【摘要】：公交行車計劃的編制是將各車次分配至各公交車輛的過程。因此對其的優(yōu)化包括了決定車次的公交時刻表以及場站的公交車輛數(shù)。優(yōu)化的目標(biāo)是減少場站配車數(shù)并且解決目前存在的各公交車輛之間載客量、總運行時長不均衡等問題,為各公交車輛構(gòu)建均衡合理的車次鏈。而行車計劃的優(yōu)化過程中必不可少的一項即為乘客的出行數(shù)據(jù),目前常用的數(shù)據(jù)獲取方式為人工調(diào)查,此方式在耗費大量人力財力的同時,精確度得不到保證,因此本文采用乘客出行的公交IC卡刷卡數(shù)據(jù)作為數(shù)據(jù)來源對公交行車計劃進(jìn)行優(yōu)化。首先,基于公交IC卡數(shù)據(jù)判斷乘客的上、下車站點。通過刷卡時間差臨界值區(qū)分兩個相鄰的刷卡記錄是否位于同站,在此基礎(chǔ)上建立站點上車人數(shù)計算算法,并通過Pathon語言實現(xiàn)程序化的站點上車人數(shù)計算。此外,論文通過建立假設(shè)與集合的方式,將公交出行鏈法與站點吸引權(quán)重法相結(jié)合,通過乘客下一次上車站點推導(dǎo)乘客的下車站點,以求得各站點的下車人數(shù);然后,引入斷面客流量的計算方法,以建立期望載客量模型,該期望載客量模型考慮了公交運營成本以及乘客舒適性兩方面的因素,確定出車輛合理的載客人數(shù),即期望載客量值。為保證各發(fā)車車次均衡載客,選擇載客量較大的前幾個站點作為關(guān)鍵站點,構(gòu)建關(guān)鍵站點累計載客量曲線,確定出各關(guān)鍵站點累計客流量曲線達(dá)到期望載客量值時所需要的發(fā)車時間,并選取最小的發(fā)車時間作為優(yōu)化后的發(fā)車時間,以此類推,依次得到各時段優(yōu)化后的發(fā)車時間;之后,需要將優(yōu)化后的時刻表所對應(yīng)的各車次安排給各公交車輛,因此建立了基于發(fā)車時刻表的場站逆差函數(shù),并建立不同場站間空駛車次的插入算法,在時刻表優(yōu)化不變的條件下,減小場站逆差函數(shù)高峰值,即減少配車數(shù)。在優(yōu)化場站車輛數(shù)后,各車次按照FIFO并且車輛總運行時長均衡的規(guī)則進(jìn)行分配,構(gòu)建各車輛的車次鏈,得到均衡的行車計劃。本文選取了廣州市23路以及37路作為實例進(jìn)行分析,證明本文提出的行車計劃優(yōu)化方案,不僅在滿足客流需求的同時減少了場站所需的配車數(shù),并且解決了平峰時段部分車輛過于擁擠而部分車輛載客不足、各公交車輛車次鏈總運行時長不均衡等問題,為各車輛分配了合理的車次鏈,形成一個完整的行車計劃。
[Abstract]:The compilation of bus plan is the process of distributing each train number to each bus vehicle. Therefore, the optimization includes the bus schedule that determines the number of buses and the number of buses at the station. The aim of the optimization is to reduce the number of buses assigned to the station and to solve the existing problems such as the capacity of each bus and the imbalance of the total running time so as to build a balanced and reasonable train number chain for each bus. One of the essential items in the optimization of train planning is passenger travel data. At present, the commonly used data acquisition method is manual survey, which consumes a lot of human and financial resources, but the accuracy can not be guaranteed. Therefore, this paper uses the IC card data of passenger travel as the data source to optimize the bus plan. First of all, based on the bus IC card data to judge the passenger on, get off the station. According to the critical value of the time difference of credit card, two adjacent credit card records are located at the same station or not. On this basis, an algorithm for calculating the number of boarding passengers at the station is established, and the program calculation of the number of boarding stations is realized by Pathon language. In addition, the paper combines the bus trip chain method with the station attraction weight method by establishing the assumption and the set, and deduces the passenger's alighting station through the next boarding station, so as to find out the number of the passengers at each station. This paper introduces the calculation method of cross-section passenger flow to establish the expected passenger capacity model, which takes into account the two factors of bus operation cost and passenger comfort, and determines the reasonable number of passengers carried by the vehicle, that is, the expected passenger load value. In order to ensure the balanced passenger load of each train, select the first few stations with large passenger capacity as the key stations, and construct the cumulative load curve of the key stations. Determine the departure time required when the accumulated passenger flow curve of each key station reaches the expected capacity value, and select the minimum departure time as the optimized departure time, and so on, and then get the optimized departure time of each time period in turn; After that, it is necessary to arrange the trains corresponding to the optimized timetable to each bus, so the deficit function of the station based on the departure schedule is established, and the algorithm of inserting empty train numbers between different stations is established. Under the condition that the schedule is optimized, the peak value of the deficit function of the field station is reduced, that is to say, the number of cars allocated is reduced. After optimizing the number of vehicles in the station, each vehicle is allocated according to the rules of FIFO and the equilibrium of the total running time of the vehicle, the train number chain of each vehicle is constructed, and the balanced driving plan is obtained. In this paper, the 23 and 37 roads in Guangzhou are selected as examples. It is proved that the train planning optimization scheme proposed in this paper can not only meet the demand of passenger flow, but also reduce the number of bus distribution required by the station at the same time. It also solves the problems of overcrowded part of vehicles and insufficient carrying capacity of some vehicles in the flat peak period, and the total running time of each bus vehicle is not balanced, which allocates a reasonable train number chain for each vehicle and forms a complete train plan.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：U491.17

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本文編號：2265009