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PU Yun, HU Lu, JIANG Yang-sheng, ZHU Juan-xiu, PENG Bo. Variable speed-limit control before expressway mainline toll station[J]. Journal of Traffic and Transportation Engineering, 2012, 12(5): 119-126. doi: 10.19818/j.cnki.1671-1637.2012.05.016
Citation: PU Yun, HU Lu, JIANG Yang-sheng, ZHU Juan-xiu, PENG Bo. Variable speed-limit control before expressway mainline toll station[J]. Journal of Traffic and Transportation Engineering, 2012, 12(5): 119-126. doi: 10.19818/j.cnki.1671-1637.2012.05.016
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Variable speed-limit control before expressway mainline toll station

doi: 10.19818/j.cnki.1671-1637.2012.05.016
  • 1.

    School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, Sichuan, China

  • 2.

    Comprehensive Transportation Key Laboratory of Sichuan Province, Southwest Jiaotong University, Chengdu 610031, Sichuan, China

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  • Author Bio:

    PU Yun(1962-), male, professor, PhD, +86-28-87601715, ypu@swjtu.edu.cn

  • Received Date: 2012-05-08
    Abstract
  • An optimization model of variable speed-limit control with the object of the least accident rate and the limitations of cost and speed was set up, in which the number of variable message signs and corresponding variable limit speeds were determined. The distances between variable message signs were computed by using the traffic wave model, and the optimization model was verified by using the simulation software Vissim. For different traffic flows, variable speed-limit control and static speed-limit control were simulated on the expressway with two-lanes and six toll windows in single direction. Analysis result shows that when 4 variable message signs with setting separation distances of 1 293, 2 695 and 4 056 m apart are installed before the queuing square of expressway mainline toll station, the minimum relative error between simulation result and calculated values of traffic wave model is 3.9%, and the maximum is 9.5%. Compared with static speed-limit control, passing vehicle number in variable speed-limit control rises by 51.82%, average travel time and queue length decrease by 15.81% and 18.98% respectively, which proves that the model is reasonable.

     

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