【摘要】：公交調(diào)度是地面公交運(yùn)營(yíng)管理的重要組成部分,也是提供便捷、舒適的公交服務(wù)的關(guān)鍵技術(shù)手段之一。針對(duì)目前國(guó)內(nèi)地面公交調(diào)度普遍采用人工調(diào)度、調(diào)度優(yōu)化技術(shù)缺乏有效數(shù)據(jù)支撐的現(xiàn)狀,論文以實(shí)際采集的昆山市公交AFC(自動(dòng)收費(fèi)采集)刷卡數(shù)據(jù)為基礎(chǔ),研究了基于公交AFC數(shù)據(jù)的公交客流需求及沿線交通狀況規(guī)律提取方法,在此基礎(chǔ)上重點(diǎn)研究了地面公交時(shí)刻表優(yōu)化技術(shù)和動(dòng)態(tài)調(diào)度技術(shù)。在公交客流需求及沿線交通狀況變化規(guī)律提取方法研究方面,論文分析了AFC刷卡數(shù)據(jù)的特點(diǎn),分析了歷史平均模型、多元線性回歸估計(jì)在客流需求及沿線交通狀況提取中的適用性,在此基礎(chǔ)上提出了從AFC刷卡數(shù)據(jù)中提取乘客到達(dá)率及路段旅行速度以表征公交客流需求及沿線道路交通運(yùn)行狀況的算法,并且利用實(shí)際數(shù)據(jù)進(jìn)行了實(shí)驗(yàn),得到了較為詳細(xì)的公交需求及交通運(yùn)行狀況數(shù)據(jù)。在公交時(shí)刻表優(yōu)化技術(shù)研究方面,論文將地面公交時(shí)刻表優(yōu)化問題抽象為一個(gè)非線性優(yōu)化問題,在此基礎(chǔ)上分析了智能算法在非線性優(yōu)化問題求解的適用性,并提出了利用遺傳算法進(jìn)行求解的基于歷史公交需求與沿線交通狀況的公交時(shí)刻表優(yōu)化算法。該算法以乘客平均等待時(shí)間為優(yōu)化目標(biāo),以發(fā)車次數(shù)為約束條件,對(duì)實(shí)際地面公交線路原有時(shí)刻表進(jìn)行了優(yōu)化。在公交動(dòng)態(tài)調(diào)度技術(shù)研究方面,論文首先分析了動(dòng)態(tài)調(diào)度的功能需求,進(jìn)而研究了高峰短掉頭以及就近場(chǎng)站空車調(diào)度兩種動(dòng)態(tài)調(diào)度技術(shù)的適用性與具體算法。論文采用仿真方法對(duì)地面公交時(shí)刻表優(yōu)化算法和動(dòng)態(tài)調(diào)度算法進(jìn)行了評(píng)估。仿真結(jié)果表明,論文所設(shè)計(jì)的時(shí)刻表優(yōu)化算法能夠在原有時(shí)刻表的基礎(chǔ)上有效降低乘客平均等待時(shí)間；高峰短掉頭技術(shù)以及就近場(chǎng)站空車調(diào)度兩種動(dòng)態(tài)調(diào)度方法對(duì)調(diào)度執(zhí)行時(shí)段的公交運(yùn)力及服務(wù)質(zhì)量有明顯提升,但對(duì)整體的線路運(yùn)行的平均等待時(shí)間影響較小。
[Abstract]:Bus scheduling is an important part of ground bus operation and management, and it is also one of the key technical means to provide convenient and comfortable bus service. In view of the current situation that manual dispatching is widely used in domestic ground bus dispatching, and the technology of dispatching optimization lacks effective data support, the paper is based on the data collected by AFC (automatic collection of bus charges) card in Kunshan City. This paper studies the extraction method of bus passenger flow demand and traffic conditions along the road based on bus AFC data. On this basis, it focuses on the optimization technology and dynamic scheduling technology of ground bus timetables. In this paper, the characteristics of AFC card payment data and the historical average model are analyzed in terms of the extraction method of bus passenger flow demand and the change rule of traffic condition along the route. The applicability of multivariate linear regression estimation in the extraction of passenger demand and traffic conditions along the route. On this basis, an algorithm is proposed to extract the arrival rate of passengers and the speed of road travel from the data of AFC card swiping to represent the demand of bus passenger flow and the running condition of the road traffic along the road, and the experiment is carried out by using the actual data. The detailed data of bus demand and traffic operation are obtained. In the research of bus schedule optimization technology, this paper abstracts the optimization problem of ground bus schedule into a nonlinear optimization problem, and then analyzes the applicability of intelligent algorithm in solving nonlinear optimization problems. The optimization algorithm of bus schedule based on historical public transportation demand and traffic condition along the route is proposed based on genetic algorithm (GA). Taking the average waiting time of passengers as the optimization objective and the number of departure times as the constraint, the original timetable of the actual ground bus line is optimized. In the research of bus dynamic scheduling technology, this paper first analyzes the functional requirements of dynamic scheduling, and then studies the applicability and specific algorithms of the two dynamic scheduling technologies, namely, peak short-turn and near-field empty vehicle scheduling. In this paper, the simulation method is used to evaluate the optimization algorithm and dynamic scheduling algorithm of ground bus timetables. The simulation results show that the proposed algorithm can effectively reduce the average waiting time of passengers on the basis of the original timetable. Two dynamic scheduling methods, peak short turn-around technology and empty vehicle scheduling in near-field stations, can improve the public transport capacity and service quality in the scheduling execution period obviously, but have little effect on the average waiting time of the whole line operation.
【學(xué)位授予單位】：東南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：U491.17

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