[1] Ni Peizhou, Li Xu, Xia Liang, Huang Liang, et al. Modeling the special intersections for enhanced digital map [J]. Journal of Southeast University (English Edition), 2020, 36 (3): 264-272. [doi:10.3969/j.issn.1003-7985.2020.03.003]

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Modeling the special intersections for enhanced digital map()

用于增强型数字地图的特殊交叉路口道路建模

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

36

Issue:

2020 03

Page:

264-272

Research Field:

Traffic and Transportation Engineering

Publishing date:

2020-09-20

Info

Title:

Modeling the special intersections for enhanced digital map

用于增强型数字地图的特殊交叉路口道路建模

Author(s):

Ni Peizhou¹;  Li Xu¹;  Xia Liang¹;  Huang Liang²;  3

¹School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
²NavInfo Co., Ltd, Beijing 100083, China
³China Satellite Navigation Communication Co., Ltd, Beijing 100094, China

倪培洲¹;  李旭¹;  夏亮¹;  黄亮²;  3

¹东南大学仪器科学与工程学院, 南京 210096; ²北京四维图新科技股份有限公司, 北京 100083; ³中寰卫星导航通信有限公司, 北京 100094

Keywords:

enhanced digital map;  lane-level;  intersection model;  cardinal spline

增强型数字地图;  车道级;  交叉路口模型;  cardinal样条

PACS:

U495

DOI:

10.3969/j.issn.1003-7985.2020.03.003

Abstract:

A new lane-level road modeling method based on cardinal spline is proposed for the special intersections which are covered by vegetation or artificial landscape in their central regions. First, cardinal spline curves are used to fit the virtual lanes inside special intersections, and an initial road model is established using a series of control points and tension parameters. Then, the progressive optimization algorithm is proposed to determine the final road model based on the initial model. The algorithm determines reasonable control points and optimal tension parameters according to the degree of road curvature changes, so as to achieve a balance between the efficiency and reliability of the road model. Finally, the proposed intersection model is verified and evaluated through experiments. The results show that this method can effectively describe the lane-level topological relationship and geometric details of this kind of special intersection where the central area is covered by vegetation or artificial landscape, and can achieve a good balance between the efficiency and reliability of the road model.

针对中心区域被植被或人工景观覆盖的特殊交叉路口场景, 提出了一种基于cardinal样条的数字地图车道级道路建模方法.首先, 采用cardinal样条曲线来拟合特殊交叉路口内部的虚拟车道, 建立一个初始的道路模型, 此模型由一系列的控制点和张力参数确定.然后, 针对该初始模型, 提出一种渐进优化算法确定最终的道路模型, 该算法根据道路曲率的变化程度确定合理的控制点和最优的张力参数, 以实现道路模型高效性与可靠性两者之间的平衡.最后, 通过实验对所提方法进行了验证和评价.结果表明, 在交叉路口中心区域被植被或人工景观覆盖的情况下, 此方法能够有效地描述这类特殊交叉路口的车道级拓扑关系和几何细节, 同时能够较好地实现道路模型高效性与可靠性之间的平衡.

References:

[1] Jo K, Sunwoo M. Generation of a precise roadway map for autonomous cars[J].IEEE Transactions on Intelligent Transportation Systems, 2014, 15(3): 925-937. DOI:10.1109/TITS.2013.2291395.
[2] Ress C, Etemad A, Kuck D, et al. Electronic horizon-providing digital map data for ADAS applications[C]//2nd International Workshop on Intelligent Vehicle Control Systems. Funchal-Madeira, Portugal, 2008: 40-49.
[3] Kim S W, Liu W, Ang M H, et al. The impact of cooperative perception on decision making and planning of autonomous vehicles[J].IEEE Intelligent Transportation Systems Magazine, 2015, 7(3): 39-50. DOI:10.1109/MITS.2015.2409883.
[4] Gwon G P, Hur W S, Kim S W, et al. Generation of a precise and efficient lane-level road map for intelligent vehicle systems[J].IEEE Transactions on Vehicular Technology, 2017, 66(6): 4517-4533. DOI:10.1109/tvt.2016.2535210.
[5] Durekovic S, Smith N. Architectures of map-supported ADAS[C]//2011 IEEE Intelligent Vehicles Symposium. Baden-Baden, Germany, 2011: 207-211. DOI:10.1109/IVS.2011.5940402.
[6] Du J, Barth M J. Next-generation automated vehicle location systems: Positioning at the lane level[J].IEEE Transactions on Intelligent Transportation Systems, 2008, 9(1): 48-57. DOI:10.1109/TITS.2007.908141.
[7] Ziegler J, Bender P, Schreiber M, et al. Making bertha drive: An autonomous journey on a historic route[J].IEEE Intelligent Transportation Systems Magazine, 2014, 6(2): 8-20. DOI:10.1109/MITS.2014.2306552.
[8] Betaille D, Toledo-Moreo R. Creating enhanced maps for lane-level vehicle navigation[J].IEEE Transactions on Intelligent Transportation Systems, 2010, 11(4): 786-798. DOI:10.1109/tits.2010.2050689.
[9] Naumann M, Hellmund A M. Multi-drive road map generation on standardized high-velocity roads using low-cost sensor data[C]//19th International IEEE Conference on Intelligent Transportation Systems(ITSC 2016). Rio de Janeiro, Brazil, 2016: 113-120. DOI:10.1109/ITSC.2016.7795540.
[10] Zhang T, Yang D G, Li T, et al. An improved virtual intersection model for vehicle navigation at intersections[J].Transportation Research Part C: Emerging Technologies, 2011, 19(3): 413-423. DOI:10.1016/j.trc.2010.06.001.
[11] Zhang T, Arrigoni S, Garozzo M, et al. A lane-level road network model with global continuity[J].Transportation Research Part C: Emerging Technologies, 2016, 71(10): 32-50. DOI:10.1016/j.trc.2016.07.003.
[12] Chen A N, Ramanandan A, Farrell J A. High-precision lane-level road map building for vehicle navigation[C]//IEEE/ION Position, Location and Navigation Symposium. Indian Wells, CA, USA, 2010: 1035-1042. DOI:10.1109/PLANS.2010.5507331.
[13] Gikas V, Stratakos J. A novel geodetic engineering method for accurate and automated road/railway centerline geometry extraction based on the bearing diagram and fractal behavior[J].IEEE Transactions on Intelligent Transportation Systems, 2012, 13(1): 115-126. DOI:10.1109/TITS.2011.2163186.
[14] Brummer S, Janda F, Maier G, et al. Evaluation of a mapping strategy based on smooth arc splines for different road types[C]//16th International IEEE Conference on Intelligent Transportation Systems(ITSC 2013). Hague, The Netherlands, 2013: 160-165. DOI:10.1109/ITSC.2013.6728227.
[15] Schindler A, Maier G, Janda F. Generation of high precision digital maps using circular arc splines[C]// 2012 IEEE Intelligent Vehicles Symposium. Madrid, Spain, 2012: 246-251. DOI:10.1109/IVS.2012.6232124.
[16] Ben-Arieh D, Chang S, Rys M, et al. Geometric modeling of highways using global positioning system data and B-spline approximation[J].Journal of Transportation Engineering, 2004, 130(5): 632-636. DOI:10.1061/(asce)0733-947x(2004)130:5(632).
[17] Schindler A, Maier G, Pangerl S. Exploiting arc splines for digital maps[C]// 14th International IEEE Conference on Intelligent Transportation Systems(ITSC 2011). Washington, DC, USA, 2011: 1-6. DOI:10.1109/ITSC.2011.6082800.
[18] Wedel A, Badino H, Rabe C, et al. B-spline modeling of road surfaces with an application to free-space estimation[J].IEEE Transactions on Intelligent Transportation Systems, 2009, 10(4): 572-583. DOI:10.1109/TITS.2009.2027223.
[19] Loose H, Franke U. B-spline-based road model for 3d lane recognition[C]//13th International IEEE Conference on Intelligent Transportation Systems(ITSC 2010). Funchal, Madeira, Portugal, 2010: 91-98. DOI:10.1109/ITSC.2010.5624968.
[20] Zhao K, Meuter M, Nunn C, et al. A novel multi-lane detection and tracking system[C]// 2012 IEEE Intelligent Vehicles Symposium. Madrid, Spain, 2012: 1084-1089.
[21] Bodduna K, Siddavatam R. A novel algorithm for detection and removal of random valued impulse noise using cardinal splines[C]//2012 Annual IEEE India Conference(INDICON). Kochi, India, 2012: 1003-1008. DOI:10.1109/INDCON.2012.6420763.

Memo

Memo:

Biographies: Ni Peizhou(1994—), male, graduate; Li Xu(corresponding author), male, doctor, professor, lixu.mail@163.com.
Foundation items: The National Natural Science Foundation of China(No. 61973079, 61273236), the Program for Special Talents in Six Major Fields of Jiangsu Province(No.2017JXQC-003).
Citation: Ni Peizhou, Li Xu, Xia Liang, et al. Modeling the special intersections for enhanced digital map[J].Journal of Southeast University(English Edition), 2020, 36(3):264-272.DOI:10.3969/j.issn.1003-7985.2020.03.003.

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