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A Case Based Reasoning System for Developing Incident Management and Evacuation Strategies in Rural Areas (2006)Sponsor: Southern Rural Transportation Center As a part of a research team I developed simulation models in PARAMICS for incident management and evacuation strategies for rural South Carolina. Sections of I-85, and I-385 have been selected as a study sites. OD matrices have been developed with help of Matlab using collected volumes and speed data. The travel time data was used to calibrate and validate the models. Case Based Reasoning was then used to develop evacuation strategies for Incident management.
Benefit/Cost Analysis of Accelerated Incident Clearance Sponsor: South Carolina Department of Transportation (2005 - 2006) The research attempts to examine the feasibility of Artificial Intelligence (AI) paradigm as a decision support tool. Case Based Reasoning (CBR) and Support Vector Regression (SVR) have been used to create AI models. PARAMICS has been used to recreate on-site conditions and run simulations. A Section of I- 85, from exit 66 to exit 70 and another section of I-385, from exit 16 to exit 22, have been chosen to represent on-site conditions. VB coding was used generate multiple cases from the study network. All the cases were then simulated to create output training parameter (i.e. time saving rate) for SVR and CBR models. The models were then calibrated. Validation was done using the Vermont network created by Rutgers University.
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