Analysis of Factors Affecting the Accuracy of MFD Construction in Multisource Complex Data Scenarios

Author:

Hong Rongrong12ORCID

Affiliation:

1. School of Traffic and Transportation Engineering, Xinjiang University, Hua Rui Street #777, Urumqi 830017, China

2. Xinjiang Key Laboratory of Green Construction and Smart Traffic Control of Transportation Infrastructure, Xinjiang University, Hua Rui Street #777, Urumqi 830017, China

Abstract

The macroscopic fundamental diagram (MFD), as a model depicting the correlation between traffic flow parameters at the network level, offers a new way to understand regional traffic state using derived traffic flow data from detectors directly. The accuracy of MFD construction is directly related to factors such as the type of detectors, their distribution, and their quantity within the road network. Understanding these influencing factors and mechanisms is crucial for enhancing the reliability of MFD-based applications such as congestion pricing and threshold control. Present investigations on factors that affect MFD construction’s accuracy have frequently been confined to sensitivity analysis of single-source data and individual influencing factors such as the penetration rate. However, the accuracy of MFD is influenced by a multitude of factors, including the spatial distribution equilibrium, penetration rate, and coverage rate of traffic flow detection equipment. Despite this, this paper utilized the Q-paramics simulation software V6.8.1 to acquire simulated data and employed the orthogonal experimental method from statistics to explore the impact mechanisms of factors on the accuracy of MFD construction. The results of the case study demonstrated that when the penetration rate reaches 20%, the error remains approximately around 10%; once the coverage rate surpasses 45%, the errors stabilize at around 10%. This study provides practical guidance for traffic management and planning decisions aimed at promoting sustainable development through the application of MFD in real-world road networks.

Funder

Natural Science Foundation of Xinjiang Uygur Autonomous Region

Tianchi Talent Recruitment Plan of Xinjiang Uygur Autonomous Region

Publisher

MDPI AG

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