隨著國民經(jīng)濟(jì)的不斷發(fā)展,人均汽車擁有量不斷提高,與之帶來的是城市機(jī)動車保有量持續(xù)增長。然而現(xiàn)有的交通基礎(chǔ)設(shè)施的建設(shè)速度和規(guī)模不能滿足日益增長的城市交通的需要,供需矛盾突出,使得城市的交通日益擁堵。要解決城市交通問題,需要發(fā)展城市公共交通�，F(xiàn)階段,在很多中小城市,常規(guī)公共汽車是公共交通的主要組成部分。常規(guī)公共汽車是覆蓋面最廣、運(yùn)行線路最多、乘車費(fèi)用最低的一種解決城市居民出行的最好方式。然而現(xiàn)階段在很多中小城市,常規(guī)公交的出行比例不高,公交對居民出行的吸引力較低。究其原因主要是由于常規(guī)公交車到站時間不確定,準(zhǔn)時性較差,乘客需要等待未知的時間,需要時刻關(guān)注到站的車輛信息,公交信息發(fā)布較落后,出現(xiàn)“伸脖子”等公交的情況。乘客容易出現(xiàn)焦急的等待情緒,或者直接改換其他交通方式出行。因此,準(zhǔn)確實時的公交車到站時間預(yù)測可以提高中小城市居民公交出行的比例,提高乘客乘車的滿意度,提高城市公交的服務(wù)水平,對解決交通問題具有重要意義。本文首先分析公交車到站時間的運(yùn)行特性及影響因素,把城市公交車輛到站時間分為三部分,分別為路段行駛時間、站點停靠時間、交叉口延誤時間。針對這三部分的運(yùn)行特性和影響因素進(jìn)行分析,選取...

【文章頁數(shù)】：93 頁

【學(xué)位級別】：碩士

【文章目錄】：
摘要
Abstract
Chapter 1 Introduction
    1.1 Research background and significance
    1.2 The current state of forecasting on arrival time of buses
        1.2.1 Application status of forecasting bus arrival time in abroad
        1.2.2 Status of theoretical research on bus arrival time
        1.2.3 Theoretical study on the prediction bus arrival time in China
    1.3 Research content and technical route
Chapter 2 Bus arrival time analysis and data preprocessing
    2.1 Analysis of the operating characteristics of public transport vehicles
        2.1.1 Operation characteristics of bus sections
        2.1.2 Operation characteristics of bus stop stations
        2.1.3 Deceleration pit stop
        2.1.4 Stop in the station
        2.1.5 Accelerating outbound
        2.1.6 Operation characteristics of bus intersections
    2.2 Analysis of the influencing factors of bus arrival time
        2.2.1 Analysis of road travel time factors
        2.2.2 Analysis of the influencing factors of bus stop time
        2.2.3 Intersection transit time analysis
    2.3 Data acquisition and processing
        2.3.1 Collection of basic data
        2.3.2 Pre-processing of bus GPS data
        2.3.3 Data error analysis
        2.3.4 Data processing
        2.3.5 Bus line information collection and preprocessing
        2.3.6 Discretization of bus lines
        2.3.7 Bus GPS data matching with bus line information
    2.4 Summary of this chapter
Chapter 3 Related prediction methods of bus arrival time
    3.1 Prediction methods of bus arrival time
        3.1.1 Forecast model based on historical data
    3.2 Regression prediction model
        3.2.1 Basic principles of time series forecasting methods
    3.3 Support vector machine algorithm principle
    3.4 Kalman filter model
        3.4.1 Principle of artificial neural network model
        3.4.2 Combined forecasting model
    3.5 Summary of this chapter
Chapter 4 Establishing the prediction model of bus arrival time
    4.1 Initial prediction model of bus arrival time
        4.1.1 Prediction model of bus journey time
        4.1.2 The model for predicting the stopping time of bus stops
        4.1.3 Prediction model of transit time at bus intersections
    4.2 Kalman filter-based bus arrival time prediction model
    4.3 Summary of this chapter
Chapter 5 Research on verification of predictive model examples
    5.1 Example verification
        5.1.1 Source of experimental data
        5.1.2 Example line and survey data description
        5.1.3 Forecast results and error analysis of bus arrival time
    5.2 Summary of this chapter
Conclus?on
References
Acknowledgements



本文編號：3876283