Freight origin-destination (OD) information is increasingly important for understanding the influence of transportation on network congestion. Traditional OD estimation methods based on a single data source, usually loop detectors, are not easily transferred to freight OD estimation. However, alternative data capture technologies are nowadays available to gather traffic information. Examples are automatic number plate recognition (ANPR), Bluetooth scanners, and Weigh-in-Motion systems. This paper aims to develop feasible approaches based on Entropy Maximization and Bayesian Networks to estimate freight OD matrix using multiple sources of captured data. In the case of the A15 motorway in the Netherlands, we illustrate how the captured data is informative about transport behavior in the area and how the proposed methods lead to an estimation of the freight OD matrix.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Freight origin-destination estimation based on multiple data source


    Contributors:
    Ma, Yinyi (author) / van Zuylen, Henk (author) / Kuik, Roelof (author)


    Publication date :

    2012-09-01


    Size :

    375894 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Port Throughput Forecasting Based on Origin-Destination Freight Volume

    Zhong, Liangxia / Wen, Yiqing / Wu, Jiaxin et al. | Springer Verlag | 2024



    Multiclass Probit-Based Origin–Destination Estimation Using Multiple Data Types

    Zhao, Qing / Turnquist, Mark A. / Dong, Zhijie et al. | ASCE | 2018

    Free access

    Estimation of an Origin–Destination Table for U.S. Imports of Waterborne Containerized Freight

    Wang, Hao / Gearhart, Jared / Jones, Katherine et al. | Transportation Research Record | 2016