Investigation of the Influence of Boundary Data Assignment on the Development of Multimodal Macro-level Collision Prediction Models (CPMs)
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Collision counts data has shown that significant proportion of collisions occur frequently on the boundary of Traffic analysis zones (TAZs). Consequently, the way in which collisions, and also other geocoded data, along TAZs’ boundaries are assigned into adjacent zones is of interest because it has direct impact on the prediction ability of macro-level CPMs. In this study, data for 422 TAZs from the City of Ottawa was used to develop macro-level CPMs. Geocoded data on TAZ’s boundary were assigned between adjacent TAZs using ten different assignment methods. Models to predict total, non-fatal injury, fatal, property damage only (PDO), bike-involved, and pedestrian-involved collisions were developed. The collisions were related to four categories of independent variables. Results of the developed models show that different geocoded boundary data assignment methods do affect the accuracy of developed CPMs results significantly. It was found that allocating boundary data to TAZs evenly improved model results significantly.
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Copyright © 2014 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.
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- 2014
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ihssian-investigationoftheinfluenceofboundarydata.pdf | 2023-05-04 | Public | Download |