Volume 39 Issue 2
Apr.  2021
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Article Navigation >  Journal of Transport Information and Safety  > 2021  >  39(2): 137-144
YE Xiuxiu, MA Xiaofeng, ZHONG Ming, HUANG Chuanming. A Method of Traffic Flow Prediction for Road Segments without Detectors Based on Spatial Structure of Local Network[J]. Journal of Transport Information and Safety, 2021, 39(2): 137-144. doi: 10.3963/j.jssn.1674-4861.2021.02.017
Citation: YE Xiuxiu, MA Xiaofeng, ZHONG Ming, HUANG Chuanming. A Method of Traffic Flow Prediction for Road Segments without Detectors Based on Spatial Structure of Local Network[J]. Journal of Transport Information and Safety, 2021, 39(2): 137-144. doi: 10.3963/j.jssn.1674-4861.2021.02.017
shu

A Method of Traffic Flow Prediction for Road Segments without Detectors Based on Spatial Structure of Local Network

doi: 10.3963/j.jssn.1674-4861.2021.02.017
  • 1.

    Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, China

  • 2.

    National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan 430063, China

  • 3.

    Traffic Management Bureau of Wuhan Public Security Bureau, Wuhan 430030, China

  • Received Date: 2020-10-31
    Abstract
  • Most links in an urban road network are not monitored by any traffic detector. Lack of traffic flow data has seriously hindered the performance of traffic management programs. In this regard, this paper proposes a traffic flow prediction method for road segments without a detector(RSWD)based on the spatial structure of the local road network. The correlation between the spatial structure of the local network and the traffic flow of the links is analyzed based on the big data of traffic flow. According to the topology of the local road network, multiple linear regression is used to estimate traffic flow assignment weights using data from links with detectors, and to analyze the impacts of the spatial structure of the local road network on traffic flow assignment weights. Then, a method for estimating the traffic flow of road segments without any detector is proposed by considering the spatial structure of the local network and traffic flow of adjacent links. The results show that a significant correlation is found among links of traffic flow and its functional class, and the number and functional class of its adjacent links. The average error of traffic flow prediction based on the proposed model is about 8% and 22% for the RSWD connected with one and several adjacent upstream links in the local road network, respectively.

     

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