{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T09:20:45Z","timestamp":1780392045377,"version":"3.54.1"},"reference-count":51,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2015,12,3]],"date-time":"2015-12-03T00:00:00Z","timestamp":1449100800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This research proposes an accurate vehicular positioning system which can achieve lane-level performance in urban canyons. Multiple passive sensors, which include Global Navigation Satellite System (GNSS) receivers, onboard cameras and inertial sensors, are integrated in the proposed system. As the main source for the localization, the GNSS technique suffers from Non-Line-Of-Sight (NLOS) propagation and multipath effects in urban canyons. This paper proposes to employ a novel GNSS positioning technique in the integration. The employed GNSS technique reduces the multipath and NLOS effects by using the 3D building map. In addition, the inertial sensor can describe the vehicle motion, but has a drift problem as time increases. This paper develops vision-based lane detection, which is firstly used for controlling the drift of the inertial sensor. Moreover, the lane keeping and changing behaviors are extracted from the lane detection function, and further reduce the lateral positioning error in the proposed localization system. We evaluate the integrated localization system in the challenging city urban scenario. The experiments demonstrate the proposed method has sub-meter accuracy with respect to mean positioning error.<\/jats:p>","DOI":"10.3390\/s151229795","type":"journal-article","created":{"date-parts":[[2015,12,3]],"date-time":"2015-12-03T11:12:09Z","timestamp":1449141129000},"page":"30199-30220","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":43,"title":["Passive Sensor Integration for Vehicle Self-Localization in Urban Traffic Environment"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9708-7429","authenticated-orcid":false,"given":"Yanlei","family":"Gu","sequence":"first","affiliation":[{"name":"Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li-Ta","family":"Hsu","sequence":"additional","affiliation":[{"name":"Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shunsuke","family":"Kamijo","sequence":"additional","affiliation":[{"name":"Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2015,12,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Levinson, J., Askeland, J., Becker, J., Dolson, J., Held, D., Kammel, S., Kolter, J.Z., Langer, D., Pink, O., and Pratt, V. (2011, January 5\u20139). Towards fully autonomous driving: Systems and algorithms. Proceedings of the IEEE Intelligent Vehicles Symposium 2011, Baden-Baden, Germany.","DOI":"10.1109\/IVS.2011.5940562"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Moosmann, F., and Stiller, C. (2011, January 5\u20139). Velodyne SLAM. Proceedings of the IEEE Intelligent Vehicles Symposium 2011, Baden-Baden, Germany.","DOI":"10.1109\/IVS.2011.5940396"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Glaser, C., Michalke, T.P., Burkle, L., and Niewels, F. (2014, January 8\u201311). Environment perception for inner-city driver assistance and highly-automated driving. Proceedings of the IEEE Intelligent Vehicles Symposium 2014, Dearborn, MI, USA.","DOI":"10.1109\/IVS.2014.6856388"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Choi, J. (2014, January 8\u201311). Hybrid map-based SLAM using a Velodyne laser scanner. Proceedings of the 17th International Conference on Intelligent Transportation Systems, Qingdao, China.","DOI":"10.1109\/ITSC.2014.6958185"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"16710","DOI":"10.3390\/s150716710","article-title":"LiDAR scan matching aided inertial navigation system in GNSS-denied environments","volume":"7","author":"Tang","year":"2015","journal-title":"Sensors"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Hata, A.Y., Osorio, F.S., and Wolf, D.F. (2014, January 8\u201311). Robust curb detection and vehicle localization in urban environments. Proceedings of the IEEE Intelligent Vehicles Symposium 2014, Dearborn, Michigan, USA.","DOI":"10.1109\/IVS.2014.6856405"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Hata, A., and Wolf, D. (2014, January 8\u201311). Road marking detection using LIDAR reflective intensity data and its application to vehicle localization. Proceedings of the 17th International Conference on Intelligent Transportation Systems, Qingdao, China.","DOI":"10.1109\/ITSC.2014.6957753"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1007\/978-3-540-73429-1_2","article-title":"A robust approach to high-speed navigation for unrehearsed desert terrain","volume":"36","author":"Urmson","year":"2007","journal-title":"Springer Tracts Adv. Robot."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1080","DOI":"10.1109\/TCST.2006.886439","article-title":"Kalman filter-based integration of DGPS and vehicle sensors for localization","volume":"15","author":"Rezaei","year":"2007","journal-title":"IEEE Trans. Control Syst. Technol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1007\/s10291-002-0029-z","article-title":"Performance analysis of a stand-alone high-sensitivity receiver","volume":"6","author":"MacGougan","year":"2002","journal-title":"GPS Solut."},{"key":"ref_11","first-page":"40","article-title":"GNSS solutions: Multipath vs. NLOS signals. How does non-line-of-sight reception differ from multipath interference?","volume":"8","author":"Groves","year":"2013","journal-title":"Inside GNSS Mag."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1016\/j.trc.2013.11.008","article-title":"Toward accurate localization in guided transport: Combining GNSS data and imaging information","volume":"43","author":"Marais","year":"2014","journal-title":"Transp. Res. Part C: Emerg. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1109\/TITS.2008.2011688","article-title":"GPS multipath mitigation for urban area using omnidirectional infrared camera","volume":"10","author":"Meguro","year":"2009","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Bauer, S., Obst, M., Streiter, R., and Wanielik, G. (2013, January 2\u20135). Evaluation of shadow maps for non-line-of-sight detection in urban GNSS vehicle localization with vanets\u2014The GAIN approach. Proceedings of the IEEE 77th Vehicular Technology Conference 2013: VTC2013-Spring, Dresden, Germany.","DOI":"10.1109\/VTCSpring.2013.6692555"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Obst, M., Bauer, S., Reisdorf, P., and Wanielik, G. (2012, January 3\u20137). Multipath detection with 3D digital maps for robust multi-constellation GNSS\/INS vehicle localization in urban areas. Proceedings of the IEEE Intelligent Vehicles Symposium 2012, Alcala de Henares, Spain.","DOI":"10.1109\/IVS.2012.6232285"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1017\/S0373463311000087","article-title":"Shadow Matching: A new GNSS positioning technique for urban canyons","volume":"64","author":"Groves","year":"2011","journal-title":"J. Navig."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1002\/navi.38","article-title":"GNSS shadow matching: Improving urban positioning accuracy using a 3D city model with optimized visibility scoring scheme","volume":"60","author":"Wang","year":"2013","journal-title":"Navig. J. Inst. Navig."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1017\/S0373463314000836","article-title":"Smartphone shadow matching for better cross-street gnss positioning in urban environments","volume":"68","author":"Wang","year":"2014","journal-title":"J. Navig."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"3104","DOI":"10.1109\/TITS.2015.2432122","article-title":"GPS error correction with pseudorange evaluation using three-dimensional maps","volume":"16","author":"Miura","year":"2015","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Hsu, L.T., Gu, Y., and Kamijo, S. (2015). 3D building model-based pedestrian positioning method using GPS\/GLONASS\/QZSS and its reliability calculation. GPS Solut., 1\u201316.","DOI":"10.1007\/s10291-015-0451-7"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"17329","DOI":"10.3390\/s150717329","article-title":"NLOS correction\/exclusion for GNSS measurement using RAIM and city building models","volume":"7","author":"Hsu","year":"2015","journal-title":"Sensors"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1017\/S0263574708004232","article-title":"Autonomous vehicle based in cooperative GPS and inertial systems","volume":"26","author":"Milanes","year":"2008","journal-title":"Robotica"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1077","DOI":"10.1109\/TVT.2008.926076","article-title":"Performance enhancement of MEMS-based INS\/GPS integration for low-cost navigation applications","volume":"58","author":"Noureldin","year":"2009","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_24","unstructured":"Kubo, N., and Dihan, C. (2012, January 17\u201321). Availability improvement of RTK-GPS with IMU and vehicle sensors in urban environment. Proceedings of the 25th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS 2012), Nashville, TN, USA."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"5134","DOI":"10.3390\/s120405134","article-title":"Benefits of combined GPS\/GLONASS with low-cost MEMS IMUs for vehicular urban navigation","volume":"12","author":"Angrisano","year":"2012","journal-title":"Sensors"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1781","DOI":"10.1109\/TAES.2013.6558019","article-title":"Ultratight GPS\/reduced-IMU integration for land vehicle navigation","volume":"49","author":"Sun","year":"2013","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_27","unstructured":"Gu, Y., Hsu, L.-T., Wada, Y., and Kamijo, S. (2015, January 20\u201323). Integration of 3D map based GPS positioning and on-board sensors for vehicle self-localization in urban canyon. Proceedings of the ION 2015 Pacific PNT Meeting, Honolulu, HI, USA."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Gu, Y., Wada, Y., Hsu, L.-T., and Kamijo, S. (2014, January 3\u20137). vehicle self-localization in urban canyon using 3D map based GPS positioning and vehicle sensors. Proceedings of the 3rd International Conference on Connected Vehicles & Expo (ICCVE 2014), Vienna, Austria.","DOI":"10.1109\/ICCVE.2014.7297660"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1109\/TITS.2012.2228191","article-title":"Accurate ego-vehicle global localization at intersections through alignment of visual data with digital map","volume":"14","author":"Nedevschi","year":"2013","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Gruyer, D., Belaroussi, R., and Revilloud, M. (2014, January 8\u201311). Map-aided localization with lateral perception. Proceedings of the IEEE Intelligent Vehicles Symposium 2014, Dearborn, MI, USA.","DOI":"10.1109\/IVS.2014.6856528"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Zhang, J., and Singh, S. (2014, January 14\u201316). LOAM: Lidar odometry and mapping in real-time. Proceedings of the Robotics: Science and Systems Conference (RSS), Berkeley, CA, USA.","DOI":"10.15607\/RSS.2014.X.007"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Engel, J., St\u00fcckler, J., and Cremers, D. (October, January 28). Large-scale direct slam with stereo cameras. Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS) 2015, Hamburg, Germany.","DOI":"10.1109\/IROS.2015.7353631"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Klein, G., and Murray, D. (2007, January 13\u201316). Parallel tracking and mapping for small AR workspaces. Proceedings of the 6th IEEE and ACM International Symposium on Mixed and Augmented Reality 2007, Nara, Japan.","DOI":"10.1109\/ISMAR.2007.4538852"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"16159","DOI":"10.3390\/s140916159","article-title":"Incorporating a wheeled vehicle model in a new monocular visual odometry algorithm for dynamic outdoor environments","volume":"14","author":"Jiang","year":"2014","journal-title":"Sensors"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Zhang, J., and Singh, S. (2015, January 26\u201330). Visual-lidar odometry and mapping: Low-drift, robust, and fast. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA.","DOI":"10.1109\/ICRA.2015.7139486"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"17168","DOI":"10.3390\/s121217168","article-title":"PSO algorithm particle filters for improving the performance of lane detection and tracking systems in difficult roads","volume":"12","author":"Cheng","year":"2012","journal-title":"Sensors"},{"key":"ref_37","first-page":"3270","article-title":"Robust lane sensing and departure warning under shadows and occlusions","volume":"3","year":"2013","journal-title":"Sensors"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Aly, M. (2008, January 4\u20136). Real time detection of lane markers in urban streets. Proceedings of the IEEE Intelligent Vehicles Symposium 2008, Eindhoven, The Netherlands.","DOI":"10.1109\/IVS.2008.4621152"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/83.650851","article-title":"GOLD: A parallel real-time stereo vision system for generic obstacle and lane detection","volume":"7","author":"Bertozzi","year":"1998","journal-title":"IEEE Trans. Image Process."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2:1","DOI":"10.1145\/2522968.2522970","article-title":"Keeping the vehicle on the road: A survey on on-road lane detection systems","volume":"46","author":"Yenikaya","year":"2013","journal-title":"ACM Comput. Surv."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Tao, Z., Bonnifait, P., Fremont, V., and Ibanez-Guzman, J. (2013, January 6\u20139). Lane marking aided vehicle localization. Proceedings of the 16th IEEE International Conference on Intelligent Transportation Systems 2013, The Hague, The Netherlands.","DOI":"10.1109\/ITSC.2013.6728444"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Tao, Z., Bonnifait, P., Fremont, V., and Ibanez-Guzman, J. (2013, January 3\u20137). Mapping and localization using GPS, lane markings and proprioceptive sensors. IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS) 2013, Tokyo, Japan.","DOI":"10.1109\/IROS.2013.6696383"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Schreiber, M., Knoppel, C., and Franke, U. (2013, January 23\u201326). Laneloc: Lane marking based localization using highly accurate maps. Proceedings of the IEEE Intelligent Vehicles Symposium 2013, Gold Coast, Australia.","DOI":"10.1109\/IVS.2013.6629509"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Mattern, N., and Wanielik, G. (2010, January 4\u20136). Camera-based vehicle localization at intersections using detailed digital maps. Proceedings of the 2010 IEEE\/ION Position Location and Navigation Symposium (PLANS), Indian Wells, CA, USA.","DOI":"10.1109\/PLANS.2010.5507195"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"2615","DOI":"10.1109\/TITS.2014.2321108","article-title":"An integrated vehicle navigation system utilizing lane-detection and lateral position estimation systems in difficult environments for GPS","volume":"15","author":"Rose","year":"2014","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Seo, Y.W., and Rajkumar, R. (2014, January 8\u201311). Tracking and estimation of ego-vehicle's state for lateral localization. Proceeding of the 17th International Conference on Intelligent Transportation Systems, Qingdao, China.","DOI":"10.1109\/ITSC.2014.6957859"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Marita, T., Negru, M., Danescu, R., and Nedevschi, S. (2011, January 25\u201327). Stop-line detection and localization method for intersection scenarios. Proceedings of the IEEE 7th International Conference on Intelligent Computer Communication and Processing (ICCP 2011), Cluj-Napoca, Romania.","DOI":"10.1109\/ICCP.2011.6047883"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"20779","DOI":"10.3390\/s150820779","article-title":"GPS\/DR Error estimation for autonomous vehicle localization","volume":"8","author":"Lee","year":"2015","journal-title":"Sensors"},{"key":"ref_49","unstructured":"Kamijo, S., Gu, Y., and Hsu, L.-T. (2015, January 15\u201318). GNSS\/INS\/on-board aamera integration for vehicle self-localization in urban canyon. Proceedings of the IEEE 18th International Conference on Intelligent Transportation Systems (ITSC 2015), Gran Canaria, Spain."},{"key":"ref_50","unstructured":"Garin, L., van Diggelen, F., and Rousseau, J.M. (1996, January 17\u201320). Strobe & edge correlator multipath mitigation for code. Proceedings of the the 9th International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GPS 1996), Kansas City, MO, USA."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Qin, B., Chong, Z.J., Bandyopadhyay, T., Ang Jr, M.H., Frazzoli, E., and Rus, D. (2012, January 14\u201318). Curb-intersection feature based monte carlo localization on urban roads. Proceedings of the IEEE International Conference on Robotics and Automation 2012 (ICRA 2012), Saint Paul, MN, USA.","DOI":"10.1109\/ICRA.2012.6224913"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/15\/12\/29795\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:53:17Z","timestamp":1760215997000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/15\/12\/29795"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,12,3]]},"references-count":51,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2015,12]]}},"alternative-id":["s151229795"],"URL":"https:\/\/doi.org\/10.3390\/s151229795","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,12,3]]}}}