原文传递
Real-time queue length estimation using event-based advance detector data
| 题名： | Real-time queue length estimation using event-based advance detector data |
| 正文语种： | 英文 |
| 作者： | Chengchuan An; Yao-Jan Wu; Jingxin Xia; Wei Huang |
| 作者单位： | Intelligent Transportation System Research Center, Southeast University, Nanjing, P.R. China; Department of Civil Engineering and Engineering Mechanics, University of Arizona, Tucson, AZ, USA |
| 关键词： | High-resolution event-based data; input-output model; real-time queue length estimation; shock wave model |
| 摘要： | Real-time queue length information at signalized intersections is useful for both performance evaluation and signal optimization. Previous studies have successfully examined the use of high-resolution event-based data to estimate real-time queue lengths. Based on the identification of critical breakpoints, real-time queue lengths can be estimated by applying the commonly used shockwave model. Although breakpoints can be accurately identified using lane-by-lane detection, few studies have investigated queue length estimation using single-channel detection, which is a common detection scheme for actuated signal control. In this study, a breakpoint misidentification checking process and two input-output models (upstream-based and local-based) are proposed to address the overestimation and short queue length estimation problems of breakpoint-based models. These procedures are integrated with a typical breakpoint-based model framework and queue-over-detector identification process. The proposed framework was evaluated using field-collected event-based data along Speedway Boulevard in Tucson, Arizona. Significant improvements in maximum queue length estimates were achieved using the proposed method compared to the breakpoint-based model, with mean absolute errors of 35.7 and 105.6 ft., respectively. |
| 出版年： | 2018 |
| 期刊名称： | Journal of Intelligent Transportation Systems Technology Planning and Operations |
| 卷： | 22 |
| 期： | 4 |
| 页码： | 277-290 |
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