The Value of Calibration and Validation of Probabilistic Discretionary Lane-change Models
Lane changes are important in traffic flow operations. They cause differences in flow over lanes and they may determine the onset of congestion. Therefore, it is relevant to have a lane change model for which the predictive power is confirmed. This article calibrates and validates a probabilistic discretionary lane change model, both microscopically and macroscopically. This is done using traffic flow variables related to lane changing, which was possible due to a large data set where lane changes have been recorded. It is shown the model can be claimed calibrated with accurate parameter estimates using a maximum likelihood method following the current state of the practice. However, careful interpretation of the validation shows that the resulting model is not at all representing reality. It therefore is concluded that lane change models must be validated before they can be used, and the quality should be assessed by physically sound measures.
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Supplemental Notes:
- This paper was sponsored by TRB committee AHB45 Traffic Flow Theory and Characteristics.
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Corporate Authors:
500 Fifth Street, NW
Washington, DC United States 20001 -
Authors:
- Knoop, V L
- Buisson, C
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Conference:
- Transportation Research Board 93rd Annual Meeting
- Location: Washington DC
- Date: 2014-1-12 to 2014-1-16
- Date: 2014
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; References; Tables;
- Pagination: 16p
- Monograph Title: TRB 93rd Annual Meeting Compendium of Papers
Subject/Index Terms
- TRT Terms: Calibration; Lane changing; Probability; Stochastic processes; Traffic models; Validation
- Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; I71: Traffic Theory; I72: Traffic and Transport Planning;
Filing Info
- Accession Number: 01520796
- Record Type: Publication
- Report/Paper Numbers: 14-0103
- Files: TRIS, TRB, ATRI
- Created Date: Apr 2 2014 9:39AM