Software Tool for Evaluation of Multi-Sensor Object Tracking in ADAS Systems

被引:0
|
作者
Medaglini, A. [1 ]
Bartolini, S. [1 ]
Di Massa, V. [2 ]
Dini, F. [3 ]
机构
[1] Department of Information Engineering and Mathematics, University of Siena, Via Roma 56, Siena, Italy
[2] Thales Italy, Via Lucchese 33, Sesto Fiorentino, Italy
[3] Magenta srl, Via B. Pasquini 6, Florence, Italy
来源
Ada User Journal | 2022年 / 43卷 / 03期
关键词
Advanced driver assistance systems - Automobile drivers - Autonomous vehicles - Decision making - Tracking (position);
D O I
暂无
中图分类号
学科分类号
摘要
Nowadays, the innovations of AI and other automated decision-making software are spreading to many differ-ent areas. The automotive field in particular is rapidly shifting towards the concepts of Advanced Driver Assis-tance Systems (ADAS), which could bring huge benefits in the future. However, before being able to use these tools, many assurances are required regarding their functioning and safety. To this end, several control tech-niques exist to evaluate the performance of this software, but a reliable and repeatable method for evaluating complex scenarios and corner cases is still lacking. In this paper, we propose a suite of tools for the generation and analysis of synthetic tests, aimed at evaluating and an-alyzing the functioning of autonomous driving systems in order to measure their effectiveness and drive their development. © 2022, Ada-Europe. All rights reserved.
引用
收藏
页码:177 / 186
相关论文
共 50 条
  • [41] Multi-sensor multi-object tracking with different fields-of-view using the LMB filter
    Li, Suqi
    Battistelli, Giorgio
    Chisci, Luigi
    Yi, Wei
    Wang, Bailu
    Kong, Lingjiang
    2018 21ST INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION), 2018, : 1201 - 1208
  • [42] Object recognition for a multi-sensor measuring system
    Brenner, C
    Fritsch, D
    VIDEOMETRICS V, 1997, 3174 : 197 - 206
  • [43] Multi-sensor, probabilistic multi-hypothesis tracking
    Krieg, ML
    Gray, DA
    ADFS-96 - FIRST AUSTRALIAN DATA FUSION SYMPOSIUM, 1996, : 153 - 158
  • [44] A Multi-Sensor Approach for Multi-Joint Tracking
    Ando, Bruno
    Graziani, Salvatore
    Manenti, Mattia
    Greco, Danilo
    2024 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE, I2MTC 2024, 2024,
  • [45] Performance Evaluation of Multiband Multi-Sensor Spectrum Sensing Systems
    Liang, Jason C. K.
    Blostein, Steven D.
    2011 IEEE GLOBECOM WORKSHOPS (GC WKSHPS), 2011, : 1002 - 1007
  • [46] Multi-sensor tracking on a grid-II
    Sworder, D. D.
    Boyd, J. E.
    Hutchins, R. G.
    Elliott, R. J.
    2005 39th Asilomar Conference on Signals, Systems and Computers, Vols 1 and 2, 2005, : 574 - 578
  • [47] COLLABORATIVE MULTI-SENSOR TRACKING AND DATA FUSION
    DeMars, Kyle J.
    McCabe, James S.
    Darling, Jacob E.
    SPACEFLIGHT MECHANICS 2015, PTS I-III, 2015, 155 : 1089 - 1108
  • [48] Methods of evaluating multi-sensor tracking performance
    Desbois, M
    FUSION'98: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MULTISOURCE-MULTISENSOR INFORMATION FUSION, VOLS 1 AND 2, 1998, : 642 - 647
  • [49] Multi-Sensor Tracking with SPRT in an Autonomous Vehicle
    Stess, Marek
    Schildwaechter, Christian
    Mersheeva, Vera
    Ortmeier, Frank
    Wagner, Bernardo
    2016 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), 2016, : 252 - 257
  • [50] Multi-sensor identity tracking with Event Graphs
    Morton, Peter
    Douillard, Bertrand
    Underwood, James
    2013 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2013, : 4742 - 4748