A Method to Enhance the Performance of Synthetic Origin-Destination (O-D) Trip Table Estimation Models

Abstract

The conventional methods of determining origin-destination (O-D) trip tables involve elaborate surveys, e.g., home interviews, that require considerable time, staff, and funds. To overcome this drawback, a number of theoretical models that synthesize O-D trip tables from link volume data have been developed. The focus of the research reported here was on two of these models The Highway Emulator (THE) and the Linear Programming (LP) model. These models use target/seed tables for guiding the development of output trip tables. In earlier research conducted by the Virginia Tech Center for Transportation Research for the Virginia Transportation Research Council, it was determined that the performance of these models could potentially be enhanced by using a superior target/seed table. The research in this report uses readily available socioeconomic data and link volume information to develop a methodology for obtaining an enhanced target/seed table through application of the trip generation and trip distribution steps of the four-step planning process. The enhanced table was then used as the target/seed to THE and LP models, and their performance evaluated. In addition to measuring the closeness of the output tables to surveyed tables and their capability to replicate observed volumes, their improvements over the case when a structural table is used as target was also studied. Tests showed that the use of the enhanced target/seed table significantly improved the performance of the LP model. However, mixed trends were obtained for THE.