基于收費數(shù)據(jù)的高速公路旅行時間自適應(yīng)插值卡爾曼濾波預(yù)測研究
發(fā)布時間：2018-12-18 17:37
【摘要】：摘要：高速公路站間旅行時間可衡量所經(jīng)路段通行效率和交通狀態(tài),是交管部門交通控制和誘導(dǎo)的重要依據(jù),也是出行者高度關(guān)注的首要信息,已成為先進出行者信息系統(tǒng)ATIS (advanced traveler information systems)和路徑導(dǎo)航系統(tǒng)RGS (route guidance systems)的關(guān)鍵因素。本文依托高速公路收費數(shù)據(jù)開展站間旅行時間預(yù)測研究,具體研究內(nèi)容如下： (1)針對MTC(manual toll collection)數(shù)據(jù)相比ETC (electronic toll collection)數(shù)據(jù)包含車輛排隊等待繳費時間的問題,提出一套MTC和ETC數(shù)據(jù)實時融合處理準(zhǔn)則,包含極端異常數(shù)據(jù)處理和數(shù)據(jù)融合,提高了周期內(nèi)車輛數(shù)據(jù)數(shù)量。 (2)針對收費數(shù)據(jù)中異常數(shù)據(jù)難以剔除的問題,提出一種改進后平均旅行時間計算模型,模型融入四分法數(shù)據(jù)剔除思想,提高了收費數(shù)據(jù)質(zhì)量和平均旅行時間計算精度。 (3)針對卡爾曼濾波算法非線性性能弱及自適應(yīng)性能差的問題,提出了高速公路旅行時間自適應(yīng)插值卡爾曼濾波算法。算法利用等間距插值方法重構(gòu)實時及歷史旅行時間之間的時間序列,基于最小二乘法實時搭建卡爾曼濾波模型,并詳細(xì)闡述了Sage-Husa自適應(yīng)卡爾曼濾波旅行時間預(yù)測原理。 (4)為驗證算法有效性,實際路段算法驗證結(jié)果可知,自適應(yīng)插值預(yù)測算法在正常、事故、小長假三種交通流狀態(tài)下所有周期平均相對誤差控制在7.5%內(nèi),事故周期平均相對誤差控制在10%內(nèi)。 (5)搭建了旅行時間預(yù)測系統(tǒng)架構(gòu)和預(yù)測系統(tǒng)業(yè)務(wù)邏輯,詳細(xì)闡述了預(yù)測系統(tǒng)收費數(shù)據(jù)存儲數(shù)據(jù)庫設(shè)計、旅行時間算法設(shè)計、發(fā)布界面設(shè)計,并基于C#. SQL Server2008開發(fā)了高速公路站間旅行時間預(yù)測系統(tǒng)。 (6)搭建了離線旅行時間系統(tǒng)穩(wěn)定性測試環(huán)境,系統(tǒng)運行穩(wěn)定后,將其布設(shè)到高速公路信息中心,實時預(yù)測高速公路旅行時間。京港澳高速公路旅行時間預(yù)測示范系統(tǒng)應(yīng)用良好,可為公眾出行提供時間參考。
[Abstract]:Absrtact: Expressway interstation travel time can measure the traffic efficiency and traffic state, which is the important basis for traffic control and guidance of traffic management department, and is also the most important information that travelers pay close attention to. It has become the key factor of the advanced traveler information system (ATIS (advanced traveler information systems) and the path navigation system (RGS (route guidance systems). Based on highway toll data, this paper carries out the research of interstation travel time prediction. The specific research contents are as follows: (1) compared with ETC (electronic toll collection) data, MTC (manual toll collection) data contains the problem of vehicle queuing waiting for payment time. A set of real-time fusion criteria for MTC and ETC data is proposed, which includes extreme anomaly data processing and data fusion, which improves the number of vehicle data in the cycle. (2) aiming at the difficulty of eliminating abnormal data in toll data, an improved average travel time calculation model is put forward. The model integrates the idea of quaternion data elimination, and improves the quality of toll data and the accuracy of average travel time calculation. (3) aiming at the problem of weak nonlinear performance and poor adaptive performance of Kalman filtering algorithm, an adaptive interpolation Kalman filter algorithm for expressway travel time is proposed. The algorithm uses equal-space interpolation method to reconstruct the time series between real time and historical travel time. Based on the least square method, the Kalman filter model is built in real time, and the principle of Sage-Husa adaptive Kalman filter travel time prediction is described in detail. (4) in order to verify the validity of the algorithm, the experimental results show that the average relative error of all periods is controlled within 7.5% under normal traffic flow, accident and small length false traffic flow. The average relative error of accident period is controlled within 10%. (5) the structure of the travel time prediction system and the business logic of the prediction system are built. The design of the database of charge data storage, the design of travel time algorithm, the design of the publishing interface, and the design based on C#are described in detail. SQL Server2008 has developed a travel time prediction system between freeway stations. (6) an off-line travel time system stability test environment is built. After the system runs stably, it is arranged in the expressway information center to predict the expressway travel time in real time. The Beijing, Hong Kong and Macao Expressway Travel time Prediction demonstration system is applied well and can provide time reference for public travel.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：U495
本文編號：2386234
[Abstract]:Absrtact: Expressway interstation travel time can measure the traffic efficiency and traffic state, which is the important basis for traffic control and guidance of traffic management department, and is also the most important information that travelers pay close attention to. It has become the key factor of the advanced traveler information system (ATIS (advanced traveler information systems) and the path navigation system (RGS (route guidance systems). Based on highway toll data, this paper carries out the research of interstation travel time prediction. The specific research contents are as follows: (1) compared with ETC (electronic toll collection) data, MTC (manual toll collection) data contains the problem of vehicle queuing waiting for payment time. A set of real-time fusion criteria for MTC and ETC data is proposed, which includes extreme anomaly data processing and data fusion, which improves the number of vehicle data in the cycle. (2) aiming at the difficulty of eliminating abnormal data in toll data, an improved average travel time calculation model is put forward. The model integrates the idea of quaternion data elimination, and improves the quality of toll data and the accuracy of average travel time calculation. (3) aiming at the problem of weak nonlinear performance and poor adaptive performance of Kalman filtering algorithm, an adaptive interpolation Kalman filter algorithm for expressway travel time is proposed. The algorithm uses equal-space interpolation method to reconstruct the time series between real time and historical travel time. Based on the least square method, the Kalman filter model is built in real time, and the principle of Sage-Husa adaptive Kalman filter travel time prediction is described in detail. (4) in order to verify the validity of the algorithm, the experimental results show that the average relative error of all periods is controlled within 7.5% under normal traffic flow, accident and small length false traffic flow. The average relative error of accident period is controlled within 10%. (5) the structure of the travel time prediction system and the business logic of the prediction system are built. The design of the database of charge data storage, the design of travel time algorithm, the design of the publishing interface, and the design based on C#are described in detail. SQL Server2008 has developed a travel time prediction system between freeway stations. (6) an off-line travel time system stability test environment is built. After the system runs stably, it is arranged in the expressway information center to predict the expressway travel time in real time. The Beijing, Hong Kong and Macao Expressway Travel time Prediction demonstration system is applied well and can provide time reference for public travel.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：U495
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