Online optimization with look-ahead for freeway emergency vehicle dispatching considering availability

•Online dispatching minimizing a sequence of emergency responses.•Network dependency with probability distribution of secondary incidents.•The lookahead online algorithm is compared with other dispatching policies.•Server availability is considered by estimating service times of each request.•Dispat...

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Vydáno v:Transportation research. Part C, Emerging technologies Ročník 109; číslo C; s. 95 - 116
Hlavní autoři: Park, Hyoshin, Waddell, Deion, Haghani, Ali
Médium: Journal Article
Jazyk:angličtina
Vydáno: United Kingdom Elsevier Ltd 01.12.2019
Elsevier
Témata:
Emergency response
Nearest neighbor algorithm
Online optimization
Secondary incidents
Service time
Work function algorithm
Work function algorithm
Online optimization
Service time
Secondary incidents
Emergency response
Nearest neighbor algorithm
ISSN:0968-090X, 1879-2359
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Shrnutí:•Online dispatching minimizing a sequence of emergency responses.•Network dependency with probability distribution of secondary incidents.•The lookahead online algorithm is compared with other dispatching policies.•Server availability is considered by estimating service times of each request.•Dispatching strategies visualized different scenarios. Traditional emergency management studies have made resource allocation decisions to serve the current emergency without knowing which future emergency will be occurring. Different ordered combinations of emergencies result in different performance outcomes. Even though future events can be anticipated, previous studies follow an assumption that events over a time interval are independent. This study follows an assumption that events are interdependent, because speed reduction and rubbernecking due to an initial incident provoke secondary incidents on freeways and the resource availability depends on service times of each request. The misconception that secondary incidents are not common has resulted in overlooking a look-ahead concept. This study is the pioneer in relaxing the structural assumptions of independency during the assignment of servers and approaching the challenge from an operational perspective, online optimization. The main objective is to minimize the time needed to respond to a sequence of requests. We introduce online dispatching strategies with visualization applied in different network sizes, number of requests, and service times to provide insights on model behavior and solution quality. The experimental evidence indicates that the algorithm works well in practice. We envision a new era in which an optimal resource allocation adapts to external events effectively and anticipates the future learning from the past to produce effective solutions.
Bibliografie:USDOE Advanced Research Projects Agency - Energy (ARPA-E)
ISSN:0968-090X
1879-2359
DOI:10.1016/j.trc.2019.09.016