Applicability of an automatic pneumatic-tube-based traffic counting device for collecting data under mixed traffic

被引:5
|
作者
Puan, O. C. [1 ]
Nor, N. S. M. [2 ]
Mashros, N. [1 ]
Hainin, M. R. [1 ]
机构
[1] Univ Teknol Malaysia, Fac Engn, Sch Civil Engn, Skudai 81310, Johor, Malaysia
[2] Jabatan Kerja Raya Johor, Pasukan Projek Persekutuan Negeri Johor, Iskandar Puteri 79582, Johor, Malaysia
来源
INTERNATIONAL CONFERENCE ON AGRICULTURAL TECHNOLOGY, ENGINEERING AND ENVIRONMENTAL SCIENCES 2019 | 2019年 / 365卷
关键词
D O I
10.1088/1755-1315/365/1/012032
中图分类号
S2 [农业工程];
学科分类号
0828 ;
摘要
Traffic volume and composition data can be collected using several techniques such as manual, camera video recordings and automatic traffic count devices installed across the road pavement. An automatic traffic count device is often used for long hours of traffic data collection exercises. In view that the accuracy of the data is an important aspect of data analysis, this paper discusses the applicability of an automatic traffic count device to be used for traffic volume and composition data collections based on Malaysian vehicle classification system, i.e. where traffic is characterised by various types of vehicles or mixed traffic. The automatic traffic count (ATC) used in the study was the pneumatic tube based equipment known as Metrocount@5600. The data used for validating the ATC was obtained using a video recording technique. The data was collected at four different sites to ensure the result of the analysis is reliable. A video camera and ATC were installed at each of the sites considered in the study. Traffic volumes and compositions from video recordings were extracted manually based on five classes of vehicles, i.e. cars and small vans, medium trucks and lorries with two axles, large trucks and lorries with three and more axles, buses and motorcycles. The ATC was set to classify vehicle types using one of the equipment's default setting, i.e. 13 classes (Scheme F). The data retrieved from the ATC was reorganised based on the vehicle classifications used in the data collected using the video recording technique. Twenty datasets of vehicles composition from four sites were used in the analysis. The result of the statistical analysis showed that there is no significant different in traffic volumes and compositions obtained using both techniques. The finding implies that an automatic pneumatic-tube-based traffic counting device such as MetroCount@5600 with scheme F can be used as an alternative technique to collect traffic volumes and compositions data based on five standard classes of vehicles classification system.
引用
收藏
页数:11
相关论文
共 50 条
  • [1] Pattern Recognition of Vehicle Types and Reliability Analysis of Pneumatic Tube Test Data under Mixed Traffic Condition
    Liu Bohang
    Li Qingbing
    Chen Duiyong
    Sun Hailong
    2010 2ND INTERNATIONAL ASIA CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS (CAR 2010), VOL 3, 2010, : 44 - 47
  • [2] A Trajectory Based Method of Automatic Counting of Cyclist in Traffic Video Data
    Shahraki, Farideh Foroozandeh
    Yazdanpanah, Ali Pour
    Regentova, Emma E.
    Muthukumar, Venkatesan
    INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS, 2017, 26 (04)
  • [3] Data accuracy on automatic traffic counting: The SMART project results
    Bellucci P.
    Cipriani E.
    European Transport Research Review, 2010, 2 (04) : 175 - 187
  • [4] Validation of Bicycle Counts from Pneumatic Tube Counters in Mixed Traffic Flows
    Brosnan, Martin
    Petesch, Michael
    Pieper, Jason
    Schumacher, Scott
    Lindsey, Greg
    TRANSPORTATION RESEARCH RECORD, 2015, (2527) : 80 - 89
  • [5] Automatic traffic data extraction tool for mixed traffic conditions using image processing techniques
    Diwakar, Priyanka
    Landge, Vishrut S.
    Jain, Udit
    Kulkarni, Pranav
    INNOVATIVE INFRASTRUCTURE SOLUTIONS, 2024, 9 (05)
  • [6] Traffic Data Collection under Mixed Traffic Conditions Using Video Image Processing
    Mallikarjuna, C.
    Phanindra, A.
    Rao, K. Ramachandra
    JOURNAL OF TRANSPORTATION ENGINEERING, 2009, 135 (04) : 174 - 182
  • [7] A Vehicular Mobility Model Based on Real Traffic Counting Data
    Pigne, Yoann
    Danoy, Gregoire
    Bouvry, Pascal
    COMMUNICATION TECHNOLOGIES FOR VEHICLES, 2011, 6596 : 131 - +
  • [8] Automatic incident detection algorithm based on under-sampling for imbalanced traffic data
    Li, Miao-hua
    Chen, Shu-yan
    Lao, Ye-chun
    GREEN BUILDING, ENVIRONMENT, ENERGY AND CIVIL ENGINEERING, 2017, : 145 - 150
  • [9] Study on the Traffic Congestion Control Based on Big Data Rule Collecting
    Gao, Bo
    2018 4TH INTERNATIONAL CONFERENCE ON EDUCATION, MANAGEMENT AND INFORMATION TECHNOLOGY (ICEMIT 2018), 2018, : 133 - 136
  • [10] A Prediction Method for City Traffic Noise Based on Traffic Simulation under a Mixed Distribution Probability
    Wang, Haibo
    Wu, Zhaolang
    Chen, Jincai
    SUSTAINABILITY, 2024, 16 (16)