Identifying and illustrating urban traffic congestion, mobility, and accessibility using a GIS

Urban congestion, accessibility, and mobility are important concerns affecting the quality of life in metropolitan areas. It is important that accessibility and mobility should not be compromised while developing strategies to alleviate congestion. The effects of traffic congestion include not only increase travel delays, which result in the increase of travel times, but also impacts energy consumption and air quality. All of these have detrimental effects on the quality of life. In order to develop strategies to alleviate urban congestion, it is necessary to first identify where and when congestion occurs--i.e., the spatial and temporal distribution of congestion. The objective of this research is to demonstrate the application of a geographic information system (GIS) to help identify and illustrate urban congestion, accessibility, and mobility. Definitions of mobility, accessibility, and congestion are presented as well as the advantages of using a GIS. A list of performance measures which are typically used to quantify these transportation functions are discussed. Data required to quantify the performance measures, their sources and integration within a GIS are discussed. Lastly GIS analyses used to quantify the performance measure are discussed. The performance measures used are: (1) non-recurring delay, (2) average vehicle occupancy, (3) business and employee accessibility to transit routes, (4) residential accessibility to transit routes, (5) Transit accessibility to areas of low automobile ownership, and finally (6) travel time. Specific example are presented to illustrate the application of GIS to evaluate the performance measures identified. In turn, these can be used to develop policies and operational strategies to address congestion (and potential congestion), mobility, and accessibility issues in urban areas. Conclusions are the GIS is a viable tool to assist planners and engineers to identify problem areas using already existing data sources.