Improving the Estimation of Travel Demand for Traffic Simulation, Part 2
University of Minnesota, Center for Transportation Studies, 2004 - Computer algorithms - 95 pages
This report examined several methods for estimating Origin-Destination (OD) matrices for freeways using loop detector data. Least squares based methods were compared in terms of both off-line and on-line estimation. Simulated data and observed data were used for evaluating the static and recursive estimators. For off-line estimation, four fully constrained least squares methods were compared. The results showed that the variations of a constrained least squares approach produced more efficient estimates. For on-line estimation, two recursive least squares algorithms were examined. The first method extends Kalman Filtering to satisfy the natural constraints of the OD split parameters. The second was developed from sequential quadratic programming. These algorithms showed different capabilities to capture an abrupt change in the split parameters. Practical recommendations of the choice of different algorithms are given.
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abrupt change algorithm Assumed OD matrix Average bias and efﬁciency binomial distribution conﬁdence interval constrained least squares convergence data set DelﬁOD DelftOD demand uncertainty double precision end do call end do end end for i=1 endif end equality constraints equation estimated OD matrix Figure B.l Filter ﬁrst forecast uncertainty freeway i=1 nor*ndes i=l,nor Initial solution j=l ndes Kalman ﬁlter least squares-based methods line estimation linear model linear trafﬁc model mainline Measures of Bias Measures of forecast network with data objective function off-line estimation off-ramp on-ramp counts one-minute data optimization method optimization routine parameter uncertainty pattem ramp counts real network Recursive Least Squares Results of RLS Results of SQP RSQP satisﬁed Sequential Quadratic Programming simulated network simulation and optimization speciﬁed split parameters standard deviations subroutine TCLS Time-series plot trafﬁc counts trafﬁc ﬂow trafﬁc volumes Transportation Research travel demand true OD matrix true value uncertainty for data variables vehicles WCLS