An adaptive real-time intravehicle network protocol for intelligent vehicle systems

被引:6
|
作者
Richardson, PC [1 ]
Elkateeb, A
Sieh, L
机构
[1] Univ Michigan, Dept Elect & Comp Engn, Dearborn, MI 48128 USA
[2] USA, Tank Automot Res Dev & Engn Ctr, Warren, MI 48397 USA
关键词
adaptive network protocols; intelligent vehicle systems (IVSs); real-time networks; transient faults;
D O I
10.1109/TVT.2004.833616
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
Intelligent vehicle systems are inherently real-time systems that must perform continuous operations, often in harsh and unpredictable environments. The real-time network infrastructure is a key technology enabler for these systems. This effort presents an adaptive real-time network protocol (ARTNP) that provides multidimensional quality-of-service support for time-sensitive data under nominal conditions and during transient surges. Transient surges (e.g., the retransmission of corrupt or lost data and the unspecified arrival of sporadic messages) are problematic in that they can temporarily overload the network, causing message transmissions to be late. ARTNP is a fully distributed protocol that specifically addresses the issue of transient surges in network loading. Under nominal conditions, ARTNP can guarantee the time constraints of any messages at optimally high levels of network utilization. During a transient surge, ARTNP will detect the surge and alter the ordering of message transmissions to sustain the timely transmission of critical messages. The CAN protocol is selected as the underlying network, because of its wide spread use in vehicular systems. Simulations compare the performance of ARTNP against an optimal nonadaptive approach.
引用
下载
收藏
页码:1594 / 1606
页数:13
相关论文
共 50 条
  • [41] A framework for developing intelligent real-time scheduling systems
    McPherson, Ronald F.
    White, K. Preston, Jr.
    HUMAN FACTORS AND ERGONOMICS IN MANUFACTURING, 2006, 16 (04): : 385 - 408
  • [42] Mixed integrated systems for real-time intelligent processing
    Yamakawa, T
    INTELLIGENT AUTOMATION AND SOFT COMPUTING, 2004, 10 (02): : 67 - 67
  • [43] Variable depth resolution for intelligent real-time systems
    Foxvog, D
    Taipale, T
    SEKE '96: THE 8TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING, PROCEEDINGS, 1996, : 400 - 407
  • [44] Real-time intelligent failure diagnosis of electromechanical systems
    Chetate, B.
    Lebaroud, A.
    Aitouche, M.A.
    Advances in Modeling and Analysis B, 1999, 41 (01): : 39 - 2
  • [45] Automatic Mobile Vehicle for Adaptive Real-time Communication Relay
    Hu, Hai
    Wang, Furong
    Zhang, Fan
    Jia, Weijia
    Tang, Ge
    ICDCS: 2009 INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS WORKSHOPS, 2009, : 32 - +
  • [46] An adaptive evolutionary approach for real-time vehicle routing and dispatching
    Barkaoui, Mohamed
    Gendreau, Michel
    COMPUTERS & OPERATIONS RESEARCH, 2013, 40 (07) : 1766 - 1776
  • [47] A real-time adaptive signal control in a connected vehicle environment
    Feng, Yiheng
    Head, K. Larry
    Khoshmagham, Shayan
    Zamanipour, Mehdi
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2015, 55 : 460 - 473
  • [48] Adaptive Vehicle Detection for Real-time Autonomous Driving System
    Hemmati, Maryam
    Biglari-Abhari, Morteza
    Niar, Smail
    2019 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION (DATE), 2019, : 1034 - 1039
  • [49] Adaptive and Real-time Optimal Control for Adaptive Optics Systems
    Doelman, Niek
    Fraanje, Rufus
    Houtzager, Ivo
    Verhaegen, Michel
    EUROPEAN JOURNAL OF CONTROL, 2009, 15 (3-4) : 480 - 488
  • [50] Intelligent Vehicle Counting and Classification Sensor for Real-Time Traffic Surveillance
    Balid, Walid
    Tafish, Hasan
    Refai, Hazem H.
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2018, 19 (06) : 1784 - 1794