[1] Wang Chaonan, Li Wenquan, Tong Xiaolong, Chen Chen, et al. An automatic identification algorithm for freeway bottleneckbased on loop detector data [J]. Journal of Southeast University (English Edition), 2014, 30 (4): 495-499. [doi:10.3969/j.issn.1003-7985.2014.04.016]
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An automatic identification algorithm for freeway bottleneckbased on loop detector data(
)
基于线圈数据的瓶颈点自动识别算法
)Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]
- Volumn:
- 30
- Issue:
- 2014 4
- Page:
- 495-499
- Research Field:
- Traffic and Transportation Engineering
- Publishing date:
- 2014-12-31
Info
- Title:
- An automatic identification algorithm for freeway bottleneckbased on loop detector data
- 基于线圈数据的瓶颈点自动识别算法
- Author(s):
- Wang Chaonan; Li Wenquan; Tong Xiaolong; Chen Chen
- School of Transportation, Southeast University, Nanjing 210096, China
- Keywords:
- bottleneck; loop detector data; occupancy rate; flow rate
- PACS:
- U491.2
- DOI:
- 10.3969/j.issn.1003-7985.2014.04.016
- Abstract:
- A bottleneck automatic identification algorithm based on loop detector data is proposed. The proposed algorithm selects the critical flow rate as the trigger variable of the algorithm, which is calculated by the road conditions, the level of service and the proportion of trucks. The process of identification includes two parts. One is to identify the upstream of the bottleneck by comparing the distance between the current occupancy rate and the mean value of the occupancy rate and the variance of the occupancy rate. The other process is to identify the downstream of the bottleneck by calculating the difference of the upstream occupancy rate with that of the downstream. In addition, the algorithm evaluation standards, which are based on the time interval of the data, the detection rate and the false alarm rate, are discussed. The proposed algorithm is applied to detect the bottleneck locations in the Shanghai Inner Ring Viaduct Dabaishu-Guangzhong road section. The proposed method has a good performance in improving the accuracy and efficiency of bottleneck identification.
- 提出了一种基于线圈数据的瓶颈点自动识别算法.算法以临界流量作为算法的触发变量, 根据道路条件、服务水平和大型车比例计算临界流量.算法的识别程序包括2部分:首先通过计算当前占有率与前时刻占有率的相对差值来判定瓶颈点上游位置;然后通过计算上游占有率与下游占有率的相对差值确定瓶颈点下游的位置.此外, 提出了基于数据集计周期、瓶颈点识别率和误判率的算法性能评价方法.利用上海市内环高架大柏树-广中路段的线圈数据进行试验, 结果表明, 瓶颈点自动识别算法在准确率和效率上有显著提高.
References:
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Memo
- Memo:
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Biographies: Wang Chaonan(1990—), female, graduate; Li Wenquan(corresponding author), male, doctor, professor, wenqli@seu.edu.cn.
Citation: Wang Chaonan, Li Wenquan, Tong Xiaolong, et al. An automatic identification algorithm for freeway bottleneck based on loop detector data[J].Journal of Southeast University(English Edition), 2014, 30(4):495-499.[doi:10.3969/j.issn.1003-7985.2014.04.016]