DYNAMIC ORIGIN-DESTINATION FLOWS ESTIMATION FOR FREEWAY CORRIDORS USING GENETIC ALGORITHM

Abstract

Real-time origin-destination (O-D) flows are important input data for most freeway management systems, and very difficult to obtain. This research puts forward two categories of parameter optimization models for estimating dynamic O-D flows in freeway corridors. The proposed models make full use of information from ramp traffic counts and mainline flow measurements, which are provided by surveillance systems. The models also take into account time-varying route travel time, which is estimated by using a recursive method reported in this paper, and realistically formulate the nonlinear dynamic interrelations between O-D fractions and traffic flow measurements. A genetic algorithm is presented to improve the accuracy and operational efficiency necessary for practical applications. The results of simulation experiments indicate that the proposed methods are rather accurate, robust and efficient, and offer the potential for real-time applications.