Holistic Calibration of Microscopic Traffic Flow Models: Methodology and Real World Application Studies

Abstract

This study proposes and applies a methodology to calibrate microscopic traffic flow simulation models. The proposed methodology has the capability to calibrate simultaneously all the calibration parameters as well as demand patterns for any type of network. Parameters considered include global and local as well as driver behaviour and vehicle performance parameters. Demand patterns, in terms of turning volumes, are included in the calibration framework. Multiple performance measures involving link counts and speeds are used to formulate and solve the proposed calibration problem. In addition, multiple time periods were considered. A Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm is used to search for the vector of the model's parameters that minimizes the difference between actual and simulated network states. The third network was an arterial network, with time-dependent link counts and speed used as performance measurements. The experimental results illustrate the effectiveness and validity of this proposed methodology. The same set of calibration parameters was used in all experiments.

Simultaneous Generation of Optimum Pavement Clusters and Associated Performance Models

“…These values may not be obvious to determine, but rather might be determined by trial and error for a given problem [40]. In this study, values assigned to the optimization parameters were determined using experience gained from previous research [45][46][47][48][49][50][51] that involved SA and other comparable algorithms. Table 3 lists the parameter values used in this study.…”

A Multi-Objective Approach for the Calibration of Microscopic Traffic Flow Simulation Models

“…The objective functions in this study are provided by (1) and (2); they respectively involve the minimization of the normalize root mean square (NRMS) difference between simulated and actual volumes and speeds. Previous studies [2], [38] have combined these objectives into a single function using weights as illustrated in (3). A single objective function enables the use of mono-objective optimization algorithms as well as to break ties along the Pareto Front.…”

“…A common calibration criterion from the literature was used in this study [2], [8], [22], [38]: the absolute difference between actual and simulated link counts and speeds should be less than 15% for at least 85% of the links. In addition, the GEH [40] is required to be less than 5 for at least 85% of the links.…”

“…The performance of the proposed solution algorithm is compared with the following alternatives which were used recently and successfully to solve the same calibration problem [2], [8], [22], [38]:  Mono-objective algorithms,  Single-state multi-objective algorithms, also used as local search strategies in memetic algorithms, and  Memetic multi-objective algorithms. All algorithms were implemented to take advantage of parallel computing using multi-threading.…”

Simulation Tools

“…There are parameters regarding the drivers, the vehicles, the roads, etc. Therefore, there are literarily hundreds of works on CORSIM calibration methods, using Artificial Intelligence techniques like in Cobos (2016), Statistical Techniques (Paz, 2015), Bayesian methods (Bayarri, 2004), and more.…”