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Cycle-Based Estimation on Lane-Level Queue Length at Isolated Signalized Intersection Using License Plate Recognition Data
| 题名： | Cycle-Based Estimation on Lane-Level Queue Length at Isolated Signalized Intersection Using License Plate Recognition Data |
| 正文语种： | eng |
| 作者： | Qun Chen;Min Li;Chengcheng Wang;Xinyuan Liu;Jinjun Tang |
| 作者单位： | Smart Transport Key Laboratory of Hunan Province School of Traffic and Transportation Engineering Central South Univ. Changsha 410075 China;Smart Transport Key Laboratory of Hunan Province School of Traffic and Transportation Engineering Central South Univ. Changsha 410075 China;Shandong Provincial Communications Planning and Design Institute Group Co. Ltd. No. 2177 Tianchen Rd. Jinan 250101 China;Smart Transport Key Laboratory of Hunan Province School of Traffic and Transportation Engineering Central South Univ. Changsha 410075 China;Smart Transport Key Laboratory of Hunan Province School of Traffic and Transportation Engineering Central South Univ. Changsha 410075 China |
| 关键词： | License plate recognition (LPR) data; Queue length estimation; Signalized intersection; Oversaturated condition; Maximum probability |
| 摘要： | Queue length is an important parameter to evaluate the congestion level of urban intersections. Abundant methods based on different data sources, such as loop detector data and mobile sensor data, for estimating queue length have received wide attention. A license plate recognition (LPR) system recording vehicle information can be used as a data source to estimate lane-level queue length. In this study, an improved method is proposed for cycle-based queue length estimation at an isolated signalized intersection using LPR data, considering the residual queued vehicles under oversaturated conditions. First, a modified interpolation method is developed to infer the travel time of unmatched vehicles. Then, the complete arrival and departure information are processed as three characteristic parameters of vehicles, which are the input to the maximum probability function for queue length estimation at each lane. Finally, the proposed model is validated using actual cycle maximum queue length collected from a video camera and LPR data in Changsha city, China. The numerical results showed that the proposed model can achieve accurate estimation for lane-level queue length. |
| 出版年： | 2023 |
| 期刊名称： | Journal of Transportation Engineering |
| 卷： | 149 |
| 期： | 1 |
| 页码： | 04022123.1-04022123.12 |
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