本文選題：公共交通 + 代價值　； 參考：《北京郵電大學(xué)》2014年碩士論文

【摘要】：近年來隨著科學(xué)技術(shù)的不斷進(jìn)步,人們的生活水平極大提高,各城市的城市化進(jìn)程不斷被推進(jìn),但隨之而來的問題也日益嚴(yán)重。城市規(guī)模的擴(kuò)大致使城市公交系統(tǒng)變得越來越發(fā)達(dá),錯綜復(fù)雜的公交線路,給人們的出行方便帶來極大的挑戰(zhàn)。我國的大中型城市人口密度和機(jī)動車數(shù)量迅速增長,給公交系統(tǒng)帶來巨大的壓力,交通形勢尤為嚴(yán)峻。為了提高公共交通系統(tǒng)對人們出行的吸引力,減少私家車的使用,緩解城市交通壓力,論文提出了一種有效、高效、完善的基于實(shí)時路況的公交換乘算法。 論文首先分析了國內(nèi)外的學(xué)者對于人們的出行問題的研究結(jié)果,發(fā)現(xiàn)提高公共交通系統(tǒng)的服務(wù)質(zhì)量可以使人們更多地使用公共交通工具,于是論文給出了六種不同的換乘方案；之后分析了國內(nèi)外公交換乘算法的研究現(xiàn)狀,提出了相應(yīng)的算法設(shè)計方案,具體分為靜態(tài)換乘算法與動態(tài)換乘算法兩部分；靜態(tài)換乘算法部分利用了數(shù)據(jù)建模的相關(guān)理論進(jìn)行建模、利用數(shù)據(jù)庫相關(guān)技術(shù)最大限度的提升該方案的查詢速度。在此算法的基礎(chǔ)上使用人工神經(jīng)網(wǎng)絡(luò)進(jìn)行方案路程消耗時間的預(yù)測,將預(yù)測值作為最終的換乘方案評判條件；然后使用大量的歷史公交系統(tǒng)數(shù)據(jù)對人工神經(jīng)網(wǎng)絡(luò)進(jìn)行訓(xùn)練,將實(shí)時的道路狀況和公交車的運(yùn)行狀態(tài)輸入網(wǎng)絡(luò)得到相應(yīng)時間的預(yù)測值,根據(jù)預(yù)測值對靜態(tài)方案重新排序從而得到動態(tài)換乘方案。 論文還對靜態(tài)換乘算法進(jìn)行了準(zhǔn)確率、覆蓋率和查詢效率的系統(tǒng)測試,結(jié)果表明論文所提出的靜態(tài)換乘算法不僅可以提供六種換乘模型,還具有高準(zhǔn)確率、高覆蓋率和高效的查詢效率。將動態(tài)換乘方案與靜態(tài)換乘方案進(jìn)行了對比,結(jié)果表明利用神經(jīng)網(wǎng)絡(luò)預(yù)測的動態(tài)換乘算法結(jié)果可以根據(jù)查詢的時間點(diǎn)進(jìn)行不同程度的調(diào)整,提供實(shí)時的換乘方案；與百度換乘工具結(jié)果對比,說明了動態(tài)換乘算法可以根據(jù)實(shí)時路況對路程消耗時間進(jìn)行很好預(yù)測,對人們的出行有更好的指導(dǎo)作用。最后總結(jié)了在研究生期間的工作內(nèi)容和成果。
[Abstract]:In recent years, with the development of science and technology, the living standard of people has been greatly improved, and the urbanization process of various cities has been pushed forward, but the following problems are becoming more and more serious. With the expansion of the city scale, the urban public transport system becomes more and more developed, and the complicated bus routes bring great challenges to people's travel convenience. The population density and the number of motor vehicles in large and medium-sized cities in China are increasing rapidly, which brings great pressure to the public transport system, especially the traffic situation. In order to improve the attraction of public transport system to people, reduce the use of private cars, and alleviate the pressure of urban traffic, this paper proposes an effective, efficient and perfect bus transfer algorithm based on real-time traffic conditions. Firstly, this paper analyzes the research results of domestic and foreign scholars on people's travel problem, and finds that improving the service quality of public transportation system can make people use more public transport vehicles, so the paper gives six different transfer schemes. After analyzing the research status of bus transfer algorithm at home and abroad, the corresponding algorithm design scheme is put forward, which is divided into static transfer algorithm and dynamic transfer algorithm. In the part of static transfer algorithm, the theory of data modeling is used to model, and the database correlation technology is used to improve the query speed of the scheme. On the basis of this algorithm, the artificial neural network is used to predict the travel time of the scheme, and the predicted value is taken as the final evaluation condition of the transfer scheme, and then the artificial neural network is trained with a large number of historical bus system data. The real-time road condition and the running state of the bus are input into the network to get the prediction value of the corresponding time. According to the forecast value, the static scheme is reordered and the dynamic transfer scheme is obtained. The static transfer algorithm is tested on the accuracy, coverage and query efficiency. The results show that the static transfer algorithm can not only provide six transfer models, but also have a high accuracy. High coverage and efficient query efficiency. The dynamic transfer scheme is compared with the static transfer scheme. The results show that the dynamic transfer algorithm predicted by neural network can be adjusted according to the query time points to provide real-time transfer scheme. Compared with the result of Baidu transfer tool, it is proved that the dynamic transfer algorithm can predict the travel time well according to the real time traffic conditions, and it has better guidance for people to travel. Finally, it summarizes the contents and achievements of the work during the graduate period.
【學(xué)位授予單位】：北京郵電大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：U491.17

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