Calibration of microsimulation models using nonparametric statistical techniques

Seung Jun Kim, Wonho Kim, Laurence R Rilett

Research output: Contribution to journalArticle

38 Citations (Scopus)

Abstract

The calibration of traffic microsimulation models has received widespread attention in transportation modeling. A recent concern is whether these models can simulate traffic conditions realistically. The recent widespread deployment of intelligent transportation systems in North America has provided an opportunity to obtain traffic-related data. In some cases the distribution of the traffic data rather than simple measures of central tendency such as the mean, is available. This paper examines a method for calibrating traffic microsimulation models so that simulation results, such as travel time, represent observed distributions obtained from the field. The approach Is based on developing a statistically based objective function for use in an automated calibration procedure. The Wilcoxon rank-sum test, the Moses test and the Kolmogorov-Smirnov test are used to test the hypothesis that the travel time distribution of the simulated and the observed travel tunes are statistically identical. The approach is tested on a signalized arterial roadway in Houston, Texas. It is shown that potentially many different parameter sets result in statistically valid simulation results. More important, it is shown that using simple metrics, such as the mean absolute error, may lead to erroneous calibration results.

Original languageEnglish (US)
Pages (from-to)111-119
Number of pages9
JournalTransportation Research Record
Issue number1935
DOIs
StatePublished - Jan 1 2005

Fingerprint

Calibration
Travel time

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Mechanical Engineering

Cite this

Calibration of microsimulation models using nonparametric statistical techniques. / Kim, Seung Jun; Kim, Wonho; Rilett, Laurence R.

In: Transportation Research Record, No. 1935, 01.01.2005, p. 111-119.

Research output: Contribution to journalArticle

@article{08d70843c431411a80c47b3d6c7d2721,
title = "Calibration of microsimulation models using nonparametric statistical techniques",
abstract = "The calibration of traffic microsimulation models has received widespread attention in transportation modeling. A recent concern is whether these models can simulate traffic conditions realistically. The recent widespread deployment of intelligent transportation systems in North America has provided an opportunity to obtain traffic-related data. In some cases the distribution of the traffic data rather than simple measures of central tendency such as the mean, is available. This paper examines a method for calibrating traffic microsimulation models so that simulation results, such as travel time, represent observed distributions obtained from the field. The approach Is based on developing a statistically based objective function for use in an automated calibration procedure. The Wilcoxon rank-sum test, the Moses test and the Kolmogorov-Smirnov test are used to test the hypothesis that the travel time distribution of the simulated and the observed travel tunes are statistically identical. The approach is tested on a signalized arterial roadway in Houston, Texas. It is shown that potentially many different parameter sets result in statistically valid simulation results. More important, it is shown that using simple metrics, such as the mean absolute error, may lead to erroneous calibration results.",
author = "Kim, {Seung Jun} and Wonho Kim and Rilett, {Laurence R}",
year = "2005",
month = "1",
day = "1",
doi = "10.3141/1935-13",
language = "English (US)",
pages = "111--119",
journal = "Transportation Research Record",
issn = "0361-1981",
publisher = "US National Research Council",
number = "1935",

}

TY - JOUR

T1 - Calibration of microsimulation models using nonparametric statistical techniques

AU - Kim, Seung Jun

AU - Kim, Wonho

AU - Rilett, Laurence R

PY - 2005/1/1

Y1 - 2005/1/1

N2 - The calibration of traffic microsimulation models has received widespread attention in transportation modeling. A recent concern is whether these models can simulate traffic conditions realistically. The recent widespread deployment of intelligent transportation systems in North America has provided an opportunity to obtain traffic-related data. In some cases the distribution of the traffic data rather than simple measures of central tendency such as the mean, is available. This paper examines a method for calibrating traffic microsimulation models so that simulation results, such as travel time, represent observed distributions obtained from the field. The approach Is based on developing a statistically based objective function for use in an automated calibration procedure. The Wilcoxon rank-sum test, the Moses test and the Kolmogorov-Smirnov test are used to test the hypothesis that the travel time distribution of the simulated and the observed travel tunes are statistically identical. The approach is tested on a signalized arterial roadway in Houston, Texas. It is shown that potentially many different parameter sets result in statistically valid simulation results. More important, it is shown that using simple metrics, such as the mean absolute error, may lead to erroneous calibration results.

AB - The calibration of traffic microsimulation models has received widespread attention in transportation modeling. A recent concern is whether these models can simulate traffic conditions realistically. The recent widespread deployment of intelligent transportation systems in North America has provided an opportunity to obtain traffic-related data. In some cases the distribution of the traffic data rather than simple measures of central tendency such as the mean, is available. This paper examines a method for calibrating traffic microsimulation models so that simulation results, such as travel time, represent observed distributions obtained from the field. The approach Is based on developing a statistically based objective function for use in an automated calibration procedure. The Wilcoxon rank-sum test, the Moses test and the Kolmogorov-Smirnov test are used to test the hypothesis that the travel time distribution of the simulated and the observed travel tunes are statistically identical. The approach is tested on a signalized arterial roadway in Houston, Texas. It is shown that potentially many different parameter sets result in statistically valid simulation results. More important, it is shown that using simple metrics, such as the mean absolute error, may lead to erroneous calibration results.

UR - http://www.scopus.com/inward/record.url?scp=33646402063&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33646402063&partnerID=8YFLogxK

U2 - 10.3141/1935-13

DO - 10.3141/1935-13

M3 - Article

SP - 111

EP - 119

JO - Transportation Research Record

JF - Transportation Research Record

SN - 0361-1981

IS - 1935

ER -