An Analysis of the Interactions between Adjustment Factors of Saturation Flow Rates at Signalized Intersections

Yi Wang, Jian Rong, Chenjing Zhou, Xin Chang and Siyang Liu
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Yi Wang: Beijing Key Laboratory of Traffic Engineering, Beijing Engineering Research Center of Urban Transport Operation Guarantee, Beijing University of Technology, Beijing 100124, China
Jian Rong: Beijing Key Laboratory of Traffic Engineering, Beijing Engineering Research Center of Urban Transport Operation Guarantee, Beijing University of Technology, Beijing 100124, China
Chenjing Zhou: School of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
Xin Chang: Beijing Key Laboratory of Traffic Engineering, Beijing Engineering Research Center of Urban Transport Operation Guarantee, Beijing University of Technology, Beijing 100124, China
Siyang Liu: Beijing Key Laboratory of Traffic Engineering, Beijing Engineering Research Center of Urban Transport Operation Guarantee, Beijing University of Technology, Beijing 100124, China

Sustainability, 2020, vol. 12, issue 2, 1-18

Abstract: An insufficient functional relationship between adjustment factors and saturation flow rate (SFR) in the U.S. Highway Capacity Manual (HCM) method increases an additional prediction bias. The error of SFR predictions can reach 8–10%. To solve this problem, this paper proposes a comprehensive adjusted method that considers the effects of interactions between factors. Based on the data from 35 through lanes in Beijing and 25 shared through and left-turn lanes in Washington, DC, the interactions between lane width and percentage of heavy vehicles and proportion of left-turning vehicles were analyzed. Two comprehensive adjustment factor models were established and tested. The mean absolute percentage error (MAPE) of model 1 (considering the interaction between lane width and percentage of heavy vehicles) was 4.89% smaller than the MAPE of Chinese National Standard method (Standard Number is GB50647) at 13.64%. The MAPE of model 2 (considering the interaction between lane width and proportion of left-turning vehicles was 33.16% smaller than the MAPE of HCM method at 14.56%. This method could improve the accuracy of SFR prediction, provide support for traffic operation measures, alleviate the traffic congestion, and improve sustainable development of cities.

Keywords: signalized intersections; adjustment factors; percentage of heavy vehicles; lane width; proportion of left-turning vehicles; interactions (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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