Development of an Integrated Driving path Estimation Algorithm for ACC and AEBS Using Multi-sensor Fusion

被引:0
|
作者
Lee, Dongwoo [1 ]
Kim, Beomjun [1 ]
Yi, Kyoungsu [1 ]
Jaewan, Lee [2 ]
机构
[1] Seoul Natl Univ, Sch Mech & Aerosp Engn, Seoul, South Korea
[2] Korea Automobile Testing & Res Inst, Korea Transportat Safety Author, Ansan, South Korea
来源
2012 IEEE 75TH VEHICULAR TECHNOLOGY CONFERENCE (VTC SPRING) | 2012年
基金
新加坡国家研究基金会;
关键词
Driving path; Sensor fusion; Vision sensor; Adaptive cruise control; Advanced emergency braking system;
D O I
暂无
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
This paper presents an integrated driving path estimation algorithm for adaptive cruise control system and advanced emergency braking system using multi-sensor fusion. This algorithm is developed to predict the ego-vehicle's path accurately and improve primary target detection rate. The path prediction is consisted of two prediction process; one is based on vehicle states and the other is based on vision data. For application to dynamic maneuvering situation, the driving mode index which allows a detection of the driver maneuver intention is proposed. In accordance with the driving mode, the two types of driving path information are integrated finally. The proposed driving path estimation algorithm has been investigated via closed-loop simulation. It has been shown that the proposed driving path estimation algorithm enhance the capabilities of adaptive cruise control and advanced emergency braking system functions by providing the ego-vehicles path accurately, especially in dynamic maneuvering situation.
引用
收藏
页数:5
相关论文
共 50 条
  • [1] Multi-sensor fusion development
    Bish, Sheldon
    Rohrer, Matthew
    Scheffel, Peter
    Bennett, Kelly
    GROUND/AIR MULTISENSOR INTEROPERABILITY, INTEGRATION, AND NETWORKING FOR PERSISTENT ISR VII, 2016, 9831
  • [2] Multi-sensor fusion using an adaptive multi-hypothesis tracking algorithm
    Kester, LJHM
    MULTISENSOR, MULTISOURCE INFORMATION FUSION: ARCHITECTURES, ALGORITHMS, AND APPLICATIONS 2003, 2003, 5099 : 164 - 172
  • [3] 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
  • [4] Global Pose Estimation using Multi-Sensor Fusion for Outdoor Augmented Reality
    Schall, Gerhard
    Wagner, Daniel
    Reitmayr, Gerhard
    Taichmann, Elise
    Wieser, Manfred
    Schmalstieg, Dieter
    Hofmann-Wellenhof, Bernhard
    2009 8TH IEEE INTERNATIONAL SYMPOSIUM ON MIXED AND AUGMENTED REALITY - SCIENCE AND TECHNOLOGY, 2009, : 153 - +
  • [5] Walking Trajectory Estimation Using Multi-Sensor Fusion and a Probabilistic Step Model
    Rabb, Ethan
    Steckenrider, John Josiah
    SENSORS, 2023, 23 (14)
  • [6] Obstacle detection using multi-sensor fusion
    Qing Lin
    Youngjoon Han
    Namki Lee
    Hwanik Chung
    JournalofMeasurementScienceandInstrumentation, 2013, 4 (03) : 247 - 251
  • [7] Environment recognition based on multi-sensor fusion for autonomous driving vehicles
    Weon I.-S.
    Lee S.-G.
    Journal of Institute of Control, Robotics and Systems, 2019, 25 (02): : 125 - 131
  • [8] Modular Multi-Sensor Fusion: A Collaborative State Estimation Perspective
    Jung, Roland
    Weiss, Stephan
    IEEE ROBOTICS AND AUTOMATION LETTERS, 2021, 6 (04) : 6891 - 6898
  • [9] Lane Detection Algorithm in Curves Based on Multi-Sensor Fusion
    Zhang, Qiang
    Liu, Jianze
    Jiang, Xuedong
    SENSORS, 2023, 23 (12)
  • [10] Visual Marker based Multi-Sensor Fusion State Estimation
    Luis Sanchez-Lopez, Jose
    Arellano-Quintana, Victor
    Tognon, Marco
    Campoy, Pascual
    Franchi, Antonio
    IFAC PAPERSONLINE, 2017, 50 (01): : 16003 - 16008