Hollowbush, R.R.[Richard R.],
Ultrasonic obstacle detector,
US_Patent5,059,946, Oct 22, 1991
WWW Link. Vehicles
BibRef
9110
Dombrowski, A.E.[Anthony E.],
School bus obstacle detection device,
US_Patent5,250,945, Oct 5, 1993
WWW Link.
BibRef
9310
Jefferis, B.[Brian],
Morgan, S.D.[Shaun D.],
Vehicle detection systems,
US_Patent5,339,081, Aug 16, 1994
WWW Link. Radar based
BibRef
9408
Hibino, K.[Katsuhiko],
Kurahashi, A.[Akira],
Hashimoto, M.[Mitsufumi],
System for distinguishing a vehicle traveling ahead based
on an adjustable probability distribution,
US_Patent5,510,990, Apr 23, 1996
WWW Link. Radar
BibRef
9604
Shisgal, B.Z.[Ben Z.],
Anderman, H.[Hanan],
Fashchik, Y.[Yosef],
Porat, Y.[Yariv],
Obstacle detection system for vehicles moving in reverse,
US_Patent5,574,426, Nov 12, 1996
WWW Link.
BibRef
9611
Yuan, Z.P.[Zhi-Ping],
Vehicular safety distance alarm system,
US_Patent5,627,510, May 6, 1997
WWW Link.
BibRef
9705
Kato, T.,
Ninomiya, Y.,
Masaki, I.,
An obstacle detection method by fusion of radar and motion stereo,
ITS(3), No. 3, September 2002, pp. 182-188.
IEEE Abstract.
0402
BibRef
Shimomura, N.,
Fujimoto, K.,
Oki, T.,
Muro, H.,
An algorithm for distinguishing the types of objects on the road using
laser radar and vision,
ITS(3), No. 3, September 2002, pp. 189-195.
IEEE Abstract.
0402
BibRef
Tsang, S.H.,
Hall, P.S.,
Hoare, E.G.,
Clarke, N.J.,
Advance Path Measurement for Automotive Radar Applications,
ITS(7), No. 3, September 2006, pp. 273-281.
IEEE DOI
0609
BibRef
Jimenez Ruiz, A.R.,
Seco Granja, F.,
A Short-Range Ship Navigation System Based on Ladar Imaging and Target
Tracking for Improved Safety and Efficiency,
ITS(10), No. 1, March 2009, pp. 186-197.
IEEE DOI
0903
BibRef
Zhao, H.,
Chiba, M.,
Shibasaki, R.,
Shao, X.,
Cui, J.,
Zha, H.,
A Laser-Scanner-Based Approach Toward Driving Safety and Traffic Data
Collection,
ITS(10), No. 3, September 2009, pp. 534-546.
IEEE DOI
0909
Laser scanner data. Use both for obstacles and collecting general data.
BibRef
Viikari, V.V.,
Varpula, T.,
Kantanen, M.,
Road-Condition Recognition Using 24-GHz Automotive Radar,
ITS(10), No. 4, December 2009, pp. 639-648.
IEEE DOI
0912
BibRef
Pietzsch, S.,
Vu, T.D.,
Burlet, J.,
Aycard, O.,
Hackbarth, T.,
Appenrodt, N.,
Dickmann, J.,
Radig, B.,
Results of a Precrash Application Based on Laser Scanner and
Short-Range Radars,
ITS(10), No. 4, December 2009, pp. 584-593.
IEEE DOI
0912
BibRef
Yamamoto, H.[Hiroshi],
Ishii, Y.[Yoshinori],
Yamazaki, K.[Katsuyuki],
Development and Evaluation of Roadside/Obstacle Detection Method Using
3D Scanned Data Processing,
IEICE(E95-D), No. 2, February 2012, pp. 540-541.
WWW Link.
1202
BibRef
Kim, T.[Taewung],
Jeong, H.Y.[Hyun-Yong],
A Novel Algorithm for Crash Detection Under General Road Scenes Using
Crash Probabilities and an Interactive Multiple Model Particle Filter,
ITS(15), No. 6, December 2014, pp. 2480-2490.
IEEE DOI
1412
Monte Carlo methods
BibRef
Lehtomaki, M.,
Jaakkola, A.,
Hyyppa, J.,
Lampinen, J.,
Kaartinen, H.,
Kukko, A.,
Puttonen, E.,
Hyyppa, H.,
Object Classification and Recognition From Mobile Laser Scanning
Point Clouds in a Road Environment,
GeoRS(54), No. 2, February 2016, pp. 1226-1239.
IEEE DOI
1601
Accuracy
BibRef
Kellner, D.,
Barjenbruch, M.,
Klappstein, J.,
Dickmann, J.,
Dietmayer, K.,
Tracking of Extended Objects with High-Resolution Doppler Radar,
ITS(17), No. 5, May 2016, pp. 1341-1353.
IEEE DOI
1605
Doppler radar
BibRef
Luo, H.[Huan],
Wang, C.[Cheng],
Wen, C.L.[Cheng-Lu],
Cai, Z.P.[Zhi-Peng],
Chen, Z.Y.[Zi-Yi],
Wang, H.Y.[Han-Yun],
Yu, Y.T.[Yong-Tao],
Li, J.[Jonathan],
Patch-Based Semantic Labeling of Road Scene Using Colorized Mobile
LiDAR Point Clouds,
ITS(17), No. 5, May 2016, pp. 1286-1297.
IEEE DOI
1605
Context
BibRef
Luo, H.[Huan],
Wang, C.[Cheng],
Wen, C.L.[Cheng-Lu],
Chen, Z.Y.[Zi-Yi],
Zai, D.,
Yu, Y.T.[Yong-Tao],
Li, J.[Jonathan],
Semantic Labeling of Mobile LiDAR Point Clouds via Active Learning
and Higher Order MRF,
GeoRS(56), No. 7, July 2018, pp. 3631-3644.
IEEE DOI
1807
Markov processes, image representation, image segmentation,
learning (artificial intelligence), optical radar,
semantic labeling
BibRef
Zhang, H.C.[Hao-Cheng],
Li, J.[Jonathan],
Cheng, M.[Ming],
Wang, C.[Cheng],
Rapid Inspection Of Pavement Markings Using Mobile Lidar Point Clouds,
ISPRS16(B1: 717-723).
DOI Link
1610
BibRef
Wang, X.,
Xu, L.,
Sun, H.,
Xin, J.,
Zheng, N.,
On-Road Vehicle Detection and Tracking Using MMW Radar and Monovision
Fusion,
ITS(17), No. 7, July 2016, pp. 2075-2084.
IEEE DOI
1608
millimetre wave radar
BibRef
Nijsure, Y.A.,
Kaddoum, G.,
Khaddaj Mallat, N.,
Gagnon, G.,
Gagnon, F.,
Cognitive Chaotic UWB-MIMO Detect-Avoid Radar for Autonomous UAV
Navigation,
ITS(17), No. 11, November 2016, pp. 3121-3131.
IEEE DOI
1609
Bayes methods
BibRef
Jung, H.[Ha_Rim],
Kim, U.M.[Ung-Mo],
The SSP-Tree: A Method for Distributed Processing of Range Monitoring
Queries in Road Networks,
IJGI(6), No. 11, 2017, pp. xx-yy.
DOI Link
1712
BibRef
Deng, Z.,
Zhou, L.,
Detection and Recognition of Traffic Planar Objects Using Colorized
Laser Scan and Perspective Distortion Rectification,
ITS(19), No. 5, May 2018, pp. 1485-1495.
IEEE DOI
1805
Cameras, Distortion, Feature extraction, Image color analysis,
Laser noise, Shape, Autonomous vehicle,
planar object detection and recognition
BibRef
Eltrass, A.[Ahmed],
Khalil, M.[Mohammed],
Automotive radar system for multiple-vehicle detection and tracking in
urban environments,
IET-ITS(12), No. 8, October 2018, pp. 783-792.
DOI Link
1809
BibRef
Ma, L.F.[Ling-Fei],
Li, Y.[Ying],
Li, J.[Jonathan],
Wang, C.[Cheng],
Wang, R.[Ruisheng],
Chapman, M.A.[Michael A.],
Mobile Laser Scanned Point-Clouds for Road Object Detection and
Extraction: A Review,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link
1811
BibRef
Hossain, M.A.[Md Anowar],
Elshafiey, I.[Ibrahim],
Al-Sanie, A.[Abdulhameed],
Waveform diversity for mutual interference mitigation in automotive
radars under realistic traffic environments,
SIViP(13), No. 1, February 2019, pp. 1-8.
Springer DOI
1901
BibRef
Lisowski, J.[Józef],
Mohamed-Seghir, M.[Mostefa],
Comparison of Computational Intelligence Methods Based on Fuzzy Sets
and Game Theory in the Synthesis of Safe Ship Control Based on
Information from a Radar ARPA System,
RS(11), No. 1, 2019, pp. xx-yy.
DOI Link
1901
BibRef
Stateczny, A.[Andrzej],
Kazimierski, W.[Witold],
Gronska-Sledz, D.[Daria],
Motyl, W.[Weronika],
The Empirical Application of Automotive 3D Radar Sensor for Target
Detection for an Autonomous Surface Vehicle's Navigation,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link
1906
BibRef
Lee, S.,
Lee, B.,
Lee, J.,
Kim, S.,
Statistical Characteristic-Based Road Structure Recognition in
Automotive FMCW Radar Systems,
ITS(20), No. 7, July 2019, pp. 2418-2429.
IEEE DOI
1907
Roads, Automotive engineering, Radar detection, Vehicles,
Support vector machines, Radar measurements,
support vector machine (SVM)
BibRef
Parmar, Y.[Yashrajsinh],
Natarajan, S.[Sudha],
Sobha, G.[Gayathri],
DeepRange: deep-learning-based object detection and ranging in
autonomous driving,
IET-ITS(13), No. 8, August 2019, pp. 1256-1264.
DOI Link
1908
BibRef
Simon, M.[Martin],
Milz, S.[Stefan],
Amende, K.[Karl],
Gross, H.M.[Horst-Michael],
Complex-YOLO: An Euler-Region-Proposal for Real-Time 3D Object
Detection on Point Clouds,
CVRoads18(I:197-209).
Springer DOI
1905
Lidar, automated driving.
BibRef
Vaquero, V.,
Sanfeliu, A.,
Moreno-Noguer, F.,
Hallucinating Dense Optical Flow from Sparse Lidar for Autonomous
Vehicles,
ICPR18(1959-1964)
IEEE DOI
1812
Laser radar, Optical imaging, Optical sensors, Image resolution,
Optical variables measurement, Training, Three-dimensional displays
BibRef
Razali, H.,
Ouarti, N.,
Lidarbox: A fast and accurate method for object proposals VIA lidar
point clouds for autonomous vehicles,
ICIP17(1352-1356)
IEEE DOI
1803
Automobiles, Autonomous vehicles, Laser radar, Proposals, Sensors,
Point-Clouds
BibRef
Chen, X.,
Ma, H.,
Wan, J.,
Li, B.,
Xia, T.,
Multi-view 3D Object Detection Network for Autonomous Driving,
CVPR17(6526-6534)
IEEE DOI
1711
Laser radar, Object detection, Proposals,
BibRef
Askeland, S.A.,
Ekman, T.,
Tracking With a High-Resolution 2D Spectral Estimation Based
Automotive Radar,
ITS(16), No. 5, October 2015, pp. 2418-2423.
IEEE DOI
1511
estimation theory
BibRef
Peasley, B.[Brian],
Birchfield, S.T.[Stanley T.],
Real-time obstacle detection and avoidance in the presence of
specular surfaces using an active 3D sensor,
WORV13(197-202)
IEEE DOI
1307
BibRef
Haberjahn, M.[Mathias],
Reulke, R.[Ralf],
Object Discrimination and Tracking in the Surroundings of a Vehicle by
a Combined Laser Scanner Stereo System,
CVVT10(225-234).
Springer DOI
1109
BibRef
Catala-Prat, A.,
Köster, F.,
Reulke, R.,
Image And Laser Scanner Processing As Confident Cues For Object
Detection In Driving Situations,
CloseRange10(xx-yy).
PDF File.
1006
BibRef
Izumi, K.,
Watanabe, K.,
Shindo, M.,
Sato, R.,
Acquisition of Obstacle Avoidance Behaviors for a Quadruped Robot Using
Visual and Ultrasonic Sensors,
ICARCV06(1-6).
IEEE DOI
0612
BibRef
Zhang, F.,
Justh, E.W.,
Krishnaprasad, P.S.,
Boundary following using gyroscopic control,
DC04(V: 5204-5209).
IEEE DOI For guidance of space objects.
BibRef
0400
Kalyan, B.,
Balasuriya, A.,
Ura, T.,
Wijesoma, S.,
Sonar and vision based navigation schemes for autonomous underwater
vehicles,
ICARCV04(I: 437-442).
IEEE DOI
0412
BibRef
Sole, A.,
Mano, O.,
Stein, G.P.,
Kumon, H.,
Tamatsu, Y.,
Shashua, A.,
Solid or not solid: vision for radar target validation,
IVS04(819-824).
IEEE DOI
0411
Radar in dense urban traffic.
Vision to validate radar.
BibRef
Mendes, A.,
Bento, L.C.,
Nunes, U.,
Multi-target detection and tracking with a laser scanner,
IVS04(796-801).
IEEE DOI
0411
For collision avoidance. Detect other vehicles.
BibRef
Sugimoto, S.,
Tateda, H.,
Takahashi, H.,
Okutomi, M.,
Obstacle detection using millimeter-wave radar and its visualization on
image sequence,
ICPR04(III: 342-345).
IEEE DOI
0409
BibRef
Song, K.T.[Kai-Tai],
Chen, C.H.[Chih-Hao],
Huang, C.H.C.[Cheng-Hsien Chiu],
Design and experimental study of an ultrasonic sensor system for
lateral collision avoidance at low speeds,
IVS04(647-652).
IEEE DOI
0411
BibRef
Hancock, J.,
Laser Intensity-Based Obstacle Detection and Tracking,
CMU-RI-TR-99-01, January, 1999.
HTML Version.
BibRef
9901
Chapter on Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following continues in
Airplane Obstacles, Collision Detection, Sense and Avoid, Aircraft Landings .