首页|Practical approach to determining traffic congestion propagation boundary due to traffic incidents

Practical approach to determining traffic congestion propagation boundary due to traffic incidents

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A practical approach for predicting the congestion boundary due to traffic incidents was proposed. Based on the kinematic wave theory and Van Aerde single-regime flow model, a model for estimating the congestion propagation speed for the basic road segment was developed. Historical traffic flow data were used to analyze the time variant characteristics of the urban traffic flow for each road type. Then, the saturation flow rate was used for analyzing the impact of the traffic incident on the traversing traffic flow at the congestion area. The base congestion propagation speed for each road type was calculated based on field data, which were provided by the remote traffic microwave sensors (RTMS), floating car data (FCD) system and screen line survey. According to a comparative analysis of the congestion propagation speed, it is found that the expressway, major arterial, minor arterial and collector are decreasingly influenced by the traffic incident. Subsequently, the impact of turning movements at intersections on the congestion propagation was considered. The turning ratio was adopted to represent the impact of turning movements, and afterward the corresponding propagation pattern at intersections was analyzed. Finally, an implementation system was designed on a geographic information system (GIS) platform to display the characteristics of the congestion propagation over the network. The validation results show that the proposed approach is able to capture the congestion propagation properties in the actual road network.

kinematic wave modelVan Aerde modeltraffic incidentcongestion propagation on network

FEI Wen-peng、SONG Guo-hua、ZHANG Fan、GAO Yong、YU Lei

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School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China

China Communications News, Beijing 100011, China

Beijing Transportation Research Center, Beijing 100073, China

College of Science, Engineering and Technology, Texas Southern University, Houston, Texas 77004, USA

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Project supported by the National Basic Research Program of ChinaProjects supported by the National Natural Science Foundation of ChinaProjects supported by the National Natural Science Foundation of ChinaProject supported by the Fundamental Research Funds for the Central Universities, China

2012CB72540351678045515780522016JBM032

2017

10.1007/s11171-017-3443-2

中南大学学报(英文版)
中南大学

中南大学学报(英文版)

CSCDSCIEI
影响因子：0.47
ISSN：2095-2899
年,卷(期)：2017.24(2)
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