基于公交動態(tài)客流OD的車輛調(diào)度優(yōu)化模型研究
本文選題:公交客流 + 公交OD矩陣; 參考:《重慶交通大學(xué)》2014年碩士論文
【摘要】:城市化進程的不斷推進,,使得城市居民面臨日漸嚴重的城市交通擁堵,加大公交發(fā)展力度能夠使其有效地緩解。但是,現(xiàn)狀公交一般實行首末站調(diào)度或者根據(jù)經(jīng)驗制定車輛發(fā)車時刻表等調(diào)度方法,不能實現(xiàn)實時、動態(tài)的調(diào)度而面臨較為嚴峻的挑戰(zhàn)。因此,對于公交調(diào)度優(yōu)化進行研究具有重要的意義。 本文通過對車輛運營調(diào)度相關(guān)內(nèi)容的分析,提出基于公交客流動態(tài)OD預(yù)測構(gòu)建車輛調(diào)度優(yōu)化模型的研究思路,并對構(gòu)建的公交線路區(qū)間車與全程車混合調(diào)度模型應(yīng)用遺傳算法進行求解。具體研究方法為: 首先,基于目前發(fā)展迅速的IC卡技術(shù),通過與公交GPS基礎(chǔ)信息、GIS相關(guān)信息以及可實現(xiàn)的數(shù)據(jù)實時傳輸技術(shù),應(yīng)用數(shù)據(jù)的處理融合理論,實現(xiàn)了對線路公交客流OD的較為合理的推算,并提出了對區(qū)域內(nèi)公交客流OD的研究方法。 再者,通過研究公交站點輻射范圍內(nèi)公交出行能力,預(yù)測公交站點發(fā)生量和吸引量,并提出“一小時公交圈”的思路,在此基礎(chǔ)上實現(xiàn)對公交線路兩站點間任一時刻OD的動態(tài)預(yù)測,為在此基礎(chǔ)上構(gòu)建車輛優(yōu)化調(diào)度模型提供數(shù)據(jù)支持。 最后,基于公交客流動態(tài)OD的預(yù)測,建立了以公交乘客費用與公交運營企業(yè)總的費用最小為目標的公交線路區(qū)間車與全程車混合調(diào)度優(yōu)化模型,通過遺傳算法對該優(yōu)化模型進行求解,從而獲得了較為合理的公交線路車輛調(diào)度優(yōu)化方案,并選取重慶市內(nèi)公交線路實例對模型的可行性和實用性進行了驗證。 通過對公交線路調(diào)度優(yōu)化方案的可行性和實用性驗證,能夠分析出基于公交客流OD動態(tài)預(yù)測的車輛調(diào)度優(yōu)化模型在實踐操作中具有一定的應(yīng)用價值。
[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.
【學(xué)位授予單位】:重慶交通大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2014
【分類號】:U491.17;U492.22
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