Fast L2 Calibration for Inexact Highway Traffic Flow Systems

Abstract

Transportation systems need more accurate predictions to further optimize traffic network design with the development and application of autonomous driving technology. In this article, we focus on highway traffic flow systems that are often simulated by the modified Greenshields model. However, this model can not perfectly match the true traffic flow due to its underlying simplifications and assumptions, implying that it is inexact. Specifically, some parameters affect the simulation accuracy of the modified Greenshields model, while tuning these parameters to improve the model’s accuracy is called model calibration. The parameters obtained using the L2 calibration have the advantages of high accuracy and small variance for an inexact model. However, the method is calculation intensive, requiring optimization of the integral loss function. Since traffic flow data are often massive, this paper proposes a fast L2 calibration framework to calibrate the modified Greenshields model. Specifically, the suggested method selects a sub-design containing more information on the calibration parameters, and then the empirical loss function obtained from the optimal sub-design is utilized to approximate the integral loss function. A case study highlights that the proposed method preserves the advantages of L2 calibration and significantly reduces the running time.

Efficient simulation-based method for calibrating the fundamental diagram of operational performance decaying transportation network

“…Wang [3] et al reviewed the research progress in the field of fundamental diagram calibration, and used the proposed basic framework of parameter calibration and METANET to calibrate the real highway data in Shanghai area. Huang [4] fastened and improved the L2 calibration method, so that it can handle a large amount of traffic information without affecting the computational efficiency, and at the same time, ensured the accuracy of calibration. Zhong [5] et al proposed an automatic calibration method for estimating MCTM fundamental diagram parameters through a dynamic quadratic nonlinear model, which enables it to maintain accuracy under circulating and abnormal traffic conditions.…”

Improving the Maritime Traffic Evaluation with the Course and Speed Model

“…These models can elucidate traffic flow characteristics, such as delay, congestion, and bottlenecks. While typically employed in road traffic facilities, various single-mode models have been studied, with Greenshields (linear model) [19], Greenberg (algebraic model), and Underwood (exponential model) [20] being representative examples. A recent study assumed that excessive speed was the cause of accidents in road traffic and compared the deviation of driving speed by vehicle type to the speed limit [21].…”