A Review of Sensor Technologies for Perception in Automated Driving

被引:180
|
作者
Marti, Enrique [1 ]
Perez, Joshue [1 ]
Angel de Miguel, Miguel [2 ]
Garcia, Fernando [2 ]
机构
[1] Fdn Tecnalia, Automated Driving Grp, Derio 48160, Spain
[2] Univ Carloss III Madrid, Leganes 28911, Spain
关键词
Cameras; Robot sensing systems; Accidents; Laser radar; Roads; PEDESTRIAN DETECTION; VEHICLE; RADAR; VISION; SYSTEM; LANE; TRACKING; LIDAR; ROAD;
D O I
10.1109/MITS.2019.2907630
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
After more than 20 years of research, ADAS are common in modern vehicles available in the market. Automated Driving systems, still in research phase and limited in their capabilities, are starting early commercial tests in public roads. These systems rely on the information provided by on-board sensors, which allow to describe the state of the vehicle, its environment and other actors. Selection and arrangement of sensors represent a key factor in the design of the system. This survey reviews existing, novel and upcoming sensor technologies, applied to common perception tasks for ADAS and Automated Driving. They are put in context making a historical review of the most relevant demonstrations on Automated Driving, focused on their sensing setup. Finally, the article presents a snapshot of the future challenges for sensing technologies and perception, finishing with an overview of the commercial initiatives and manufacturers alliances that will show the intention of the market in sensors technologies for Automated Vehicles.
引用
收藏
页码:94 / 108
页数:15
相关论文
共 50 条
  • [1] Perception sensor modeling for virtual validation of automated driving
    Cao, Peng
    Wachenfeld, Walther
    Winner, Hermann
    IT-INFORMATION TECHNOLOGY, 2015, 57 (04): : 243 - 251
  • [2] Exploiting Redundancy for Reliability Analysis of Sensor Perception in Automated Driving Vehicles
    Berk, Mario
    Schubert, Olaf
    Kroll, Hans-Martin
    Buschardt, Boris
    Straub, Daniel
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2020, 21 (12) : 5073 - 5085
  • [3] Classification of sensor Errors for the Statistical Simulation of Environmental Perception in Automated Driving Systems
    Hanke, Timo
    Hirsenkorn, Nils
    Dehlink, Bernhard
    Rauch, Andreas
    Rasshofer, Ralph
    Biebl, Erwin
    2016 IEEE 19TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2016, : 643 - 648
  • [4] Reliability assessment of multi-sensor perception system in automated driving functions
    Qiu, Minhao
    Bazan, Peter
    Antesberger, Tobias
    Bock, Florian
    German, Reinhard
    2021 IEEE 26TH PACIFIC RIM INTERNATIONAL SYMPOSIUM ON DEPENDABLE COMPUTING (PRDC 2021), 2021, : 104 - 112
  • [5] Resilience of Spatial Environment Perception Toward Fully Automated Driving: A Review
    Kahlert, Moritz
    Peitzmeier, Henning
    Evans, Daniel
    Talits, Kevin
    Kortmann, Felix
    Tebruegge, Claas
    IEEE SENSORS JOURNAL, 2024, 24 (14) : 21801 - 21812
  • [6] Automated Ground Vehicle (AGV) and Sensor Technologies- A Review
    Lynch, Liam
    Newe, Thomas
    Clifford, John
    Coleman, Joseph
    Walsh, Joseph
    Toal, Daniel
    2018 12TH INTERNATIONAL CONFERENCE ON SENSING TECHNOLOGY (ICST), 2018, : 347 - 352
  • [7] Technologies for highly automated driving on highways
    Kämpchen, Nico
    Aeberhard, Michael
    Ardelt, Michael
    Rauch, Sebastian
    ATZ worldwide, 2012, 114 (06) : 34 - 38
  • [8] Recent Advances in Automated Driving Technologies
    Lenzo, Basilio
    de Castro, Ricardo
    Chen, Yan
    Xu, Shaobing
    Zhang, Xudong
    IEEE VEHICULAR TECHNOLOGY MAGAZINE, 2022, 17 (04): : 16 - 17
  • [9] MASS: Mobility-Aware Sensor Scheduling of Cooperative Perception for Connected Automated Driving
    Jia, Yukuan
    Mao, Ruiqing
    Sun, Yuxuan
    Zhou, Sheng
    Niu, Zhisheng
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2023, 72 (11) : 14962 - 14977
  • [10] Multi-sensor Fusion and Cooperative Perception for Autonomous Driving A Review
    Xiang, Chao
    Feng, Chen
    Xie, Xiaopo
    Shi, Botian
    Lu, Hao
    Lv, Yisheng
    Yang, Mingchuan
    Niu, Zhendong
    IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE, 2023, 15 (05) : 36 - 58