A Location Cloud for Highly Automated Driving

被引:3
作者
Redzic, Ogi [1 ]
Rabel, Dietmar [2 ]
机构
[1] HERE, 500 W Madison St 32, Chicago, IL 60661 USA
[2] HERE, D-65824 Schwalbach, Germany
来源
Road Vehicle Automation 2 | 2015年
关键词
Highly automated driving; Autonomous driving; High definition maps; Location; Vehicle localization; Cloud;
D O I
10.1007/978-3-319-19078-5_5
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
For highly and, ultimately, fully automated driving to become a reality and gain broad market acceptance, industry participants must resolve three critical technological problems. The first concerns the car's ability to localize itself to centimeter-level precision: 'where exactly am I?' The second relates to the car's ability to recognize and react to events occurring on the road beyond the reach of its onboard sensors: 'what lies ahead?' And the third concerns the car's ability to drive in a way that is acceptable to the car's occupants and other road users: 'how can I get there comfortably?' In this paper, the authors outline the work of their organization, HERE, in developing a location cloud for highly automated driving that offers resolutions to each of these problems.
引用
收藏
页码:49 / 60
页数:12
相关论文
共 50 条
  • [21] Sleep in highly automated driving: Takeover performance after waking up
    Woerle, Johanna
    Metz, Barbara
    Othersen, Ina
    Baumann, Martin
    ACCIDENT ANALYSIS AND PREVENTION, 2020, 144 (144)
  • [22] The role of driver models in testing highly-automated driving: a survey
    Lemmer, Markus
    Schwab, Stefan
    Hohmann, Soeren
    AT-AUTOMATISIERUNGSTECHNIK, 2023, 71 (01) : 16 - 26
  • [23] Review on Status and Challenges of Crowdsourced Updating of Highly Automated Driving Maps
    Yang M.-M.
    Jiang K.
    Wen T.-P.
    Chen H.-X.
    Huang J.
    Zhang H.
    Huang J.-Q.
    Tang X.-W.
    Yang D.-G.
    Zhongguo Gonglu Xuebao/China Journal of Highway and Transport, 2023, 36 (05): : 244 - 259
  • [24] Highly Automated Driving on Freeways in Real Traffic Using a Probabilistic Framework
    Ardelt, Michael
    Coester, Constantin
    Kaempchen, Nico
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2012, 13 (04) : 1576 - 1585
  • [25] Drivers' individual design preferences of takeover requests in highly automated driving
    Brandenburg S.
    Epple S.
    i-com, 2019, 18 (02) : 167 - 178
  • [26] Automatic Generation of Critical Test Cases for the Development of Highly Automated Driving Functions
    Baumann, Daniel
    Pfeffer, Raphael
    Sax, Eric
    2021 IEEE 93RD VEHICULAR TECHNOLOGY CONFERENCE (VTC2021-SPRING), 2021,
  • [27] The ergonomic value of a bidirectional haptic interface when driving a highly automated vehicle
    Martin Kienle
    Daniel Damböck
    Heiner Bubb
    Klaus Bengler
    Cognition, Technology & Work, 2013, 15 : 475 - 482
  • [28] The Effect of Surrounding Scenery Complexity on the Transfer of Control Time in Highly Automated Driving
    Wiehr, Frederik
    Cakar, Baris
    Daiber, Florian
    Krueger, Antonio
    IUI '21 - 26TH INTERNATIONAL CONFERENCE ON INTELLIGENT USER INTERFACES, 2021, : 92 - 97
  • [29] On cognitive management and non-causal reasoning for enabling highly automated driving
    Panagiotopoulos, Ilias E.
    Karathanasopoulou, Konstantina N.
    Dimitrakopoulos, George J.
    2021 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE (CSCI 2021), 2021, : 1856 - 1861
  • [30] Confidence Arguments for Evidence of Performance in Machine Learning for Highly Automated Driving Functions
    Burton, Simon
    Gauerhof, Lydia
    Sethy, Bibhuti Bhusan
    Habli, Ibrahim
    Hawkins, Richard
    COMPUTER SAFETY, RELIABILITY, AND SECURITY, SAFECOMP 2019, 2019, 11699 : 365 - 377