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| Title: | Time-series-based validation methods for microscopic traffic simulation models |
| Author (s): | Kan, Shengnan Bham, Ghulam |
| Department/Lab Affiliations: | Civil, Architectural & Environmental Engineering Intelligent Systems Center University Transportation Center |
| Keywords: | correlation analysis cross correlation measure of effectiveness validation |
| Subject Terms: | Multivariate analysis. Time-series analysis. Traffic flow -- Simulation methods. |
| Issue Date: | 2008 |
| Publisher: | US Department of Transportation Research and Innovative Technology Administration |
| Citation: | Kan, Shengnan., and Bham, Ghulam Hussain. "Time-Series-Based Validation Methods for Microscopic Traffic Simulation Models.", Transportation Research Board 87th Annual Meeting, 2008. |
| Abstract: | This paper proposes two time-series based validation methods, spectral analysis for evaluating univariate measure of effectiveness (MOE) and cross-correlation analysis for multivariate MOE. The spectral analysis quantifies and evaluates the autocorrelation after the data have been transformed into the frequency domain. The cross-correlation analysis can evaluate the stochastic relationship between two MOEs. Validation using the spectral and cross-correlation analysis is performed by constructing simultaneous confidence intervals over spectrums and cross-correlations from the field data and comparing that with the simulated spectrums and cross-correlations. The time-series based validation methods do not require the independent and identical distribution assumption, the common basis for classical statistical methods, and are more suitable for field data and simulation results as they are highly autocorrelated. The validation methods are demonstrated using two sets of field data, NGSIM data for I-80 in Emeryville, CA, and FHWA data for I-95 on Baltimore-Washington Parkway using two popular microscopic simulation models, VISSIM and AIMSUN. |
| Type: | Article - Conference proceedings text |
| In Title: | Transportation Research Board 87th Annual Meeting |
| Copyright Notice: | Pre-print: Can be archived Post-print:Can be archived This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. FULL COPYRIGHT INFORMATION: |
| Publisher URL: | |
| Link to this page: |
| title | Time-series-based validation methods for microscopic traffic simulation models |
| contributor.author | Kan, Shengnan |
| contributor.author | Bham, Ghulam |
| contributor.deptlab | Civil, Architectural & Environmental Engineering |
| contributor.deptlab | Intelligent Systems Center |
| contributor.deptlab | University Transportation Center |
| subject | correlation analysis |
| subject | cross correlation |
| subject | measure of effectiveness |
| subject | validation |
| subject.LCSH | Multivariate analysis. |
| subject.LCSH | Time-series analysis. |
| subject.LCSH | Traffic flow -- Simulation methods. |
| date.issued | 2008 |
| publisher | US Department of Transportation Research and Innovative Technology Administration |
| identifier.citation | Kan, Shengnan., and Bham, Ghulam Hussain. "Time-Series-Based Validation Methods for Microscopic Traffic Simulation Models.", Transportation Research Board 87th Annual Meeting, 2008. |
| identifier.pub.URI | |
| description.abstract | This paper proposes two time-series based validation methods, spectral analysis for evaluating univariate measure of effectiveness (MOE) and cross-correlation analysis for multivariate MOE. The spectral analysis quantifies and evaluates the autocorrelation after the data have been transformed into the frequency domain. The cross-correlation analysis can evaluate the stochastic relationship between two MOEs. Validation using the spectral and cross-correlation analysis is performed by constructing simultaneous confidence intervals over spectrums and cross-correlations from the field data and comparing that with the simulated spectrums and cross-correlations. The time-series based validation methods do not require the independent and identical distribution assumption, the common basis for classical statistical methods, and are more suitable for field data and simulation results as they are highly autocorrelated. The validation methods are demonstrated using two sets of field data, NGSIM data for I-80 in Emeryville, CA, and FHWA data for I-95 on Baltimore-Washington Parkway using two popular microscopic simulation models, VISSIM and AIMSUN. |
| type | Article - Conference proceedings |
| type.DCMIType | text |
| rights | Pre-print: Can be archived Post-print:Can be archived |
| rights | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. |
| rights.URI | |
| relation.isPartOf | Transportation Research Board 87th Annual Meeting |
| date.available | 2008-06-16T21:01:08Z |
| identifier.persist.URI |