INTERMODAL CONTAINER PORTS: APPLICATION OF AUTOMATIC VEHICLE CLASSIFICATION SYSTEM FOR COLLECTING TRIP GENERATION DATA

With the evolution of containers and growth in intermodalism, intermodal seaports have experienced a tremendous growth in containerized trade associated with international and domestic trade. With the increase in port activity has come a comparable increase in port landside traffic. The results of a case study of a container port (Houston's Barbours Cut) are reported, and the impact of existing container port operations on urban infrastructure and mobility is addressed. The application of an automatic vehicle classification system used to collect the necessary traffic data is presented. Commercially available photoelectric sensors were used to collect accurate traffic volume and classification data over a period of 7 days. The data collection procedures provide quantitative information on the traffic characteristics of the container port. Mathematical models were then developed to accurately forecast travel demand for use in planning and designing transportation facilities. The results of the analysis provide trip generation rates for both average weekday and peak hour of generator, and they show the variation in traffic demand by vehicle types. The existing trip rates calculated were consistent with the ITE trip generation rates. The other interesting finding is that only 30% of the total traffic were container trucks; the rest were two- and three-axle vehicles.