中山大学学报自然科学版 ›› 2019, Vol. 58 ›› Issue (2): 37-44.doi: 10.13471/j.cnki.acta.snus.2019.02.006

• 论文 • 上一篇    下一篇

基于过车速度分布的中观仿真模型参数校准

杨昀霖1,2,何兆成1,2,王亦民1,2   

  1. 1.中山大学智能交通研究中心,广东 广州 510275;
    2.广东省智能交通系统(ITS)重点实验室,广东 广州 510275
  • 收稿日期:2018-09-10 出版日期:2019-03-25 发布日期:2019-03-25
  • 通讯作者: 何兆成(1977年生),男;研究方向:交通流建模与系统仿真;E-mail:hezhch@mail.sysu.edu.cn

Calibration of mesoscopic traffic flow model based on distributions of single-vehicle speed

YANG Yunlin1,2,HE Zhaocheng1,2,WANG Yimin1,2   

  1. 1. School of Engineering, Sun Yat-sen University, Guangzhou 510275, China;
    2. Guangdong Provincial Key Laboratory of Intelligent Transportation System, Guangzhou 510275, China
  • Received:2018-09-10 Online:2019-03-25 Published:2019-03-25

摘要:

通过微观仿真模型,可基于均值残差的拟合优度指标来校准模型参数,但因模型结构和数据粒度不匹配,且校准指标缺乏对个体信息的考虑,容易误导优化算法陷入到不合理的“最优局部”的问题,以结构更简洁的中观仿真模型作为研究对象,提出了基于过车速度分布的拟合优度指标。然后,利用广州市内环路的实测数据,对模型的参数进行了优化求解,并与基于传统指标的校准方法进行了对比。结果表明:新指标在校准效果、参数合理性以及优化算法收敛效率方面明显占优,具有可行性和推广应用的潜力。

关键词: 中观交通仿真, 参数校准, 过车速度分布, K-S统计量

Abstract:

Parameters of microscopic traffic simulation model could be calibrated using the mean error as goodness of fit. However, due to the unmatched specification of model with the granularity of data and lack of regard for the individual information, optimization algorithm might be misled to find unreasonable solutions. To deal with such issue, mesoscopic model was chosen for its simpler specification and the goodness of fit function based on the distribution of singlevehicle speed is proposed in this paper. Then, a case study was employed for calibration of simulation model by using the network of inner ring road, Guangzhou. Moreover, a traditional calibration method was used for comparison and analysis. Results show that the new measure of goodness of fit outperform the traditional one in terms of the calibration effect, parameters rationality and optimization efficiency, which reveal that the proposed method has the potential to be feasible and popularized.

Key words: mesoscopic traffic flow model, parameter calibration, single-vehicle speed distribution, K-S statistics

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