NGSIM车辆轨迹重构
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摘要
下一代交通仿真(next generation simulation,NGSIM)车辆轨迹数据存在异常值和测量误差,为了使其准确可用,在建模之前需要对NGSIM车辆轨迹进行重构.建立了两步车辆轨迹数据重构算法:1)通过小波分析和物理约束界限值识别两类异常值,并分别采用拉格朗日5次和3次多项式插值对异常值进行重新估计; 2)在保证信号能量比的前提下,根据卡尔曼滤波算法对车辆轨迹进行滤波去噪.通过对NGSIM车辆轨迹数据库I-80中的样本轨迹进行重构,速度曲线和加速度曲线以及Jerk分析表明该轨迹重构算法使模型建立更加精确.之后,将该算法应用于整个数据库中,加速度分布图表明轨迹重构效果良好.
Many outliers and measurement errors exist in the next generation simulation( NGSIM) data.To make the vehicle trajectories more precise and usable for researching,they should be reconstructed before establishing certain models. In this paper,a two-step model was developed: 1) The two patterns of outliers were identified by wavelet analysis and physical restricts and modified by 5~(th)-degree and 3~(th)-degree Lagrange polynomial interpolation,respectively; 2) The Kalman filter,taking signal energy into account,was conducted to filter the noises in NGSIM data. The performance of the two-step model was supported by the speed curve,acceleration curve,and jerk analysis from the NGSIM database I-80.Finally,this method was implemented to reconstruct all the vehicle trajectories in NGSIM data,and the acceleration distribution indicated that the performance was very good.
Many outliers and measurement errors exist in the next generation simulation( NGSIM) data.To make the vehicle trajectories more precise and usable for researching,they should be reconstructed before establishing certain models. In this paper,a two-step model was developed: 1) The two patterns of outliers were identified by wavelet analysis and physical restricts and modified by 5~(th)-degree and 3~(th)-degree Lagrange polynomial interpolation,respectively; 2) The Kalman filter,taking signal energy into account,was conducted to filter the noises in NGSIM data. The performance of the two-step model was supported by the speed curve,acceleration curve,and jerk analysis from the NGSIM database I-80.Finally,this method was implemented to reconstruct all the vehicle trajectories in NGSIM data,and the acceleration distribution indicated that the performance was very good.
引文
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[21]MONTAINO M,PUNZO V.Making NGSIM data usable for studies on traffic flow theory[J].Transportation Research Record:Journal of the Transportation Research Board,2013,2390:99-111.
[22]WANG J,CHAI R,XUE X.The effects of stop-and-go wave on the immediate follower and change in driver characteristics[J].Procedia Engineering,2016,137:289-298.
[23]FARD M R,MOHAYMANY A S,SHAHRI M.A new methodology for vehicle trajectory reconstruction based on wavelet analysis[J].Transportation Research Part C:Emerging Technologies,2017,74:150-167.
[24]POLIKAR R.Multiresolution analysis:the continuous wavelet transform[Z/OL].[2017-08-11].http:∥users.rowan.edu/~polikar/WAVELETS/WTpart3.html.
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[26]杜延松,覃太贵.数值分析及实验[M].2版.北京:科学出版社,2012:125-134.
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[28]WELCH G,BISHOP G.An introduction to the Kalman filter[Z/OL].[2017-8-11].http:∥www.cs.unc.edu/~welch/media/pdf/Kalman_intro.pdf.
[2]MA X,ANDREASSON I.Statistical analysis of driver behavior data in different regimes of the car-following stage[J].Transportation Research Record:Journal of the Transportation Research Board,2007,2018:87-96.
[3]张智勇,黄轶,任福田.城市快速路跟车行为的状态划分[J].北京工业大学学报,2009,35(11):1512-1515ZHANG Z Y,HUANG Y,REN F T.Compartmentalizing car-following regime in expressway[J].Journal of Beijing University of Technology,2009,35(11):1512-1515.(in Chinese)
[4]WEI H,FENG C,MEYER E,et al.Closure to“videocapture-based approach to extract multiple vehicular trajectory data for traffic modeling”[J].Journal of Transportation Engineering,2009,135(3):150-152.
[5]曹雨,孙小端,贺玉龙.基于可接受间隙理论的交通冲突判别方法研究[J].道路交通与安全,2014,14(3):34-40.CAO Y,SUN X D,HE Y L.Research on methods of traffic conflict discrimination based on gap acceptance theory[J].Road Traffic and Safety,2014,14(3):34-40.(in Chinese)
[6]CHU T D,MIWA T,MORIKAWA T.Modeling speed adjustment behavior of merging vehicles at urban expressway merging sections[J].Procedia-Social and Behavioral Sciences,2014(138):116-126.
[7]CHU T D,MIWA T,MORIKAWA T.An analysis of merging maneuvers at urban expressway merging sections[J].Procedia-Social and Behavioral Sciences,2014(138):105-115.
[8]LU X Y,SKABARDONIS A.Freeway traffic shockwave analysis:exploring the NGSIM trajectory data[J].European Journal of Public Health,2007,24(5):26-32.
[9]DURET A,BUISSON C,CHIABAUT N.Estimating individual speed-spacing relationship and assessing the newell's car-following model ability to reproduce trajectories[J].Transportation Research Record:Journal of the Transportation Research Board,2008,2088:188-197.
[10]ZHENG Z,AHN S,CHEN D,et al.The effects of lanechanging on the immediate follower:anticipation,relaxation,and change in driver characteristics[J].Transportation Research Part C:Emerging Technologies,2013,26(26):367-379.
[11]HOU Y,EDARA P,SUN C.Situation assessment and decision making for lane change assistance using ensemble learning methods[J].Expert Systems with Applications,2015,42(8):3875-3882.
[12]THIEMANN C,TREIBER M,KESTING A.Estimating acceleration and lane-changing dynamics from Next Generation Simulation Trajectory Data[J].Transportation Research Record:Journal of the Transportation Research Board,2008,2088:90-101.
[13]CHEN C,LI L,HU J,et al.Calibration of MITSIM and IDM car-following model based on ngsim trajectory datasets[C]∥IEEE International Conference on Vehicular Electronics and Safety.Piscataway:IEEE,2010:48-53.
[14]YANG L X,ZHAO X M,ZHENG J F.Correlations among various parameters in car-following models with NGSIM trajectory data[J].Applied Mechanics&Materials,2011,66/67/68:179-184.
[15]张颖达,邵春福,李慧轩,等.基于NGSIM轨迹数据的换道行为微观特性分析[J].交通信息与安全,2015,33(6):19-24.ZHANG Y D,SHAO C F,LI H X,et al.Microscopic characteristics of lane-change maneuvers based on NGSIM[J].Journal of Transportation Information and Safety,2015,33(6):19-24.(in Chinese)
[16]HERRERA J C,BAYEN A M.Traffic flow reconstruction using mobile sensors and loop detector data[C/OL].[2018-07-04].https:∥cloudfront.escholarship.org/dist/prd/content/qt6v40f0bs/qt6v40f0bs.pdf?t=mc3cd7.
[17]MARCZAK F,BUISSON C.New filtering method for trajectory measurement errors and its comparison with existing methods[J].Transportation Research Record:Journal of the Transportation Research Board,2012,2315:35-46.
[18]MONTANINO M,PUNZO V.Trajectory data reconstruction and simulation-based validation against macroscopic traffic patterns[J].Transportation Research Part B:Methodology,2015,80:82-106.
[19]PUNZO V,BORZACCHIELLO M T,CIUFFO B.Estimation of vehicle trajectories from observed discrete positions and next-generation simulation program(NGSIM)data[C/OL].[2018-07-04].http:∥xueshu.baidu.com/s?wd=paperuri%3A%28c4e7cae4e07c5fb28be361cad9 66c83b%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.469.8275%26rep%3Drep1%26type%3Dpdf&ie=utf-8&sc_us=2381835565708922088.
[20]PUNZO V,BORZACCHIELLO M T,CIUFFO B.On the assessment of vehicle trajectory data accuracy and application to the next generation simulation(NGSIM)program data[J].Transportation Research Part C:Emerging Technologies,2011,19(6):1243-1262.
[21]MONTAINO M,PUNZO V.Making NGSIM data usable for studies on traffic flow theory[J].Transportation Research Record:Journal of the Transportation Research Board,2013,2390:99-111.
[22]WANG J,CHAI R,XUE X.The effects of stop-and-go wave on the immediate follower and change in driver characteristics[J].Procedia Engineering,2016,137:289-298.
[23]FARD M R,MOHAYMANY A S,SHAHRI M.A new methodology for vehicle trajectory reconstruction based on wavelet analysis[J].Transportation Research Part C:Emerging Technologies,2017,74:150-167.
[24]POLIKAR R.Multiresolution analysis:the continuous wavelet transform[Z/OL].[2017-08-11].http:∥users.rowan.edu/~polikar/WAVELETS/WTpart3.html.
[25]张德丰.MATLAB小波分析[M].2版.北京:机械工业出版社,2012:53-55.
[26]杜延松,覃太贵.数值分析及实验[M].2版.北京:科学出版社,2012:125-134.
[27]邓自立.最优估计理论及其应用[M].哈尔滨:哈尔滨工业出版社,2005:9-10.
[28]WELCH G,BISHOP G.An introduction to the Kalman filter[Z/OL].[2017-8-11].http:∥www.cs.unc.edu/~welch/media/pdf/Kalman_intro.pdf.