Development of an adaptive origin-destination estimation methodology considering traffic operational characteristics

Origin-destination (OD) trip matrices can provide traffic patterns that are crucial for transportation planning and traffic operational analysis. This paper applies an operational based platform for conducting capacity constrained OD estimation. It is tested on a 13-mile freeway section of state highway in California with an exclusive HOV lane, truck restricted lane, and mixed SOV/HOV/truck lane. Based on seed matrices created by TransCAD ODME, the observed traffic datasets including automatic traffic recorder (ATR) on highways, turning counts at on- or off-ramps are fed into Paramics estimator for OD estimation. A hybrid approach is taken to iteratively train the OD matrices with multiple vehicle classes. Later, the estimated OD tables are checked in the simulation model to evaluate their accuracy. The close match between the simulated flow and the observed traffic attests to the superior performance of this proposed method for OD estimation.