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Dec 14, 2023
Lane Change Correction Factor Model for Left-Turn Lane Capacity
Authors: Guangjun Zhang [email protected], Lei Zhang [email protected], Quan Wu [email protected], and Yanqing Chen [email protected]Author Affiliations
Publication: CICTP 2023
ABSTRACT
The study of left-turning traffic flow has been the focus of attention of scholars in China and abroad. The lane changing behavior of vehicles and the force between lanes can seriously affect the traffic order and also bring some safety hazards. First, combining the traffic characteristics of multi-left-turning traffic, a correction coefficient for the left-turn lane change rate is introduced through a comparative analysis of the saturation flow rate of multiple left-turn lanes. A binary logistic probability model is applied to verify the rationality of the proposed correction coefficient. Second, selected factors such as traffic flow rate during green light time, composition occupancy rate of large vehicles, and downstream interweaving section type are used to model the lane change rate of left-turn vehicles by multiple linear regression. Finally, VISSIM is applied to obtain and calibrate the data, so as to construct the intersection left-turn-only lane capacity calculation model. The validation indicates that the measured capacity of the model is basically consistent with the actual capacity, with an average error of 5.6%, which better reflects the actual condition of left-turn traffic at the intersection.
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Published online: Dec 14, 2023
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1Beijing Key Laboratory of Traffic Engineering, Dept. of Urban Construction, Beijing Univ. of Technology, Chaoyang District, Beijing, China. Email: [email protected]
2Beijing Key Laboratory of Traffic Engineering, Dept. of Urban Construction, Beijing Univ. of Technology, Chaoyang District, Beijing, China. Email: [email protected]
3Faculty of Transportation Engineering, Kunming Univ. of Science and Technology, Chenggong District, Kunming, China. Email: [email protected]
4Beijing Key Laboratory of Traffic Engineering, Dept. of Urban Construction, Beijing Univ. of Technology, Chaoyang District, Beijing, China. Email: [email protected]
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