Dynamic Routing of Unmanned Aerial and Emergency Team Incident Management
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, the model reports a 5.26% improvement in response time compared to the distributed constraint optimization problem (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 this 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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Supplemental Notes:
- This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program. Cover title: Dynamic Routing of Unmanned Aerial and Emergency Response Team Incident Management.
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Corporate Authors:
Center for Advanced Transportation Mobility
North Carolina Agricultural and Technical State University
Greensboro, NC United States 27411Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Authors:
- Park, Hyoshin
- Yi, Sun
- Alden, Andy
- Publication Date: 2022-2
Language
- English
Media Info
- Media Type: Digital/other
- Edition: Final Report
- Features: Appendices; Figures; References; Tables;
- Pagination: 61p
Subject/Index Terms
- TRT Terms: Drones; Emergency response time; Emergency vehicles; Incident management; Markov chains; Routing; Secondary crashes
- Subject Areas: Highways; Planning and Forecasting; Safety and Human Factors; Vehicles and Equipment;
Filing Info
- Accession Number: 01848900
- Record Type: Publication
- Report/Paper Numbers: CATM-2022-R2-NCAT
- Contract Numbers: 69A3551747125
- Files: UTC, NTL, TRIS, ATRI, USDOT
- Created Date: Jun 21 2022 10:28AM