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Modified Volume-Delay Function Based on Traffic Fundamental Diagram: A Practical Calibration Framework for Estimating Congested and Uncongested Conditions
| 题名： | Modified Volume-Delay Function Based on Traffic Fundamental Diagram: A Practical Calibration Framework for Estimating Congested and Uncongested Conditions |
| 正文语种： | eng |
| 作者： | Yuyan 'Annie' Pan;Han Zheng;Jifu Guo;Yanyan Chen |
| 作者单位： | Beijing Key Laboratory of Traffic Engineering Beijing Univ. of Technology Beijing 100124 China;School of Traffic and Transportation Beijing Jiaotong Univ. Beijing 100044 China;Beijing Key Laboratory of Urban Transportation Operation Simulation and Decision Support Beijing Transport Institute Beijing 100000 China;Beijing Key Laboratory of Traffic Engineering Beijing Univ. of Technology Beijing 100124 China |
| 关键词： | Bureau of public roads (BPR) function; Volume/capacity (VIC) ratio; Volume-delay functions (VDFs); Traffic congestion; Fundamental diagram |
| 摘要： | Traffic congestion occurs when there is a mismatch between the demand for road use and the available capacity. The volume-delay function (VDF) can quantify the relationship between travel time and the volume of traffic on a particular link, and also provide insight into the state of a traffic system, such as whether it is congested or uncongested. In this paper, we present a VDF model that is based on the fundamental diagram and has two main components: (1) an improved VDF with fewer parameters that can handle both congested and uncongested traffic conditions, based on a fundamental diagram, and (2) a model-based VDF practical calibration framework for practical traffic applications that can determine key parameters for a link in a corridor. Our experiments using corridors in Los Angeles and Beijing demonstrate that our proposed analytical methods effectively calculate road impedance under congested conditions. The results indicate that the proposed model is superior to other existing models in terms of the root mean squared error (RMSE) and mean absolute error (MAE). In addition, our calibrated results indicate that the travel time index (TTI) in Los Angeles is 2.12, in Beijing is 1.74. The model proposed in this paper provides a useful calibration tool for enhancing model performance and improving the accuracy of travel time and speed estimates in traffic assignment. |
| 出版年： | 2023 |
| 期刊名称： | Journal of Transportation Engineering |
| 卷： | 149 |
| 期： | 11 |
| 页码： | 04023112.1-04023112.14 |
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