Calibration and Validation of Microscopic Traffic Simulation Tools: Stockholm Case Study

Author:

Toledo Tomer1,Koutsopoulos Haris N.2,Davol Angus3,Ben-Akiva Moshe E.4,Burghout Wilco5,Andréasson Ingmar5,Johansson Tobias6,Lundin Christen6

Affiliation:

1. Center for Transportation and Logistics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, NE20-208, Cambridge, MA 02139

2. Department of Civil and Environmental Engineering, Northeastern University, 437 Snell Engineering Center, Boston, MA 02115

3. IBI Group, 3 Copley Place, 3rd Floor, Boston, MA 02116

4. Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, 1-181, Cambridge, MA 02139

5. Centre for Traffic Simulation, Royal Institute of Technology, TeknikRingen 72 BV, 100 44 Stockholm, Sweden

6. Traffic Department, Gatu-och Fastighetskontoret, Box 8311 104 20 Stockholm, Sweden

Abstract

The calibration and validation approach and results from a case study applying the microscopic traffic simulation tool MITSIMLab to a mixed urban-freeway network in the Brunnsviken area in the north of Stockholm, Sweden, under congested traffic conditions are described. Two important components of the simulator were calibrated: driving behavior models and travel behavior components, including origin–destination flows and the route choice model. In the absence of detailed data, only aggregate data (i.e., speed and flow measurements at sensor locations) were available for calibration. Aggregate calibration uses simulation output, which is a result of the interaction among all components of the simulator. Therefore, it is, in general, impossible to identify the effect of individual models on traffic flow when using aggregate data. The calibration approach used takes these interactions into account by iteratively calibrating the different components to minimize the deviation between observed and simulated measurements. The calibrated MITSIMLab model was validated by comparing observed and simulated measurements: traffic flows at sensor locations, point-to-point travel times, and queue lengths. A second set of measurements, taken a year after the ones used for calibration, was used at this stage. Results of the validation are presented. Practical difficulties and limitations that may arise with application of the calibration and validation approach are discussed.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

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