基于公交动态客流OD的车辆调度优化模型研究

发布时间：2018-05-19 01:27

本文选题：公交客流 + 公交OD矩阵　；参考：《重庆交通大学》2014年硕士论文

【摘要】：城市化进程的不断推进，，使得城市居民面临日渐严重的城市交通拥堵，加大公交发展力度能够使其有效地缓解。但是，现状公交一般实行首末站调度或者根据经验制定车辆发车时刻表等调度方法，不能实现实时、动态的调度而面临较为严峻的挑战。因此，对于公交调度优化进行研究具有重要的意义。本文通过对车辆运营调度相关内容的分析，提出基于公交客流动态OD预测构建车辆调度优化模型的研究思路，并对构建的公交线路区间车与全程车混合调度模型应用遗传算法进行求解。具体研究方法为：首先，基于目前发展迅速的IC卡技术，通过与公交GPS基础信息、GIS相关信息以及可实现的数据实时传输技术，应用数据的处理融合理论，实现了对线路公交客流OD的较为合理的推算，并提出了对区域内公交客流OD的研究方法。再者，通过研究公交站点辐射范围内公交出行能力，预测公交站点发生量和吸引量，并提出“一小时公交圈”的思路，在此基础上实现对公交线路两站点间任一时刻OD的动态预测，为在此基础上构建车辆优化调度模型提供数据支持。最后，基于公交客流动态OD的预测，建立了以公交乘客费用与公交运营企业总的费用最小为目标的公交线路区间车与全程车混合调度优化模型，通过遗传算法对该优化模型进行求解，从而获得了较为合理的公交线路车辆调度优化方案，并选取重庆市内公交线路实例对模型的可行性和实用性进行了验证。通过对公交线路调度优化方案的可行性和实用性验证，能够分析出基于公交客流OD动态预测的车辆调度优化模型在实践操作中具有一定的应用价值。
[Abstract]:With the development of urbanization, urban residents are facing more and more serious traffic jams, which can be effectively alleviated by increasing the development of public transport. However, the current bus scheduling methods, such as first and last station scheduling or vehicle departure schedule based on experience, can not achieve real-time, dynamic scheduling and face more severe challenges. Therefore, it is of great significance to study the optimization of bus dispatch. Based on the analysis of the related contents of vehicle operation and scheduling, this paper puts forward the research idea of constructing vehicle scheduling optimization model based on dynamic OD prediction of bus passenger flow. Genetic algorithm is used to solve the hybrid scheduling model of bus and whole vehicle. The specific research methods are as follows: First of all, based on the rapidly developing IC card technology, the data processing fusion theory is applied through the GIS-related information related to the basic information of bus GPS and the data real-time transmission technology that can be realized. The OD calculation of route bus passenger flow is realized, and the research method of bus passenger flow OD in the area is put forward. Furthermore, by studying the capacity of public transportation within the radiation range of public transport stations, we can predict the amount of public transport stations and the amount of attraction, and put forward the idea of "one hour bus circle". On this basis, the dynamic prediction of OD at any time between two bus stations is realized, which provides data support for the construction of vehicle optimal scheduling model on this basis. Finally, based on the dynamic OD prediction of bus passenger flow, a hybrid scheduling optimization model for bus line interval and whole vehicle is established, which aims at the minimum bus passenger cost and the total cost of public transport operation enterprises. The optimization model is solved by genetic algorithm, and a more reasonable vehicle scheduling scheme is obtained, and the feasibility and practicability of the model are verified by an example of bus routes in Chongqing. By verifying the feasibility and practicability of bus route scheduling optimization scheme, the vehicle scheduling optimization model based on OD dynamic prediction of bus passenger flow can be analyzed and has certain application value in practical operation.
【学位授予单位】：重庆交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U491.17;U492.22

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