GIS and Transportation Planning

Two main objectives of transportation planning are to simulate the current traffic volume and to forecast the future traffic volume on a transportation network. Traffic demand modeling typically consists of the following tasks (1)defining traffic analysis zones (TAZs) based on land-use characteristics, (2)building the transportation network, (3)collecting traffic data for calibration, and (4)performing the four-step traffic demand modeling process of trip generation, trip distribution, mode choice, and trip assignment. The first two tasks used to be time-consuming because paper maps and aerial photographs were the primary tools for constructing TAZs and the transportation network. In recent years, transportation planners have used geographic information systems (GIS) to perform the tasks. A GIS is a tool capturing, storing, and analyzing spatial or geo-referenced data. It also has the additional capability in data integration, such as integration of socioeconomic and traffic data for traffic demand modeling. This paper describes our experience of using a GIS to prepare TAZs and the transportation network for an Idaho statewide traffic demand model. ARC/INFO is the GIS software package for our pilot study, Latah County. We have used ARC/INFO to construct TAZs from TIGER files at different spacial scales and to build the transportation network from different data sources. Using AML programs, we have run experiments to automatically assign TAZ controids and centroid connectors, and to measure the effect of centroids and centroid connectors on traffic demand forecast. Overall, GIS has proved to be an efficient and effective tool for our study. It should be noted, however, GIS cannot by itself improve the quality of input data, a critical factor in transportation planning. This paper describes use of GIS to prepare TAZs and the transportation network for an Idaho statewide traffic demand model. Overall, GIS has proved to be an efficient and effective tool. It should be noted, however, GIS cannot by itself improve the quality of input data, a critical factor in transportation planning. 10p.