Recognition and tracking of spatial-temporal congested traffic patterns on freeways

被引:86
|
作者
Kerner, BS [1 ]
Rehborn, H [1 ]
Aleksic, M [1 ]
Haug, A [1 ]
机构
[1] Daimler Chrysler AG, RIC, TS, Telemat Res, D-73734 Esslingen, Germany
关键词
local traffic measurements on freeways; classification of traffic phases; tracking of spatial-temporal congested patterns; freeway bottlenecks; suitability of the freeway infrastructure for congested pattern recognition; traffic control center; field trial evaluation of models ASDA/FOTO; three-phase traffic theory; wide moving jams; synchronized traffic flow;
D O I
10.1016/j.trc.2004.07.015
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
The two models FOTO (Forecasting of Traffic Objects) and ASDA (Automatische Staudynamikanalyse: Automatic Tracking of Moving Traffic Jams) for the automatic recognition and tracking of congested spatial-temporal traffic flow patterns on freeways are presented. The models are based on a spatial-temporal traffic phase classification made in the three-phase traffic theory by Kerner. In this traffic theory, in congested traffic two different phases are distinguished: "wide moving jam" and "synchronized flow". The model FOTO is devoted to the identification of traffic phases and to the tracking of synchronized flow. The model ASDA is devoted to the tracking of the propagation of moving jams. The general approach and the different extensions of the models FOTO and ASDA are explained in detail. It is stressed that the models FOTO and ASDA perform without any validation of model parameters in different environmental and traffic conditions. Results of the online application of the models FOTO and ASDA at the TCC (Traffic Control Center) of Hessen near Frankfurt (Germany) are presented and evaluated. (C) 2004 Elsevier Ltd. All rights reserved.
引用
收藏
页码:369 / 400
页数:32
相关论文
共 50 条
  • [1] Recognition and tracking of spatial-temporal congested traffic patterns on freeways
    Kerner, Boris S.
    Rehborn, Hubert
    Aleksic, Mario
    Haug, Andreas
    [J]. Transp. Res. Part C Emerg. Technol., 1600, 5 (369-400):
  • [2] Tracking of congested traffic patterns on freeways in California
    Kerner, B.S.
    Rehborn, H.
    Haug, A.
    Maiwald-Hiller, I.
    [J]. Traffic Eng. Control, 10 (380-385):
  • [3] Microscopic theory of spatial-temporal congested traffic patterns at highway bottlenecks
    Kerner, BS
    Klenov, SL
    [J]. PHYSICAL REVIEW E, 2003, 68 (03):
  • [4] Methods for automatic tracing and forecasting of spatial-temporal congested patterns: A review
    Kerner, BS
    Rehborn, H
    Aleksic, M
    Haug, A
    [J]. HUMAN BEHAVIOUR AND TRAFFIC NETWORKS, 2004, : 251 - 284
  • [5] Multiple Traffic Target Tracking with Spatial-Temporal Affinity Network
    Sun, Yamin
    Zhao, Yue
    Wang, Sirui
    [J]. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2022, 2022
  • [6] Multiple Traffic Target Tracking with Spatial-Temporal Affinity Network
    Sun, Yamin
    Zhao, Yue
    Wang, Sirui
    [J]. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2022, 2022
  • [7] CONTINUUM MODELING OF TRAFFIC DYNAMICS FOR CONGESTED FREEWAYS
    MICHALOPOULOS, PG
    YI, P
    LYRINTZIS, AS
    [J]. TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 1993, 27 (04) : 315 - 332
  • [8] Capturing Spatial-Temporal Traffic Patterns: A Dynamic Partitioning Strategy for Heterogeneous Traffic Networks
    Peng, Xianyue
    Wang, Hao
    [J]. IEEE ACCESS, 2024, 12 : 131982 - 131992
  • [9] Empirical macroscopic features of spatial-temporal traffic patterns at highway bottlenecks
    Kerner, BS
    [J]. PHYSICAL REVIEW E, 2002, 65 (04):
  • [10] Empirical macroscopic features of spatial-temporal traffic patterns at highway bottlenecks
    Kerner, Boris S.
    [J]. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 2002, 65 (04): : 1 - 046138