Passive sensor integration for vehicle self-localization in urban traffic environment

Sensors (Switzerland)

Volumn 15, Issue 12, 2015, Pages 30199-30220

  Gu, Yanlei ^a   Hsu, Li Ta ^a   Kamijo, Shunsuke ^a  

^a INSTITUTE OF INDUSTRIAL SCIENCE   (Japan)

Author keywords

3D map; GNSS; Inertial sensor; Lane detection; Particle filter; Sensor integration; Vehicle self localization; Vision

Indexed keywords

INERTIAL NAVIGATION SYSTEMS; INTEGRATION; NAVIGATION SYSTEMS; VEHICLES; VISION;

GNSS; INERTIAL SENSOR; LANE DETECTION; PARTICLE FILTER; SELF LOCALIZATION; SENSOR INTEGRATION;

GLOBAL POSITIONING SYSTEM;

EID: 84949256822     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s151229795     Document Type: Article

References (51)

1. Levinson, J.; Askeland, J.; Becker, J.; Dolson, J.; Held, D.; Kammel, S.; Kolter, J.Z.; Langer, D.; Pink, O.; Pratt, V.; et al. Towards fully autonomous driving: Systems and algorithms. In Proceedings of the IEEE Intelligent Vehicles Symposium 2011, Baden-Baden, Germany, 5–9 June 2011; pp. 163–168.
2. Moosmann, F.; Stiller, C. Velodyne SLAM. In Proceedings of the IEEE Intelligent Vehicles Symposium 2011, Baden-Baden, Germany, 5–9 June 2011; pp. 393–398.
3. Glaser, C.; Michalke, T.P.; Burkle, L.; Niewels, F. Environment perception for inner-city driver assistance and highly-automated driving. In Proceedings of the IEEE Intelligent Vehicles Symposium 2014, Dearborn, MI, USA, 8–11 June 2014; pp. 1270–1275.
4. Choi, J. Hybrid map-based SLAM using a Velodyne laser scanner. In Proceedings of the 17th International Conference on Intelligent Transportation Systems, Qingdao, China, 8–11 October 2014; pp. 3082–3087.
5. Tang, J.; Chen, Y.; Niu, X.; Wang, L.; Chen, L.; Liu, J.; Shi, C.; Hyyppä, J. LiDAR scan matching aided inertial navigation system in GNSS-denied environments. Sensors 2015, 7, 16710–16728. [CrossRef] [PubMed]
6. Hata, A.Y.; Osorio, F.S.; Wolf, D.F. Robust curb detection and vehicle localization in urban environments. In Proceedings of the IEEE Intelligent Vehicles Symposium 2014, Dearborn, Michigan, USA, 8–11 June 2014; pp. 1257–1262.
7. Hata, A.; Wolf, D. Road marking detection using LIDAR reflective intensity data and its application to vehicle localization. In Proceedings of the 17th International Conference on Intelligent Transportation Systems, Qingdao, China, 8–11 October 2014; pp. 584–589.
8. Urmson, C.; Anhalt, J.; Bartz, D.; Clark, M.; Galatali, T.; Gutierrez, A.; Harbaugh, S.; Johnston, J.; Kato, H.; Koon, P.; et al. A robust approach to high-speed navigation for unrehearsed desert terrain. Springer Tracts Adv. Robot. 2007, 36, 45–102.
9. Rezaei, S.; Sengupta, R. Kalman filter-based integration of DGPS and vehicle sensors for localization. IEEE Trans. Control Syst. Technol. 2007, 15, 1080–1088. [CrossRef]
10. MacGougan, G.; Lachapelle, G.; Klukas, R.; Siu, K.; Garin, L.; Shewfelt, J.; Cox, G. Performance analysis of a stand-alone high-sensitivity receiver. GPS Solut. 2002, 6, 179–195.
11. Groves, P.D. GNSS solutions: Multipath vs. NLOS signals. How does non-line-of-sight reception differ from multipath interference? Inside GNSS Mag. 2013, 8, 40–42.
12. Marais, J.; Meurie, C.; Attia, D.; Ruichek, Y.; Flancquart, A. Toward accurate localization in guided transport: Combining GNSS data and imaging information. Transp. Res. Part C: Emerg. Technol. 2014, 43, 188–197. [CrossRef]
13. Meguro, J.I.; Murata, T.; Takiguchi, J.I.; Amano, Y.; Hashizume, T. GPS multipath mitigation for urban area using omnidirectional infrared camera. IEEE Trans. Intell. Transp. Syst. 2009, 10, 22–30. [CrossRef]
14. Bauer, S.; Obst, M.; Streiter, R.; Wanielik, G. Evaluation of shadow maps for non-line-of-sight detection in urban GNSS vehicle localization with vanets—The GAIN approach. In Proceedings of the IEEE 77th Vehicular Technology Conference 2013: VTC2013-Spring, Dresden, Germany, 2–5 June 2013; pp. 1–5.
15. Obst, M.; Bauer, S.; Reisdorf, P.; Wanielik, G. Multipath detection with 3D digital maps for robust multi-constellation GNSS/INS vehicle localization in urban areas. In Proceedings of the IEEE Intelligent Vehicles Symposium 2012, Alcala de Henares, Spain, 3–7 June 2012; pp. 184–190.
16. Groves, P.D. Shadow Matching: A new GNSS positioning technique for urban canyons. J. Navig. 2011, 64, 417–430. [CrossRef]
17. Wang, L.; Groves, P.D.; Ziebart, M.K. GNSS shadow matching: Improving urban positioning accuracy using a 3D city model with optimized visibility scoring scheme. Navig. J. Inst. Navig. 2013, 60, 195–207. [CrossRef]
18. Wang, L.; Groves, P.D.; Ziebart, M.K. Smartphone shadow matching for better cross-street gnss positioning in urban environments. J. Navig. 2014, 68, 411–433. [CrossRef]
19. Miura, S.; Hsu, L.T.; Chen, F.; Kamijo, S. GPS error correction with pseudorange evaluation using three-dimensional maps. IEEE Trans. Intell. Transp. Syst. 2015, 16, 3104–3115. [CrossRef]
20. Hsu, L.T.; Gu, Y.; Kamijo, S. 3D building model-based pedestrian positioning method using GPS/GLONASS/QZSS and its reliability calculation. GPS Solut. 2015, 1–16. [CrossRef]
21. Hsu, L.T.; Gu, Y.; Kamijo, S. NLOS correction/exclusion for GNSS measurement using RAIM and city building models. Sensors 2015, 7, 17329–17349. [CrossRef] [PubMed]
22. Milanes, V.; Naranjo, J.E.; Gonzalez, C.; Alonso, J.; de Pedro, T. Autonomous vehicle based in cooperative GPS and inertial systems. Robotica 2008, 26, 627–633. [CrossRef]
23. Noureldin, A.; Karamat, T.B.; Eberts, M.D.; El-Shafie, A. Performance enhancement of MEMS-based INS/GPS integration for low-cost navigation applications. IEEE Trans. Veh. Technol. 2009, 58, 1077–1096. [CrossRef]
24. Kubo, N.; Dihan, C. Availability improvement of RTK-GPS with IMU and vehicle sensors in urban environment. In Proceedings of the 25th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS 2012), Nashville, TN, USA, 17–21 September 2012; pp. 1545–1555.
25. Angrisano, A.; Petovello, M.; Pugliano, G. Benefits of combined GPS/GLONASS with low-cost MEMS IMUs for vehicular urban navigation. Sensors 2012, 12, 5134–5158.
26. Sun, D.B.; Petovello, M.G.; Cannon, M.E. Ultratight GPS/reduced-IMU integration for land vehicle navigation. IEEE Trans. Aerosp. Electron. Syst. 2013, 49, 1781–1791. [CrossRef]
27. Gu, Y.; Hsu, L.-T.; Wada, Y.; Kamijo, S. Integration of 3D map based GPS positioning and on-board sensors for vehicle self-localization in urban canyon. In Proceedings of the ION 2015 Pacific PNT Meeting, Honolulu, HI, USA, 20–23 April 2015.
28. Gu, Y.; Wada, Y.; Hsu, L.-T.; Kamijo, S. vehicle self-localization in urban canyon using 3D map based GPS positioning and vehicle sensors. In Proceedings of the 3rd International Conference on Connected Vehicles & Expo (ICCVE 2014), Vienna, Austria, 3–7 November 2014.
29. Nedevschi, S.; Popescu, V.; Danescu, R.; Marita, T.; Oniga, F. Accurate ego-vehicle global localization at intersections through alignment of visual data with digital map. IEEE Trans. Intell. Transp. Syst. 2013, 14,673–687. [CrossRef]
30. Gruyer, D.; Belaroussi, R.; Revilloud, M. Map-aided localization with lateral perception. In Proceedings of the IEEE Intelligent Vehicles Symposium 2014, Dearborn, MI, USA, 8–11 June 2014; pp. 674–680.
31. Zhang, J.; Singh, S. LOAM: Lidar odometry and mapping in real-time. In Proceedings of the Robotics: Science and Systems Conference (RSS), Berkeley, CA, USA, 14–16 July 2014.
32. Engel, J.; Stückler, J.; Cremers, D. Large-scale direct slam with stereo cameras. In Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS) 2015, Hamburg, Germany, 28 September–2 October 2015.
33. Klein, G.; Murray, D. Parallel tracking and mapping for small AR workspaces. In Proceedings of the 6th IEEE and ACM International Symposium on Mixed and Augmented Reality 2007, Nara, Japan, 13–16 November 2007; pp. 225–234.
34. Jiang, Y.H.; Xiong, G.M.; Chen, H.Y.; Lee, D.J. Incorporating a wheeled vehicle model in a new monocular visual odometry algorithm for dynamic outdoor environments. Sensors 2014, 14, 16159–16180. [CrossRef] [PubMed]
35. Zhang, J.; Singh, S. Visual-lidar odometry and mapping: Low-drift, robust, and fast. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 26–30 May 2015; pp. 2174–2181.
36. Cheng, W.C. PSO algorithm particle filters for improving the performance of lane detection and tracking systems in difficult roads. Sensors 2012, 12, 17168–17185. [CrossRef] [PubMed]
37. Tapia-Espinoza, R.; Torres-Torriti, M. Robust lane sensing and departure warning under shadows and occlusions. Sensors 2013, 3, 3270–3298. [CrossRef] [PubMed]
38. Aly, M. Real time detection of lane markers in urban streets. In Proceedings of the IEEE Intelligent Vehicles Symposium 2008, Eindhoven, The Netherlands, 4–6 June 2008; pp. 7–12.
39. Bertozzi, M.; Broggi, A. GOLD: A parallel real-time stereo vision system for generic obstacle and lane detection. IEEE Trans. Image Process. 1998, 7, 62–81. [CrossRef] [PubMed]
40. Yenikaya, S.; Yenikaya, G.; Düven, E. Keeping the vehicle on the road: A survey on on-road lane detection systems. ACM Comput. Surv. 2013, 46, 2:1–2:43. [CrossRef]
41. Tao, Z.; Bonnifait, P.; Fremont, V.; Ibanez-Guzman, J. Lane marking aided vehicle localization. In Proceedings of the 16th IEEE International Conference on Intelligent Transportation Systems 2013, The Hague, The Netherlands, 6–9 October 2013; pp. 1509–1515.
42. Tao, Z.; Bonnifait, P.; Fremont, V.; Ibanez-Guzman, J. Mapping and localization using GPS, lane markings and proprioceptive sensors. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2013, Tokyo, Japan, 3–7 November 2013; pp. 406–412.
43. Schreiber, M.; Knoppel, C.; Franke, U. Laneloc: Lane marking based localization using highly accurate maps. In Proceedings of the IEEE Intelligent Vehicles Symposium 2013, Gold Coast, Australia, 23–26 June 2013; pp. 449–454.
44. Mattern, N.; Wanielik, G. Camera-based vehicle localization at intersections using detailed digital maps. In Proceedings of the 2010 IEEE/ION Position Location and Navigation Symposium (PLANS), Indian Wells, CA, USA, 4–6 May 2010; pp. 1100–1107.
45. Rose, C.; Britt, J.; Allen, J.; Bevly, D. An integrated vehicle navigation system utilizing lane-detection and lateral position estimation systems in difficult environments for GPS. IEEE Trans. Intell. Transp. Syst. 2014, 15, 2615–2629. [CrossRef]
46. Seo, Y.W.; Rajkumar, R. Tracking and estimation of ego-vehicle’s state for lateral localization. In Proceeding of the 17th International Conference on Intelligent Transportation Systems, Qingdao, China, 8–11 October 2014; pp. 1251–1257.
47. Marita, T.; Negru, M.; Danescu, R.; Nedevschi, S. Stop-line detection and localization method for intersection scenarios. In Proceedings of the IEEE 7th International Conference on Intelligent Computer Communication and Processing (ICCP 2011), Cluj-Napoca, Romania, 25–27 August 2011; pp. 293–298.
48. Lee, B.H.; Song, J.H.; Im, J.H.; Im, S.H.; Heo, M.B.; Jee, G.I. GPS/DR Error estimation for autonomous vehicle localization. Sensors 2015, 8, 20779–20798. [CrossRef] [PubMed]
49. Kamijo, S.; Gu, Y.; Hsu, L.-T. GNSS/INS/on-board aamera integration for vehicle self-localization in urban canyon. In Proceedings of the IEEE 18th International Conference on Intelligent Transportation Systems (ITSC 2015), Gran Canaria, Spain, 15–18 September 2015; pp. 2533–2538.
50. Garin, L.; van Diggelen, F.; Rousseau, J.M. Strobe & edge correlator multipath mitigation for code. In Proceedings of the the 9th International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GPS 1996), Kansas City, MO, USA, 17–20 September 1996; pp. 657–664.
51. Qin, B.; Chong, Z.J.; Bandyopadhyay, T.; Ang Jr, M.H.; Frazzoli, E.; Rus, D. Curb-intersection feature based monte carlo localization on urban roads. In Proceedings of the IEEE International Conference on Robotics and Automation 2012 (ICRA 2012), Saint Paul, MN, USA, 14–18 May 2012; pp. 2640–2646.