Dey, Kakan Chandra ; Mashrur (Ronnie) Chowdhury; Plaban Das;
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This study estimated risks associated with the failure of autonomous vehicles in mixed traffic streams to develop mitigation strategies. The three components of the analysis included risk identification, risk estimation and evaluation. Since autonomous vehicles will share the roadways with human drivers for a certain number of years after their deployment, transportation infrastructure is an important component of the final risk analysis. A graphical tool in the form of a fault tree model was developed to explore the causes of system level failures for each vehicular component failure (i.e., sensors, actuators and communication platforms) and each transportation infrastructure component failure. The failure probabilities were estimated by a literature review, publicly available information, and survey results from subject matter experts.  Based on the cut sets (hierarchical sequence of events) from the fault tree analysis, 22 strategies that would minimize the failure probability of autonomous vehicles were identified and evaluated using benefit-cost (B/C) analysis.

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Prepared by Rowan University for UTRC
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Risk Analysis of Autonomous Vehicles in Mixed Traffic Streams
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