Volume 23 Issue 2
Apr.  2023
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HUANG Wei, HU Yang. Cell transmission model considering queuing characteristics of channelized zone at intersections[J]. Journal of Traffic and Transportation Engineering, 2023, 23(2): 212-224. doi: 10.19818/j.cnki.1671-1637.2023.02.015
Citation: HUANG Wei, HU Yang. Cell transmission model considering queuing characteristics of channelized zone at intersections[J]. Journal of Traffic and Transportation Engineering, 2023, 23(2): 212-224. doi: 10.19818/j.cnki.1671-1637.2023.02.015
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Cell transmission model considering queuing characteristics of channelized zone at intersections

doi: 10.19818/j.cnki.1671-1637.2023.02.015

  • School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou 510006, Guangdong, China

Funds:

National Natural Science Foundation of China 52102401

Guangdong Basic and Applied Basic Research Foundation 2019A1515111083

More Information
  • Author Bio:

    HUANG Wei(1986-), female, associate professor, PhD, huangwei5@mail.sysu.edu.cn

  • Received Date: 2022-10-05
    Available Online: 2023-05-09
  • Publish Date: 2023-04-25
    Abstract
  • In order to describe the evolution law of traffic flows at urban intersections more accurately, the signalized intersection with entrance widening areas and shared lanes was taken as the research object, and the cell transmission model (CTM) was improved by considering four practical factors: queue discharge process, divergence process, optional lane changing, and shared lanes. According to the geometric characteristics of the intersection, a method to divide cells at road sections was proposed based on lane groups. On this basis, the cell sending capacity function was adjusted to reflect and model the queue discharge process. The blocking factors were introduced in the divergence process modeling to describe the interaction of spatial queuing among different lane groups. The optional lane changing behavior in the transition zone was modeled with the goal of balancing the spatial queuing of adjacent lane groups, and the conflict effect of traffic flows with different directions was considered in the modeling of shared lanes. On the basis of an actual intersection, the maximum queue length of the lane group cycle was selected as the evaluation index to verify the effectiveness of the improved CTM. Test results show that the improved CTM can simultaneously estimate the queue lengths of different lane groups. With the increase in the proportion of through traffic flows, the estimation error of the improved CTM decreases. The mean absolute error (MAE), root mean square error (RMSE), and weighted mean absolute percentage error (WMAPE) of the maximum queue length at road sections are less than 16.43, 21.36 m, and 13.51%, respectively, under different traffic scenarios. Compared with the benchmark method, the improved CTM can reduce the MAE by 15.31%-90.03% for the maximum queue length at road sections under different scenarios, and the estimation accuracy under high-traffic scenarios improves more obviously. Thus, it can be seen that the improved CTM can more accurately describe the operational characteristics of traffic flow at intersections and improve the estimation accuracy of queue length, which can be used as an important basis for the traffic management and control.

     

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