2 research outputs found
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Transportation planning via location-based social networking data : exploring many-to-many connections
textToday’s metropolitan areas see changes in populations and land development occurring at faster rates than transportation planning can be updated. This dissertation explores the use of a new dataset from the location-based social networking spectrum to analyze origin-destination travel demand within Austin, TX. A detailed exploration of the proposed data source is conducted to determine its overall capabilities with respect to the Austin area demographics. A new methodology is proposed for the creation of origin-destination matrices using a peer-to-peer modeling structure. This methodology is compared against a previously examined and more traditional approach, the doubly-constrained gravity model, to understand the capabilities of both models with various friction functions. Each method is examined within the constructs of the study area’s existing origin-destination matrix by examining the coincidence ratios, mean errors, mean absolute errors, frequency ratios, swap ratios, trip length distributions, zonal trip generation and attraction heat maps, and zonal origin-destination flow patterns. Through multiple measures, this dissertation provides initial interpretations of the robust Foursquare data collected for the Austin area. Based upon the data analytics performed, the Foursquare data source is shown to be capable of providing immensely detailed spatial-temporal data that can be utilized as a supplementary data source to traditional transportation planning data collection methods or in conjunction with other data sources, such as social networking platforms. The examination of the proposed peer-to-peer methodology presented within this dissertation provides a first look at the potential of many-to-many modeling for transportation planning. The peer-to-peer model was found to be superior to the doubly-constrained gravity model with respect to intrazonal trips. Furthermore, the peer-to-peer model was found to better estimate productions, attractions, and zone to zone movements when a linear function was used for long trips, and was computationally more proficient for all models examined.Civil, Architectural, and Environmental Engineerin
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Location-based social networking data : doubly-constrained gravity model origin-destination estimation of the urban travel demand for Austin, TX
textPopulations and land development have the potential to shift as economies change at a rate that is faster than currently employed for updating a transportation plan for a region. This thesis uses the Foursquare location-based social networking check-in data to analyze the origin-destination travel demand for Austin, Texas. A doubly-constrained gravity model has been employed to create an origin-destination model. This model was analyzed in comparison to a singly-constrained gravity model as well as the Capital Area Metropolitan Planning Organization's 2010 Urban Transportation Study's origin-destination matrices through trip length distributions, the zonal origin-destination flow patterns, and the zonal trip generation and attraction heat maps in an effort to validate the methodology.Civil, Architectural, and Environmental Engineerin