变化的柔性公交线网设计

发布时间：2019-01-15 20:41

【摘要】：城市的公交需求是随时间的变化而变化的,不同时期公交需求量和公交需求分布均会呈现不同的特征。公交网络运能的供给适应公交需求的变化,实现不同时间下需求和供给的良好匹配,是提升公交系统服务水平、减少公交运能浪费、提升社会整体利益的必要条件。当前公交线网设计一般依据单一固定的公交需求,缺少对公交需求变化的考虑,导致了公交网络难以有效应对公交需求的变化。本文分析了公交需求的长期及短期变化规律,发现短期需求变化有较明显的规律,可以把短期需求变化归纳成以一周为周期的波动变化过程,每周的需求变化可以通过七天的OD表来反映。公交需求变化的周期性波动规律,为科学设计公交线网提供了依据。为应对公交需求的变化,提出构建柔性公交网络以应对需求变化的方法。在给出柔性公交网络概念的基础上,分析了公交网络柔性的结构层次,把公交网络柔性分为缓冲柔性、适应柔性及创新柔性三个层次,分别反映公交网络理解需求、迎合需求及引导需求的能力,其中缓冲柔性是构建柔性公交网络的基础。重点研究了构建公交网络缓冲柔性的方法。在分析乘客、公交企业和社会三方利益诉求的基础上,以三方利益加权和最优为线网设计目标,以变化的公交需求矩阵为设计依据,提出公交线网设计的目标函数,建立了科学设计公交线网的多目标优化模型。模型通过乘客等车时间、超载运营时间、公交未利用运能时间、公交车队规模、乘客多耗用的时间以及未满足乘车需求的乘客数量等指标考虑各方的利益诉求,通过不同需求模式下的目标函数值计算,考虑公交线网对不同需求模式的适应性,并且以货币的形式对这种适应性的大小进行量化。通过模型的求解得到最优的线网,达到增强公交网络缓冲柔性的目的,提高公交网络应对需求变化的能力。公交线网设计模型的求解属于多目标优化问题,采用分步求解的算法,降低模型求解的复杂程度。算法以备选线路筛选为前提,以遗传算法搜寻为骨架。第一步在线路层面缩小求解空间,第二步在线网层面应用遗传算法寻找最优的线路组合,并对遗传算法引入最优个体选择及模拟退火拉伸两种改进措施,确保种群朝着理想目标进化。算例结果表明,在考虑公交需求变化的条件下,设计出的公交线网能够更好地适应需求的变化,具有应对需求变化的缓冲柔性。同时通过备选线路的筛选缩小公交线路的搜索空间,可以减少计算时间,加快遗传算法的收敛速度。
[Abstract]:The demand for public transport varies with time, and the distribution of demand for public transportation and public transportation will show different characteristics in different periods. The supply of transit network capacity adapts to the change of public transport demand and realizes the good matching of demand and supply at different times. It is a necessary condition to improve the service level of public transport system, reduce the waste of public transportation capacity and promote the overall interests of the society. The current bus network design is generally based on a single fixed public transport demand, the lack of consideration of the change of public transport demand, leading to the public transport network is difficult to effectively cope with the change of public transport demand. In this paper, the long-term and short-term changes of public transport demand are analyzed. It is found that the change of short-term demand has obvious regularity, and the short-term demand change can be summed up as a fluctuating process with a cycle of one week. Weekly changes in demand can be reflected in a seven-day OD table. The periodical fluctuation law of the change of public transport demand provides the basis for the scientific design of public transportation network. In order to cope with the change of public transport demand, the method of constructing flexible public transport network to cope with the change of demand is put forward. Based on the concept of flexible bus network, the paper analyzes the structure of flexible bus network, divides the flexibility of public transport network into three levels: buffer flexibility, adaptive flexibility and innovative flexibility, respectively, reflecting the understanding needs of public transport network. The ability to meet and guide the demand, of which buffer flexibility is the basis of constructing flexible public transport network. The method of constructing buffer flexibility of bus network is studied emphatically. Based on the analysis of the interests of passengers, public transport enterprises and society, the objective function of bus network design is put forward based on the objective function of bus network design, which is based on the three-party benefit weighting and optimization, and the changing public transport demand matrix as the basis of the design. A multi-objective optimization model for scientifically designing public transit network is established. The model takes into account the interests of all parties through such indicators as passenger waiting time, overloading operation time, bus unused capacity time, bus fleet size, time consumed by passengers and the number of passengers who do not meet the passenger demand. By calculating the value of objective function under different demand modes, the adaptability of bus network to different demand modes is considered, and the size of the adaptability is quantified in the form of currency. The optimal line network is obtained by solving the model to enhance the flexibility of bus network buffer and improve the ability of bus network to cope with the change of demand. The solution of bus network design model is a multi-objective optimization problem. The algorithm takes alternative line selection as the premise and genetic algorithm search as the skeleton. In the first step, the solution space is reduced at the line level. In the second step, genetic algorithm is used to find the optimal line combination at the online network level, and two improved measures are introduced to the genetic algorithm, such as optimal individual selection and simulated annealing stretching. Ensure that the population evolves towards the desired goal. The numerical results show that the designed bus network can adapt to the change of demand better and has the flexibility of buffering to deal with the change of demand under the condition of considering the change of public transport demand. At the same time, the search space of bus lines can be reduced by the selection of alternative lines, and the computation time can be reduced, and the convergence speed of genetic algorithm can be accelerated.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U491.17

【参考文献】