Road Traffic Density Estimation Based on Heterogeneous Data Fusion

被引：0
|
作者：
Zissner, Philipp [1 ]
Rettore, Paulo H. L. [1 ]
Santos, Bruno P. [2 ]
Lopes, Roberto Rigolin F. [1 ]
Sevenich, Peter [1 ]
机构：
[1] Fraunhofer FKIE, Dept Commun Syst, Bonn, Germany
[2] Univ Fed Ouro Preto, Dept Comp & Syst, Joao Monlevade, Brazil
来源：
2022 27TH IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS (IEEE ISCC 2022) | 2022年
关键词：
ITS; Smart Cities; Traffic estimation; Data Fusion;
D O I：
10.1109/ISCC55528.2022.9912917
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This investigation starts with the hypothesis that fusing heterogeneous data sources can increase the data coverage and improve the accuracy of traffic-related applications in Intelligent Transportation Systems (ITS). Therefore, we designed (i) a Data Fusion on Intelligent Transportation Systems (DataFITS) framework that allows collecting data from numerous sources and fusing them according to spatial and temporal criteria; (ii) a traffic estimation method that groups road segments into regions, identify correlations between them, and measure the traffic distribution to estimate traffic. As a result, DataFITS increased by 130% the number of road segments coverage and enhanced, by fusion process, around 35% of road overlapping data sources. We evaluate the traffic estimation of the 15 most correlated regions, where the fused data together with correlated areas resulted in the best traffic estimation accuracy by reaching up to 40% in some cases and 9% on average.
引用
收藏
页数：6
相关论文
共 50 条
  • [1] Traffic Density Estimation under Heterogeneous Traffic Conditions using Data Fusion
    Anand, R. Asha
    Vanajakshi, Lelitha
    Subramanian, Shankar C.
    [J]. 2011 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), 2011, : 31 - 36
  • [2] Data Fusion-Based Traffic Density Estimation and Prediction
    Anand, Asha
    Ramadurai, Gitakrishnan
    Vanajakshi, Lelitha
    [J]. JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS, 2014, 18 (04) : 367 - 378
  • [3] ROAD TRAFFIC MEASUREMENT AND RELATED DATA FUSION METHODOLOGY FOR TRAFFIC ESTIMATION
    Tettamanti, Tamas
    Horvath, MartonTamas
    Varga, Istvan
    [J]. TRANSPORT AND TELECOMMUNICATION JOURNAL, 2014, 15 (04) : 269 - 279
  • [4] TRAFFIC DENSITY STATE ESTIMATION BASED ON ACOUSTIC FUSION
    Joshi, Vikas
    Rajamani, Nithya
    Prathapaneni, Naveen
    Subramaniam, L. V.
    [J]. 2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2013, : 478 - 482
  • [5] On the estimation of pollutants in road tunnels based on traffic data
    Pribyl, Ondrej
    Pribyl, Pavel
    [J]. 2016 ELEKTRO 11TH INTERNATIONAL CONFERENCE, 2016, : 456 - 461
  • [6] Roadside Acoustic Signals based Road Traffic Density Estimation
    Jadhav, Pradnya
    Sawarkar, S. D.
    Pete, D. J.
    [J]. 2018 FOURTH INTERNATIONAL CONFERENCE ON COMPUTING COMMUNICATION CONTROL AND AUTOMATION (ICCUBEA), 2018,
  • [7] Road Data Enrichment Framework Based on Heterogeneous Data Fusion for ITS
    Rettore, Paulo H. L.
    Santos, Bruno P.
    Lopes, Roberto Rigolin F.
    Maia, Guilherme
    Villas, Leandro A.
    Loureiro, Antonio A. F.
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2020, 21 (04) : 1751 - 1766
  • [8] Traffic state estimation based on data fusion techniques
    Cipriani, E.
    Gori, S.
    Mannini, L.
    [J]. 2012 15TH INTERNATIONAL IEEE CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2012, : 1477 - 1482
  • [9] A data-driven optimization-based approach for freeway traffic state estimation based on heterogeneous sensor data fusion
    Zhang, Jinyu
    Huang, Di
    Liu, Zhiyuan
    Zheng, Yifei
    Han, Yu
    Liu, Pan
    Huang, Wei
    [J]. TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2024, 189
  • [10] Solution for the Robust Estimation of Heterogeneous Data Fusion Based on Classification Estimation
    Tao, Yeqing
    Li, Xinchuan
    Chen, Hao
    Yang, Juan
    [J]. JOURNAL OF SURVEYING ENGINEERING, 2024, 150 (03)
12345