United States Department of Transportation
i
Dynamic Routing of Unmanned Aerial and Emergency Team Incident Management
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2022-02-01
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[PDF-2.42 MB]
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Edition:Final Report: Feb 2019 –Feb 2022
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Abstract:This study develops a proactive, dynamic emergency resource allocation framework to overcome the limitations of nearest methods while incorporating Unmanned Aerial Vehicles (UAVs) and crash dependencies. In the first part of study, the UAVs’ role includes exploring uncertain traffic conditions, detecting unexpected events, and augmenting information gained from roadway traffic sensors. Resources are relocated in anticipation of future highway incidents and dispatched in response to a highway incident request. To find the optimal assignment of vehicles, the proposed model is solved using the Maximum Gain Method, further improved by incorporating an exploration heuristics. Overall, our model reports a 5.26% improvement in response time compared to the DCOP strategy. Aside from UAVs’ assignment to incident locations, the UAVs provide enhanced transportation network coverage by reducing location assignments that result in overlapping observations. In the second part of study, a multivariate second-order Markov model estimates the probability of a secondary crash based on various primary incidents. This analysis will determine and identify if the probability of a secondary crash is higher at a specific location or higher due to a specific type of primary incident. Findings from our analysis can aid in developing countermeasures such as allowing emergency operators to allocate more resources to clear primary incidents quicker, or better prepare for secondary crashes based on the predicted probability of additional incidents.
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